Overview and Research Opportunities in Energy Management for Port Integrated Energy System

Abstract

Under the background of ‘carbon peak, carbon neutrality’, port energy conservation and emission reduction are imminent. The structure of a green low-carbon port is complex, where the interaction and coupling between heterogeneous energy sources and between the energy system and logistics system are close. The low-carbon technology of port integrated energy system is a research hotspot. This chapter analyzes the current status of port low-carbon operation, including port electricity replacement, renewable energy generation technology, clean fuel application in port and port low-carbon platform development. In view of the close coupling trend of energy and logistics in port integrated energy system, the operation characteristics of different port logistics modes are summarized, the research results of energy-logistics coupling mechanism are sorted out, and the modeling method of quantification of logistics transportation energy is discussed emphatically. The existing flexibility resources of port are summarized, and the related literature on port energy management is reviewed. Finally, this chapter analyzes and prospects the future development direction of the green port comprehensive energy system, to provide a reference for the research on the low-carbon development of ports under the ‘double carbon’ target.

1.1 Introduction

As a strategic pivot and important hub for ocean development and international trade, large ports consume huge amounts of energy and are one of the main sources of global carbon emissions [1]. China has a vast port scale, with seven of the world’s top ten ports located in China [2]. The top ten seaports in China based on their annual container throughput as of 2021 are listed in Table 1.1. Various types of ports along the coast, rivers, and inland waterways are densely distributed in China, forming a systematic networked geographical layout with Shenzhen Port, Shanghai Port, and Tianjin Port as the main hub ports for shipping, Ningbo-Zhoushan Port, Guangzhou Port, Qinhuangdao Port, Qingdao Port, Dalian Port, and Rizhao Port as important regional auxiliary ports for shipping, and other medium and small ports as supplementary ports. Against the backdrop of “carbon peak and carbon neutrality”, energy-saving and emission reduction in ports have become urgent. Relevant institutions such as the International Maritime Organization have introduced a series of regulations to restrict emissions from the shipping industry, and countries are continuously deepening the adjustment of industrial structure to address the problem of high energy consumption and emissions in the water transport industry. The “14th Five-Year Plan” for Green Transportation Development issued by the Ministry of Transport proposes that by 2025, the proportion of new energy container trucks in international hub ports will reach 60%, and the transformation of existing operational ships into electric power facilities will be accelerated. In 2022, the National Development and Reform Commission and ten other ministries jointly issued the “Guiding Opinions on Further Promoting Electrical Energy Substitution”, pointing out the need to deepen the electrification of the transportation sector and promote shore power construction. State Grid Corporation has implemented more than 600 port shore power demonstration projects in the Bohai Rim, southeast coastal large ports, the Yangtze River Delta, Beijing-Hangzhou Grand Canal, and ports along the Yangtze River. Therefore, building low-carbon and green ports, prioritizing the development and utilization of clean energy, and promoting environmental protection are hotspots that urgently need to be studied in China's energy structure upgrading and ecological green development path [3, 4].

Table 1.1 The top ten seaports in China based on their annual container throughput as of 2021

With the development of technology, various renewable energy sources such as solar energy, wind energy, tidal energy, and wave energy have become possible for application in ports [5]. The implementation of projects such as “oil-to-electricity” conversion, shore power, and new energy ships [6, 7] has turned ports into industrial hubs tightly integrated with transportation logistics and energy systems [8]. In this context, the opportunity to replace energy with electricity and construct a low-carbon green port comprehensive energy system not only meets the requirements of the era's development but also represents an inevitable trend in port development. In the future, large-scale operational equipment in green ports will fully adopt electricity substitution technologies [9], resulting in a strong coupling between port logistics and energy systems. Additionally, the port area will encompass various forms of energy, leading to increasingly complex coupling relationships and growing mutual influences between different energy sources and logistics. Under the coupling of multiple systems in logistics and energy, low-carbon methods and technologies for green port comprehensive energy systems have become a current research hotspot [10, 11].

This chapter provides an overview of the development status of low-carbon technologies in ports, focusing on aspects such as electricity substitution, renewable energy generation, and clean fuel applications. It analyzes the operational characteristics of port logistics systems and discusses in detail the coupling mechanisms and modeling methods between energy systems and logistics systems. The article summarizes the typical characteristics of port comprehensive energy systems and existing energy management methods. Finally, based on existing research, it proposes key research directions that urgently need breakthroughs in port comprehensive energy systems.

1.2 Low-Carbon Technology in Ports

1.2.1 Electric Energy Substitution

• (1) Cold-Ironing Technology

Usually, shortly after a ship arrives at a port and docks, the main generator is shut down while the diesel auxiliary generator is turned on to supply power for communication, lighting, ventilation, cargo handling, and other activities. Generally, the auxiliary generator uses cheap and low-quality fuel, resulting in low fuel efficiency, high losses, and high emissions of pollutants, creating a significant “floating chimney” effect at sea [12]. One important measure to reduce emissions during berthing is to use shore power to supply electricity to the vessel instead of using onboard auxiliary engines. Ship shore power technology refers to the practice of shutting down the ship’s own diesel auxiliary generator and using the power system on the dock to provide electricity to the vessel. This way, electrification from shore to ship can be achieved.

Shore power technology has shown significant emission reduction effects and has been gradually applied in multiple ports worldwide, such as Yangshan Port in China [13], Dongguan Port [14], and Jurong Port in Singapore [15]. Studies have shown that the use of shore power technology can reduce global port emissions by 10% [16]. However, the emission reduction effects vary significantly among different ports due to policy differences and variations in charging standards in different countries and regions. According to estimates, the emission reduction proportion of shore power in UK ports is 2% [16], while the emission reduction effect in Kaohsiung Port in Taiwan, China exceeds 57% [17].

The demand for shore power varies among different types of vessels. For bulk carriers, a comparison between shore power and shipboard fuel in literature [18] indicates that shore power has significant economic advantages when the electricity price is below 0.19 USD/kWh, reducing operational costs and energy consumption by up to 75%, providing a win–win solution for shipowners and port authorities. On the other hand, when cruise ships are berthed, a large amount of electricity is required for passenger activities, making the demand for shore power more urgent. A study [19] analyzed cruise ship cases in three different regions and found that the use of shore power can average reduce greenhouse gas emissions by 29.3%. In Norway, France, and Brazil, cruise ports can reduce carbon emissions by 99.5, 84.9, and 85.3%, respectively, through the use of shore power technology.

Although shore power technology has significant advantages in emission reduction, its widespread adoption is still a major challenge. The main obstacles include technological and policy aspects. On the technological side, issues such as power quality, system stability, reliability, safety, and synchronization caused by shore power access need to be addressed [20, 21]. After other industrial or commercial power systems are energized, circuit breakers only trip in maintenance or fault situations, while shore power systems require frequent breaker operations, posing safety hazards to operators. In addition, large-scale port shore power operations often require large substations, with the high-voltage side close to port facilities. In the absence of proper planning, grounding faults on the high-voltage side of substations can cause dangerous contact voltage. At the same time, there are multiple types of ship frequencies. In a country like China where the utility power supply frequency is 50 Hz, frequency conversion is required, which also poses challenges for the synchronization of shore power systems. On the policy side, the degree of marketization of electricity is a key factor restricting the promotion of shore power. Taking China as an example, the electricity regulations clearly state that power companies are the main providers of electricity services, while shore power requires ports to provide power services to vessels, and relevant policies and regulations need to be improved urgently.

• (2) Electrification of Logistics Equipment

Ports need to provide ample logistics services for docked ships through a variety of different types of logistics equipment, including quay cranes (QC), yard cranes (YC), conveyor belts, and transfer vehicles. QC is used for loading and unloading cargo or containers from the ship's side. YC is divided into rail-mounted gantry (RMG) and rubber-tire gantry (RTG), which are used for container loading, unloading, handling, and stacking in the yard. The main difference is that RMG moves on rails, while RTG moves on rubber tires. Conveyor belts are used to handle bulk cargo, such as coal, fertilizer, and wood. Transfer vehicles include reach stackers (RS) for container lifting, straddle carriers (SC) for container transfer, and lift trucks (LT) for cargo lifting and stacking.

Traditionally, these logistics equipment were almost all manually driven. In recent years, highly automated port equipment, such as automated RTG and RMG, have been used to improve efficiency and reduce labor costs [22]. The energy sources for these devices have also become more diversified. Table 1.2 shows the main energy supply methods for the above equipment [23]. From Table 1.2, it can be seen that electricity is the most commonly used energy supply method in ports, which can provide power for all major equipment in the port, and is energy-saving, easy to control, and easy to automate. This makes the electrification of logistics equipment in large ports an irreversible trend.

Table 1.2 Energy source for different equipment

QC can recover energy during the lifting process and store it for later use [24]. Therefore, the integration of electrification and energy storage systems can transfer QC's peak load, improving energy utilization efficiency. Literature [25] used supercapacitors to reduce QC’s peak load from 1211 to 330 kW. Literature [26] reduced QC’s peak load from 1500 to 150 kW by integrating energy storage systems. The transfer of peak load means higher energy efficiency, achieving energy conservation and emission reduction. In terms of YC, RMG usually has higher energy efficiency than traditional RTG because it is electrically driven, but RTG’s advantage is its flexibility in operation, as it is not limited to rails. Therefore, the electrified RTG (E-RTG), which balances the flexibility of RTG operation and the high energy efficiency of RMG, is currently the mainstream trend. Studies have shown that compared with traditional RTGs using diesel as fuel, the energy cost of E-RTGs has decreased by 86.60%, and greenhouse gas emissions have decreased by 67% [27].

For other yard equipment, such as RS, SC, and LT, hybrid diesel-electric engine systems have been integrated. Studies have shown that the fuel efficiency of hybrid SC has increased by 27.1%, and carbon emissions have been reduced by more than 66% [28]. With the development of electrical engineering technology, especially energy storage technology, fully electric RS, SC, and LT will soon become a reality, helping to promote green and low-carbon development in ports [29].

1.2.2 Renewable Energy

Renewable energy includes sources such as solar, wind, tidal, wave, and geothermal energy, among others. Unlike fossil fuels, renewable energy has a fast regeneration rate and does not produce gas emissions. It is an important technological tool in achieving low-carbon ports. In recent years, the use of renewable energy in ports has become increasingly widespread. Literature [30, 31] has studied the importance of renewable energy in establishing low-carbon ports. Literature [32] considers “the percentage of energy from renewable resources” as an important Key Performance Index (KPI) for sustainable intelligent ports. Literature [33] has proposed a creative method of covering the roofs of refrigerated areas with photovoltaic cells, generating electricity for lighting, refrigeration, heating, etc. Covering these areas also shields the containers from direct sunlight, reducing the amount of energy needed for cooling.

In practical engineering applications, more and more ports are considering renewable energy as the main measure to reduce carbon emissions. The port of Chennai in India evaluated the possibility of using photovoltaic power to supply energy to the port area from the perspective of open days, capacity utilization factors, and area available for placing photovoltaic cells, and gradually established test engineering projects [34]. Jurong Port in Singapore proposed the concept of a “zero-carbon” port and installed photovoltaic cells on the roofs of warehouses, creating an annual output of 12 million kWh through a leasing model [35]. The German maritime department emphasized the importance of renewable energy, particularly wind, solar, and geothermal energy, for German ports in a report published in 2017. Hamburg Port installed more than 20 wind turbines with a capacity of 25.4 MW [36]. In addition, Hamburg Port has established a photovoltaic power station with an expected annual output of 500 MWh [37]. Other renewable energies such as geothermal energy [38], tidal energy [39], and wave energy [40] are gradually being applied in ports. These examples indicate that there is enormous potential for the use of renewable energy in ports.

However, the planning and layout of renewable energy in ports still needs to be studied. Taking photovoltaic and wind power as the most widely used examples, the installation location of photovoltaic arrays must have sufficient solar radiation. Rooftop photovoltaics are preferred, so the load requirements for distributed photovoltaic power systems on the roofs of large warehouses and other buildings in newly built port areas must be considered. When installing port wind turbines, factors such as changes in sea conditions, reserved selection ranges for axis lines, navigable widths of entry channels, safety distances between anchorages and navigation channels, scale of anchorages, and safety distances between anchorages and wind farm boundaries must be considered [41]. With the adjustment of port scale, the layout of renewable energy power stations in ports also needs to be adjusted, and a safe, efficient, and economical layout plan is urgently needed.

1.2.3 Clean Fuel

Currently, the maritime transportation industry heavily relies on fossil fuels, especially heavy oil, as a source of power. Substituting low-carbon or even zero-carbon fuels for heavy oil is an important way to achieve decarbonization in the shipping industry. Liquefied natural gas, biomass fuels, and hydrogen energy are currently the most promising clean fuels for shipping.

Some ports have already considered using liquefied natural gas for port equipment. In 2008, the Port of Long Beach evaluated liquefied natural gas fueling facilities [42]. As part of the European Union-funded Green Crane project, multiple ports in Europe evaluated terminal tractors, liquefied natural gas or dual fuel RTGs, and liquefied natural gas-dual fuel RS based on liquefied natural gas fuel. The use of liquefied natural gas for terminal tractors is estimated to reduce carbon dioxide emissions by 16%, while nitrogen oxide emissions will also be reduced [27]. Research in [43] shows that using liquefied natural gas can reduce carbon dioxide emissions by 25% compared to fossil fuels. In addition, the International Maritime Organization has set stricter requirements for marine emissions in the latest International Convention for the Prevention of Pollution from Ships, which clearly stipulates that the global marine fuel sulfur content limit will be reduced from 3.5 to 0.5% from 2020 onwards. Therefore, more and more ships will begin to use clean fuels based on liquefied natural gas.

Biodiesel mixed with diesel is also an important clean fuel in ports. The Port of Rotterdam in the Netherlands produces biodiesel mixed fuel by blending biofuels with diesel fuel currently in use at a ratio of 3:7. The port's biomass fuel throughput reached 4.8 million tons in 2016 and has become a major import and export hub [44]. In this process, port waste is used as a renewable resource for producing biomass fuel.

Although liquefied natural gas and biomass fuels are cleaner than traditional fossil fuels, they are not the best long-term solution because they cannot achieve zero emissions. Hydrogen energy, as a zero-carbon fuel, is the best choice for achieving carbon neutrality in ports.

Hydrogen energy is a high-energy density and long-term storage efficient energy storage method. In terms of energy utilization, the high-capacity and long-term storage mode of hydrogen energy is more sufficient for the use of renewable energy; in terms of scale storage economy, the cost of fixed-scale hydrogen storage is one order of magnitude lower than that of battery storage [45]. The basic principle of hydrogen storage is to electrolyze water to obtain hydrogen and oxygen. Taking wind power as an example, when there is sufficient wind power but it cannot be connected to the grid, hydrogen can be produced by using wind power to electrolyze water and store hydrogen; when energy is needed, the stored hydrogen can be converted into electricity through a hydrogen fuel cell. Ports are renewable energy-intensive areas with abundant water resources. Renewable energy can be used to electrolyze water to produce hydrogen, which can be used to achieve pollution-free and zero-emission hydrogen production and utilization, while solving the problems of wind and solar energy waste [46]. Combining hydrogen storage with new energy generation is an excellent choice to reduce hydrogen storage costs and improve new energy generation utilization. Hydrogen energy can be applied to many scenarios in ports, such as commuting, transportation vehicles, loading and unloading machinery, etc. As a clean energy source with no pollutant emissions and no greenhouse gas emissions, hydrogen energy has become the focus of promoting clean energy use in port loading and unloading production equipment. The Shandong Port “14th Five-Year Plan” for scientific and technological innovation clearly stipulates that in order to build a clean energy system in ports and build a “China Hydrogen Port”, more than two hydrogen refueling stations for port scenarios should be built, with a total hydrogen refueling capacity exceeding 1000 kg/12 h.

Hydrogen fuel cells are a high-efficiency and clean way to convert hydrogen energy into stable electricity. They have already been applied in ports. For example, the Port of Qingdao in Shandong Province has launched the first hydrogen fuel cell vehicle refueling demonstration and operation project in Chinese ports [47]; The Port of Valencia in Spain tested hydrogen gas produced by renewable energy in fuel cell stackers and analyzed methods to improve energy efficiency, performance, and operational safety using fuel cell terminal equipment [48]. Research in [49] analyzed the factors that need to be considered when using hydrogen fuel cell forklifts in green port construction, including safety, facility investment, and cleanliness, pointing out the necessity of applying hydrogen fuel cell forklifts. The ports of Los Angeles and Long Beach evaluated the feasibility of using commercial fuel cells and hydrogen as clean energy sources for various equipment. The research results show that the large-scale application of hydrogen energy in ports is still restricted by low production efficiency, strict storage conditions, limited maturity level of technology, and low return on investment [50]. This is also the focus of future research.

1.2.4 Low-Carbon Port Management

With the abundance of renewable energy and flexible load resources in ports, more and more ports are introducing digital and intelligent technologies to develop low-carbon integrated management platforms. Figure 1.1 shows a schematic diagram of the integrated carbon reduction work of the low-carbon platform load source network in ports. Generally speaking, low-carbon platforms mainly monitor, control, analyze, and optimize port resources to help promote green and low-carbon development in ports. Figure 1.1 centers around the low-carbon platform and achieves centralized and distributed energy generation, multi-directional flow, and real-time data management. Literature [51] provides a construction roadmap for the port low-carbon platform project, which mainly includes the initial stage and installation stage. The initial stage includes: (1) equipment load analysis; (2) analysis of the intelligent grid scenario in the port; (3) energy balance; (4) benefit analysis. The installation stage includes: (1) analysis of renewable energy and evaluation of daily fluctuations in energy generation; (2) optimization of peak shaving and demand response plans; (3) planning of energy storage; (4) management of electricity prices and costs.

Fig. 1.1

Schematic diagram of port low-carbon platform

The low-carbon management platform uses key technologies to balance energy supply and demand in an intelligent way. The port low-carbon management platform mainly includes four pillars: (1) energy supply (electricity generation) management, including on-site renewable energy generation, cogeneration, and grid management; (2) battery energy storage capacity; (3) energy demand management, using real-time energy consumption measurement, electrified equipment, and shore power; (4) optimization management and communication of all active resources in the grid through optimization methods, load chart control, peak shaving, and utilization management. Literature [52] proposes an intelligent port low-carbon energy management system composed of microgrids and overall energy planning, and discusses the importance of permanent design, energy efficiency, operational efficiency, and architectural efficiency in overall energy planning. Literature [53] designs a port-grid comprehensive platform composed of sensor technology, advanced smart meters, real-time monitoring systems, control tools, battery technology, and communication technology to optimize port energy demand control and flexibility management. Literature [54] introduces the real-time transmission platform for energy consumption data in the stacking operation of Koper Port in Europe, which achieved a year-round power saving of 281 MWh and fuel saving of 311 tons in the port. Literature [55] proposes an intelligent port energy management system composed of microgrids and overall energy planning platforms, which can reduce port energy consumption and effectively reduce carbon emissions by monitoring the energy efficiency of port equipment facilities, terminal buildings, and other port facilities. In addition, the digital port information platform developed by Singapore Port can provide real-time information for upstream and downstream enterprises in port activities to better coordinate, plan, and allocate port resources [56]. Digital and intelligent technologies will be the backbone of low-carbon management platforms in ports.

1.3 Coupling Mechanism and Modeling for Energy and Logistics

Logistics transportation is the main responsibility of ports, which usually includes operations such as allocating berths and managing container transportation, refrigerated container management, etc. Different logistics operation modes have significant impacts on the distribution of port loads, which in turn affects port energy distribution and system operation. It is necessary to study the coupling relationship between port logistics operations and energy scheduling, as well as the energy modeling method of logistics operations.

1.3.1 Characteristics of Port Logistics Transportation

Terminal operations include allocating berth space and service time for loading and unloading ships, which are usually referred to as berth allocation problems (BAP) [57, 58]. The transfer of goods requires coordination between port equipment such as quay cranes, yard equipment such as stack cranes, and cargo loading and unloading equipment [59]. Therefore, the entire terminal operation is a comprehensive logistics problem, and the operator usually aims to maximize the efficiency and throughput of the port to obtain better economic benefits.

BAP is the focus of port operation scheduling, which determines the berthing position and time of moored ships. Currently, a large amount of research has been conducted on the berth allocation problem in ports. In [60], the impact of uncertain factors such as the arrival and operation time of moored ships on berth allocation was considered, and multi-objective optimization of BAP was achieved based on robust optimization. In [61], the existing BAP formula was modified to address the issue of priority for moored ships. In [62], the problem of dynamic berth allocation for ships was solved in a public berth system. In [63], the risk measure of the given berth timetable was minimized by considering berth productivity while minimizing the total service time of all ships. In [62], the dynamic berth allocation model was first formulated as mixed integer linear programming (MILP), and then extended to the quay crane assignment model in [64]. In [65], the optimal berth allocation model was formulated to minimize the total service time of all-electric ships, and solved using a particle swarm optimization method. In [66], a novel berth allocation model was proposed, which had effective inequalities and rolling horizon heuristics to improve problem-solving efficiency.

In the above berth allocation process, the actual berthing time of the ship depends on the number of allocated quay cranes and the processing speed of quay cranes for containers. Therefore, the berth allocation problem is usually combined with the quay crane allocation problem (QCAP) [66,67,68,69,70,71,72,73,74,75,76,77,78]. In [66], a detailed model of crane scheduling considering container groups, non-crossing constraints, and safety distance was proposed for the first time. In [67], an integrated BAP and QCAP was considered, and a berth allocation model based on relative position formula was proposed.

There is also a refrigeration demand in the port transportation process, and the refrigerated area consumes a large amount of electricity. Refrigerated containers must have external power supply, which is also an important energy consumption link. Efficient management of refrigerated containers meets the needs of ships and also reduces related costs. In [79], a spatio-temporal model suitable for relocating refrigerated containers was proposed. In [80], a scheduling method and simulation model of refrigeration-related processes were constructed in a realistic dynamic framework.

Most of the above research is based on the perspective of port logistics management and transportation, aiming to maximize logistics transportation efficiency, and energy problems in logistics transportation are not involved.

1.3.2 Coupling Mechanism of Energy and Logistics

With the increasing electrification level of ports, the coupling between logistics and energy systems is becoming increasingly tight. The close coupling of logistics and energy is an important trend in this special scenario of ports, but it also brings new problems in the port operation process. For example, when a ship docks and uses shore power, the docking time of the ship will affect the time distribution of the shore power load, and the berth (corresponding to the grid node number) determines the spatial distribution of the shore power load. In addition, ship docking brings a series of additional loads, mainly the power load of loading and unloading machinery (such as shore cranes and yard cranes). The docking time and position of the ship further determine the temporal and spatial distribution of the shore cranes, that is, the loading and unloading machinery work when the ship docks, and they are idle when the ship leaves, as shown in Fig. 1.2. Subsequently, new energy container trucks transport containers from the terminal to the yard, and the charging and discharging load of new energy forklifts is closely related to the operation path and time. In the yard, new energy forklifts and yard cranes handle the container transportation, and the charging and discharging load of new energy forklifts is similar to that of new energy container trucks, while the load of yard cranes is related to the frequency of container transportation. It can be seen that the operation mode of the logistics system determines the distribution of power load.

Fig. 1.2

Logistics and power interaction between ship and port during single berthing

On the other hand, the dispatching of the energy system also has a reverse effect on the operation of the port logistics system. The economic operation of the energy system requires the promotion of renewable energy consumption and the realization of source-load matching. By flexibly adjusting the operational methods of the logistics system, such as berth and gantry allocation, changing the temporal and spatial distribution of port logistics load can achieve the matching between logistics load and renewable energy generation. Thus, more logistics load can be supplied by renewable energy, reducing the energy consumption cost of the port energy system. Therefore, the output of renewable energy and the dispatching of the energy system will also have an impact on the operation of the port logistics system. Based on the above two points, it can be seen that port logistics transportation and energy dispatching are closely coupled and interact with each other, which is a significant characteristic of the comprehensive energy system of the port.

1.3.3 Energy-Based Modeling of Logistics

The port logistics system and energy system have different operating characteristics. In order to achieve the coordinated operation of port logistics and energy, it is necessary to establish a quantitative model of port logistics operations.

In current research, in order to associate logistics scheduling with power demand, the common practice is to introduce 0–1 variables to represent the status of ships in port and the operation status of shore cranes and yard cranes. These 0–1 variables are coupled with berth allocation and shore crane scheduling related variables, subject to logistics operation constraints, and can therefore represent the logistics operation process. At the same time, multiplying these 0–1 variables by the rated power of ships and shore cranes can obtain the ship-to-shore power load and shore crane workload related to logistics operations. Therefore, these 0–1 variables can reflect the characteristics of logistics operations and represent the power demand of ships and shore cranes, thereby obtaining a quantitative model of the port logistics system. In [81], the author introduced 0–1 variables to represent the ship’s berthing status, associated these variables with berth allocation and shore crane scheduling, and modeled the ship and shore crane power load using these variables, achieving quantitative modeling of ship logistics operations. Similarly, Literatures [82] and [83] both modeled the state of logistics equipment such as ships, shore cranes, and yard cranes by introducing 0–1 state variables, associating them with logistics operation constraints, and using them to represent the power load demand of logistics equipment.

• (1) Ships

In the above literature, the state variables of ships are the key to coupling logistics transportation and energy scheduling. Next, we will give an example of how to model the state variables of ships to couple logistics transportation and energy scheduling [81].

Let X_j(t) denote the status of ship j in the port, where X_j(t) = 0 before and after the ship berths, and X_j(t) = 1 during the ship's stay in the port. Within a single scheduling period, the ship’s status in the port can be expressed as shown in Eq. (1.1):

$$X_{j} \left( t \right) = \left\{ {\begin{array}{*{20}l} {0,\quad t \in \left[ {1,t_{1} } \right]} \hfill \\ {1,\quad t \in \left[ {t_{1} ,t_{{{\text{leave}}}} } \right]} \hfill \\ {0,\quad t \in \left[ {t_{{{\text{leave}}}} ,T} \right]} \hfill \\ \end{array} } \right.$$

(1.1)

where t₁ is the time when the ship arrives at the port, and t_leave is the time when the ship leaves the port.

Based on (1.1), the energy demand of ships can be expressed as:

$$\begin{array}{*{20}c} {P_{{{\text{ship}}}} \left( t \right) = P_{{{\text{ship}}}}^{{{\text{rated}}}} X_{j} \left( t \right)} \\ \end{array}$$

(1.2)

where the ship’s power demand changing over time is expressed as the product of rated power and state variable. For a reefer ship, its power demand $P_{{{\text{ship}}}}^{{{\text{rated}}}}$ should also include the refrigeration power of reefers.

The ship’s time window in port is related to the allocation of quay cranes. Meanwhile, the port will be informed in advance of the ship’s arrival, so the arrival time of the ship is known. After the ship arrives at the port, it will not immediately berth, but will wait in the anchorage area for port scheduling. The relationship between the time of arrival, time of berthing and time of departure is shown in (1.3). The time of departure t_leave is determined by the time of arrival, the amount of cargo loaded and unloaded and the number of quay cranes allocated, as shown in (1.4):

$$\begin{array}{*{20}c} {t_{0} \le t_{1} \le t_{leave} } \\ \end{array}$$

(1.3)

$$\begin{array}{*{20}c} {t_{{{\text{leave}}}} = t_{1} + \left[ {\frac{{N_{j} }}{{\eta \times C_{j} }}} \right]_{{{\text{up}}}} } \\ \end{array}$$

(1.4)

where t₀ is the time when the ship arrives at the port. N_j is the quantity of containers loaded and unloaded by the ship, and the unit is TEU. η is the loading and unloading efficiency of the quay crane, and the unit is per TEU/hour. C_j is the allocated number of quay cranes, and [·]_up means rounding up.

Equation (1.4) shows the basic relationship between the ship's time window in port and the number of allocated quay cranes. Ship logistics modeling is closely related to quay crane allocation, which requires further modeling of the quay crane.

• (2) Quay Cranes

For quay cranes, their operating status can be represented by introducing new 0–1 variables. Considering the close relationship between quay crane behavior and ship berthing, ship state variables are directly used to model quay cranes to reduce the variable size.

Due to the restrictions on ship length and cargo handling capacity, the number of quay cranes that can be accommodated is limited, and the number of allocated quay cranes cannot exceed the minimum and maximum quay crane demand limits of the ship, as shown in (1.5). At the same time, due to the limited quay cranes, the total number of quay cranes in operation at a certain time cannot exceed the total number of quay crane resources C_max, as shown in (1.6).

$$\begin{array}{*{20}c} {C_{j}^{{{\text{min}}}} \le C_{j} \le C_{j}^{{{\text{max}}}} } \\ \end{array}$$

(1.5)

$$\begin{array}{*{20}c} {\mathop \sum \limits_{j = 1}^{n} X_{j} \left( t \right)C_{j} \le C_{{{\text{max}}}} } \\ \end{array}$$

(1.6)

The above formulas provide the basic logistics relationship that ships and quay cranes must meet. Based on this, other detailed berth allocation formulas and quay crane scheduling formulas can be expanded on the basis of the above formulas to further model the logistics operation process in a more detailed manner.

Based on ship state variables, the power expression of a single quay crane can be further obtained:

$$\begin{array}{*{20}c} {P_{{{\text{crane}}}} \left( t \right) = P_{{{\text{crane}}}}^{{{\text{rated}}}} C_{j} X_{j} \left( t \right)} \\ \end{array}$$

(1.7)

where the time-varying power demand of quay crane is expressed as the product of rated power and state variable.

Combined with Sects. 1.3.1 and 1.3.2, it can be seen that the state variables of ships and quay cranes are affected by logistics-related constraints. Therefore, the power demand of ships and quay cranes are highly correlated with the characteristics of logistics operations. The energy-based modeling of logistics operations involving ships and quay cranes must be taken into consideration.

The above modeling process indicates the basic idea of energy-based modeling of port logistics operations. By introducing state variables to represent the working status of logistics machinery and associating the working status with logistics-related constraints, the introduced state variables can reflect the logistics operation characteristics of the equipment. On this basis, through expressions similar to Eqs. (1.2) and (1.7), the energy demand of logistics equipment can be achieved by using the introduced state variables.

• (3) New Energy Container Trucks

New energy container trucks are one of the main equipment connecting the port and the storage yard. The truck transports cargo between the port and the yard while consuming a certain amount of energy, realizing the coupling between logistics and energy. At present, there is still a lack of corresponding research on the logistics—energy coupling modeling of new energy vehicles. This section presents the preliminary modeling method.

The 0–1 variable π_i,t, σ_i,t and λ_i,t are used to indicate that the new energy container truck is in the state of transfer, charging and rest. The 0–1 variable β_j,t represents whether the truck is on the path j. The state constraint of the new energy container truck can be expressed as:

$$\begin{array}{*{20}c} {\left\{ {\begin{array}{*{20}c} {\pi_{i,t} + \sigma_{i,t} + \lambda_{i,t} = 1} \\ {\mathop \sum \limits_{t}^{T} \mathop \sum \limits_{i = 1}^{M} \pi_{i,t} L_{i} \ge L} \\ \end{array} } \right.} \\ \end{array}$$

(1.8)

where M is the total number of new energy container trucks. L_i is the transfer capacity of a single new energy container truck within a unit time. L is the total number of transfer tasks within the dispatching cycle. The constraint in the first row represents that each new energy container truck must be in a certain state. The constraint in the second row represents that the transportation volume of all new energy container trucks must meet the total task requirements within the scheduling cycle T.

In addition, there are multiple routes for new energy container trucks to transfer between the wharf and the storage yard. The path selection constraints are as follows:

$$\begin{array}{*{20}c} {\left\{ {\begin{array}{*{20}l} {\mathop \sum \limits_{j}^{J} \beta_{i,j,t} \le 1} \hfill \\ {\beta_{i,j,t} \le \pi_{i,t} } \hfill \\ {\mathop \sum \limits_{i = 1}^{M} \beta_{i,j,t} R_{i} \le R_{j} } \hfill \\ \end{array} } \right.} \\ \end{array}$$

(1.9)

where the first-row constraint means that each new energy container truck can only select one path. The second-row constraint means that only the truck in working state can select the transfer path. The third-row constraint represents the transportation bearing capacity of a certain path. The sum of bearing capacity of all the trucks occupying the path j must be less than the total bearing capacity of the path.

Based on the above model, the energy consumption of the new energy container truck can be further obtained:

$$\begin{array}{*{20}c} {\left\{ {\begin{array}{*{20}c} {\mathop \sum \limits_{t}^{T} \pi_{i,t} P_{i}^{{{\text{trans}}}} = \mathop \sum \limits_{t}^{T} \sigma_{i,t} P_{i}^{{{\text{ch}}}} } \\ {P_{i,t} = \sigma_{i,t} P_{i}^{{{\text{ch}}}} } \\ \end{array} } \right.} \\ \end{array}$$

(1.10)

where $P_{i}^{{{\text{trans}}}}$ and $P_{i}^{{{\text{ch}}}}$ are respectively the transfer power and charging power of a single truck. $P_{i,t}$ is the charging power of a single truck at every moment. The first-row constraint represents that the total energy consumption of the new energy container truck in the dispatching cycle T is equal to the charging energy, namely, the power balance constraint. The second-row constraint represents the power load of the truck from the perspective of the energy side. The truck will have an impact on the energy side only during the charging period, and will not have an impact on the energy side scheduling in the state of transfer and rest.

Simple modeling can be achieved by introducing 0–1 variables to the logistics and energy consumption constraints of the new energy container truck. Due to the complex port logistics, more detailed modeling of the new energy container truck requires detailed parameters of the logistics transfer model and the charging and discharging model.

• (4) Belt Conveyors

The quantitative modeling of belt function is similar to that of ships and quay cranes. It models the transmission speed of the belt conveyor by introducing 0–1 variables, and further associates the transmission power with the speed based on this.

Assuming there are N speed intervals for the belt conveyor, and the transmission speed in each interval is represented by V_i. Introduce 0–1 variables α_i,t for each speed interval, representing that the belt conveyor is currently in this speed interval at time t. Then the transmission speed of the belt conveyor at time t can be represented as follows:

$$\begin{array}{*{20}c} {\left\{ {\begin{array}{*{20}c} {V_{t} = \mathop \sum \limits_{i = 1}^{N} \alpha_{i,t} V_{i} } \\ {\mathop \sum \limits_{i = 1}^{N} \alpha_{i,t} = 1} \\ \end{array} } \right.} \\ \end{array}$$

(1.11)

In (1.11), the first line represents the transmission speed of the belt conveyor at time t, and the second line limits the belt conveyor at time t to only be in a speed range.

Based on (1.11) and using the linearization model pointed out in [84], the transmission power of the belt conveyor at time [84] t can be obtained as follows:

$$\begin{array}{*{20}c} {P_{t} = kV_{t} + b} \\ \end{array}$$

(1.12)

The logistics transportation task of belt conveyor is to complete a certain amount of transportation within a specified time T. The modeling is as follows:

$$\begin{array}{*{20}c} {\mathop \sum \limits_{t = 1}^{T} V_{t} L^{0} = L^{1} } \\ \end{array}$$

(1.13)

where L⁰ represents the transportation capacity of the belt conveyor in unit time. L¹ represents the total transportation volume that the belt conveyor needs to complete in the specified time T.

From (1.11) and (1.12), it can be seen that the power demand of belt conveyor is coupled with the logistics operation constraint through the transport speed V_i. The quantitative modeling of belt function considering the logistics constraint is realized.

• (5) Refrigerated Container Parks

There is a refrigerated area in the port yard, and although the refrigeration power of the refrigerated containers is relatively independent of logistics transportation, it is still an important energy consumption link in the port. The temperature change of the refrigerated containers is coupled with the refrigeration power, which can be compared to the coupling relationship between the state of charge (SOC) of an energy storage battery and the charging power. When the refrigerated container loses power, its temperature rise rate is related to environmental temperature and its own parameters; when the refrigerated container is being charged, its temperature decrease rate is related to the charging power and its own parameters. Therefore, the relationship between the temperature of the refrigerated container and the charging power can be expressed as:

$$\begin{array}{*{20}c} {T_{t + \Delta t} - T_{t} = I_{{{\text{off}}}} \Delta T_{{\text{d}}} \left( {1 - e^{{ - c_{1} \times \Delta t}} } \right) - I_{{{\text{on}}}} c_{2} P_{{\text{t}}}^{{{\text{ch}}}} \Delta t} \\ \end{array}$$

(1.14)

where T_t is the temperature of the reefer at time t. $\Delta T_{{\text{d}}}$ is the difference between the internal temperature of the reefer and the ambient temperature. I_on and I_off are 0–1 variables indicating the opening and closing of the reefer respectively. c₁ and [85] c₂ are the correlation coefficients, whose specific values can be referred to in [85]. $P_{t}^{{{\text{ch}}}}$ is the charging power of the reefer at time t.

The above model is a preliminary idea for quantifying the energy consumption in port logistics operations. With the implementation of green and low-carbon projects in ports, ports have become a common node where the three networks of energy, shipping, and logistics intersect. Large-scale equipment in the green port will fully adopt electric energy substitution technology, and the port logistics system and energy system will present strong coupling. However, a large number of discrete variables make it difficult to solve the optimization model, so it is necessary to continue to explore efficient model solving methods.

1.4 Energy Management of Green Port Integrated Energy System

With the development and maturity of low-carbon technologies, the application of electric energy substitution, renewable energy generation, and clean fuels has gradually been introduced into various ports. At the same time, the energy system and logistics system are deeply integrated, forming the Green Port Integrated Energy System. Through efficient energy management of the integrated energy system, the low-carbon development of the port can be achieved.

1.4.1 Port Integrated Energy System

As a typical representative of concentrated energy consumption in industrial production, ports have the characteristics of high energy consumption, high pollution, complex external environment, and resource-intensive, resulting in severe pollution emissions. Building low-carbon and green ports is a key area that urgently needs to be studied for upgrading the energy structure and promoting ecological green development in China. With the development of technology, the application of various renewable energies such as wind energy, solar energy, and tidal energy in ports has become possible [5]. The implementation of projects such as “oil-to-electricity,” “shore power,” and “low-carbon ships” also makes ports become industrial hubs closely integrated with energy systems and logistics systems. Against this backdrop, the construction of a low-carbon port integrated energy system is not only in line with the requirements of the times but is also an inevitable trend for port development.

The integrated energy system of ports is aimed at the loads of electricity, heat, natural gas, hydrogen, and other loads within the port area. Based on the complementary characteristics of multiple energy types and the principle of energy cascade utilization, the energy system and logistics system are unified in planning and coordinated optimization of operation. This is an important way to improve energy utilization efficiency and reduce carbon emissions in the port area. The schematic diagram of the integrated energy system of ports is shown in Fig. 1.3. Countries with abundant port resources such as Europe, America, and China have already legislated or are in the process of legislating that large-scale port equipment in the future will fully adopt electric energy substitution technology and provide energy through the power grid. At the same time, the integrated energy system of ports will also supply heat, natural gas, and hydrogen to users through infrastructure such as heating networks, gas supply networks, and hydrogen refueling stations to meet various energy needs. In the transmission process of electricity, heat, gas, and hydrogen, the integrated energy system of ports couples electric energy, thermal energy, and cooling energy through combined cooling heating and power (CCHP) units; connects the power grid and hydrogen through power-to-hydrogen technology; realizes the conversion of hydrogen to natural gas through methaneization devices; and supplements heat energy shortage through equipment such as gas boilers and fuel cells. When the energy supply and demand of the system are unbalanced, surplus or insufficient energy can be stored or supplemented through energy storage devices of various energy forms (electricity storage, gas storage, heat storage, etc.) to achieve the energy dynamic balance of the port area.

Fig. 1.3

Schematic diagram of integrated port energy system

1.4.2 Flexible Resources of Green Port

The significant difference between the green port integrated energy system and the traditional integrated energy system is the highly coupled energy system and logistics system, which includes various flexible loads. This makes the port integrated energy system have abundant flexibility resources, which can significantly improve the energy management level of the system after reasonable modeling and optimization scheduling. This section will summarize the application of adjustable flexibility resources in green port energy management from four aspects: energy storage devices, vehicle scheduling, berthing ship scheduling, and refrigerated container scheduling.

• (1) Vehicle Scheduling

Ports require a large number of transportation vehicles in the process of cargo circulation, and the electrification/new energy of transportation vehicles has become a development trend. In Singapore's Jurong Port, electric vehicles have become the main type of transportation vehicles [86]. The Port of Los Angeles in the United States has begun to use hydrogen energy as the power source for container trucks [87]. Reasonably arranging the charging and discharging behavior of transportation vehicles can provide additional flexibility for the port energy system. Literature [88] established a double-layer game model of electric vehicle aggregation merchants integrating electric vehicles to participate in power demand response, which can achieve the multi-subject optimal strategy of electric vehicles and energy suppliers. Literature [89] proposed an ordered charging and discharging scheduling strategy for commercial electric vehicle groups, which can control the number of parked and running vehicles in the electric vehicle group while meeting the operational requirements of commercial vehicles.

• (2) Berthing Ship Sheduling

Ports need to allocate berths for berthing ships to provide various transportation services. Different types of ships have different energy demand, and different berth services have different service objects [90]. Reasonably deploying all berthing ships in the scheduling cycle and allocating different berths can also balance the energy demand of the port at different time periods, thereby providing additional flexibility for the energy system. Literature [91] established a Nash game model, introduced berth parking duration price incentives, and studied the impact of berth bidding on shore power. Literature [92] studied the energy consumption model of belt conveyor system closely related to the loading and unloading behavior of berthing ships and verified the potential of the model to participate in demand response.

• (3) Refrigerated Container Scheduling

With the development of society, the demand for fresh food, plants, and flowers from different regions of the world has been increasing. The ocean refrigerated transportation business is constantly developing, and the proportion of refrigerated containers in the port yard is constantly increasing. Maintaining the temperature of goods in refrigerated containers within the allowable range requires a significant amount of energy, which is an important part of port energy consumption. At the same time, the operation of the reefer groups has flexibility in time and power, and optimizing scheduling can significantly improve the efficiency of the port energy system [93, 94]. Literature [95] proposed a multi-subject energy management system for optimizing the operation of large-scale port refrigeration box groups, which can simultaneously schedule a large number of refrigeration boxes in multiple yards to achieve peak shaving and valley filling of port loads. Literature [96] simulated the total power variation of the refrigeration box group under natural conditions, and analyzed the potential for the reefer groups to participate in power balance optimization.

• (4) Energy Storage Devices

The energy system is a complex system that maintains a balance between power and energy on different time scales, so energy storage devices that can smooth out power and energy fluctuations are an important part of the flexibility resources in the integrated energy system [97]. Thanks to the rich energy sources, ports, especially large seaport integrated energy systems, can apply various energy storage technologies such as electric energy storage, thermal energy storage, natural gas storage, and hydrogen storage. Different types of energy storage have their own advantages, and cooperation can improve the overall economic benefits of the system [98].

Electric energy storage technology is the most mature and has been widely studied in the application of the power system [99,100,101]. In terms of thermal energy storage, Literature [102] established a detailed mathematical model of thermal energy storage, which can be used to accurately simulate the operating characteristics of thermal storage devices. Literature [103] analyzed the commonalities and differences between thermal energy storage and electric energy storage, and established unified storage models and detailed thermal energy storage models. Literature [104] analyzed the impact of thermal storage equipment on the operation flexibility of combined heat and power units. Regarding natural gas storage and hydrogen storage, Literature [105] established a hydrogen-natural gas hybrid storage system model and proposed corresponding economic dispatch optimization models to analyze its operational benefits. Literature [106] studied the configuration and optimization operation methods of natural gas storage under multiple time scales. Literature [107] analyzed the energy efficiency of hydrogen storage coupled with natural gas combined cycle systems and studied the key factors affecting hydrogen production.

1.4.3 Energy Management Model of Port Integrated Energy System

The green port integrated energy system contains abundant flexible resources and and multiple forms of energy, with great potential for energy optimization management. This section summarizes existing research results on energy management models from two aspects: considering heterogeneous energy characteristics and under uncertainty conditions.

• (1) Energy Management Model Considering Heterogeneous Energy Characteristics

In port integrated energy systems, different energy types have different time scales and energy transmission characteristics due to different energy transmission media. Fully considering heterogeneous energy characteristics can make the energy management model more accurate and effectively improve the system's energy utilization efficiency. Literature [108, 109] used the node method to establish a thermal system model when managing energy, fully considering the thermal network transmission characteristics and combining transmission heat loss and temperature mixing. Literature [110] used the heat conduction equation to characterize the temperature distribution inside the heat transfer pipeline and calculated the node temperature using the temperature mixing equation. Literature [111] established a dynamic model of thermal systems, considering temperature delay and mass flow rate changes during energy transmission. Regarding natural gas systems, Literature [112] considered natural gas flow rate and pressure to establish an energy optimization scheduling model for port integrated energy systems that consider natural gas flow characteristics.

• (2) Energy Management Model Considering Uncertainty

In port integrated energy systems, due to the large-scale access of renewable energy and a large number of flexible resources, uncertainty factors are widely present. Currently, scholars often use stochastic optimization models to describe uncertain parameters probabilistically, thereby transforming models containing uncertainty into deterministic mathematical programming problems [113, 114]. Literature [115] used the Monte Carlo method to generate random scenarios to characterize uncertainty factors. Literature [116] considered the propagation of uncertainty between the electricity and gas networks and established a two-level stochastic optimization model and a multi-level stochastic optimization model. However, the accuracy of stochastic optimization models depends on the accuracy of characterizing uncertain factors, and there is a trade-off between solving accuracy and computational difficulty.

Robust optimization methods can also be used for energy management optimization under uncertainty conditions. Robust optimization models are independent of the probability distribution of uncertain parameters and only require setting an uncertainty set to represent the fluctuation range of uncertain parameters. Moreover, under the same conditions, the computational complexity of robust optimization models is often smaller than that of stochastic optimization models [117]. Literature [118] considered the uncertainty of renewable energy and established a virtual power plant stochastic optimization scheduling robust model. Literature [119] established an energy management robust optimization model for multiple microgrids, which considers the uncertainty of renewable energy and loads and can control the conservatism of feasible solutions to a certain extent. However, because robust optimization always needs to meet the worst-case scenario, there are shortcomings such as conservative results and poor economic efficiency.

1.5 Research Directions of Green Port Integrated Energy System

1.5.1 The Current Situation of Typical Ports

• (1) Los Angeles Port

Los Angeles Port, located at the top of San Pedro Bay on the southwest coast of California, is the second-largest port in the United States. It includes 15 breakbulk/general cargo berths, 36 container berths, and 14 oil berths [120]. Handling equipment includes various types of shore cranes, container cranes, floating cranes, gantry cranes, mobile cranes, loading bridges, and roll-on/roll-off facilities. The container cranes have a maximum lifting capacity of 40 tons, and the floating cranes have a lifting capacity of 350 tons. The container docks can stack up to 25,000 standard containers. The largest oil tanker to dock at the port had a capacity of 220,000 deadweight tons with a tank capacity of 500,000 tons, and the open storage area covers an area of one million square meters.

Los Angeles Port has been developed into a world-leading modern and multifunctional electrified port, with various factories, businesses, and related research institutions within its boundaries. In 2020, Los Angeles Port launched six hydrogen-powered transport trucks, becoming the first port to apply hydrogen fuel cell vehicles [121]. After the massive replacement of electrical and clean energy equipment in the port, Los Angeles Port has become a typical representative of a comprehensive energy supply system that is centered on electricity, has multiple forms of energy, and is coupled with logistics systems.

• (2) Yangshan Deepwater Port

Opened on December 10, 2005, Shanghai's Yangshan Deepwater Port is located in the rugged archipelago outside the mouth of Hangzhou Bay and consists of Xiaoyangshan Island, Donghai Bridge, and the Yangshan Free Trade Zone, making it the world's largest intelligent container terminal [122, 123]. The main port area of Yangshan Port has completed the replacement of electrical equipment, and some areas have achieved unmanned operations. In 2016, the cargo throughput of Yangshan Port reached 702 million tons, and the container throughput was 37.13 million TEUs, maintaining the world’s first place for seven consecutive years since 2010.

Yangshan Port mainly includes the energy operation port area and the container loading and unloading port area. The energy operation port area includes a liquefied natural gas receiving station and a subsea gas pipeline, with an annual import capacity of 3 million tons of liquefied natural gas. At the same time, Yangshan Port is also the largest transfer base for finished oil in the Far East, with a planned and constructed 1900-m-long oil terminal operation area that can store 2.7 million cubic meters of finished oil after the project is completed. The container loading and unloading port area is mainly in the North Harbor area and the West Harbor area, with a planned deepwater coastline of 10 km and more than 30 berths, capable of loading and unloading the world's largest post-Panamax container ships. The variety of goods, rich energy sources, and high level of intelligent operation make Yangshan Deepwater Port a pioneer in China's green port integrated energy system.

• (3) Rizhao Port

Rizhao Port is the eighth-largest port in China and an important global hub for energy, raw materials, and container transshipment. The main cargo transported by the port includes containers, ores, timber, grain, edible oil, crude oil, natural gas, and coal. The annual electricity consumption of the Port of Rizhao exceeds 100 million kilowatt-hours, which can be converted into more than 40,000 tons of standard coal and 27,000 tons of carbon emissions, with fuel loads, natural gas loads, and cold and heat loads. At the same time, Rizhao Port has abundant sunshine and wind energy, and there is great potential for the electrification transformation of equipment. The various load demands of the port have the conditions for coupling and complementarity, making it a suitable demonstration area for low-carbon energy use in ports.

Currently, Rizhao Port is promoting the “14th Five-Year Plan” for green and low-carbon ports. On the energy supply side, it is developing renewable and low-carbon energy; on the energy consumption side, it is achieving electrification and low-carbonization of port energy consumption; and ultimately, it is constructing a comprehensive energy network with multiple energy coupling and complementarity to form a smart energy solution for the port. By investing in photovoltaics, wind power, combined cooling, heating and power units, and energy storage equipment in stages at Rizhao Port, clean electrical energy replacement can be achieved. By gradually using gas-powered and electric heavy-duty trucks in proportion, electrical energy replacement can be achieved at the port.

1.5.2 Future Research Directions

In recent years, research on integrated energy systems has been flourishing and has achieved relatively complete research results, which can also be applied to the construction and development of port integrated energy systems. Although the port integrated energy system has many similarities with traditional integrated energy systems, its strong coupling requirements for shipping and logistics planning make the low-carbon operation of the port integrated energy system significantly different, and further research by scholars is urgently needed.

• (1) The Accurate Modeling and Application of Liquid Energy Network in Ports

In the study of traditional integrated energy systems, research on power grids, heat networks, and gas networks has been quite thorough and can be directly applied to the analysis and modeling of integrated energy systems in ports. However, as a transportation hub, ports also contain a large number of liquid networks, such as liquefied natural gas, hydrogen transport networks, and crude oil pipelines. These liquid networks not only transport energy but also interact with the port’s energy system to meet its own energy demands. The establishment of an accurate model of the liquid energy network and a clear understanding of its impact on the energy system beyond its transport function is a key difference between integrated energy systems in ports and traditional integrated energy systems, and is also an area that urgently needs further exploration. Based on the existing foundation, it is necessary to establish a refined model that reflects the transport and supply characteristics of liquid networks, and to incorporate this model into the dynamic optimization mathematical model of the port's integrated energy system with multiple network characteristics. The highly nonlinear nature of the above model will significantly increase the difficulty of solving the model. Therefore, the application and rapid solution of the model under the premise of accurate modeling of the liquid energy network is also a key research focus in the future.

• (2) Energy Coupling Between Energy and Logistics Systems

Currently, research on the coupled operation of energy systems and logistics systems in ports is still in its nascent stage both domestically and internationally. The problem of non-fixed equipment attributes, unstable source-load characteristics, and uncertain network topology after energy coupling urgently needs to be studied. The switching process between ship power stations and shore power, as well as the lifting process of bridge cranes, involve the transformation from load to power source, which has been ignored by existing research and cannot tap the complementary mechanism between logistics and energy. At the same time, the unstable source-load characteristics of ports have been overlooked in existing research, which only considers the time characteristics of renewable energy such as wind and solar power and does not take into account the impact of shock loads such as ships and bridge cranes, as well as logistics scheduling, on the operation characteristics. The uncertain topology of the port network due to the uncertain berthing ship topology and the interconnection node of logistics equipment causes the network topology of the port to be uncertain. Existing research treats the system as a fixed topology and cannot analyze the impact of the spatial transfer of logistics equipment and refrigerated containers on energy, and the analysis of fault energy flow is inaccurate.

Based on the analysis and disclosure of the coupling mechanism between the port logistics system and the energy system, an energy quantification modeling method for the logistics system is proposed. The spatial–temporal correlation characteristics of each logistics operation link and its impact on the energy system operation are revealed, and the two different systems are coordinated and optimized. The dynamic characteristics and dynamic behavior mechanism between each energy supply system and logistics load are currently the bottleneck that urgently needs to be overcome.

• (3) Influence of Extreme Weather on Port Energy System

In recent years, extreme weather has frequently ravaged various parts of the world. As a hub and convergence point for water and land transportation, ports are significantly affected by extreme weather such as typhoons, heavy rains, and hail. Currently, there is a significant amount of research on the power output fluctuations of wind and solar energy caused by extreme weather and equipment failures. For ports, extreme weather not only directly impacts the energy system but also indirectly affects the logistics system, which in turn affects the energy system. Large seaports contain a large number of temperature control equipment such as refrigerated containers, and drastic changes in external temperature will directly affect the port's load. At the same time, extreme weather in the port area will also affect the berthing plan of ships. More berthing ships and longer berthing times will affect the load demand of the port's energy system. The impact of extreme weather on the efficiency of internal transport equipment in the port may cause a backlog of goods, which will affect the coordination between the port and the external transportation system, disrupt the original logistics plan, and affect the energy system scheduling plan. Therefore, the diverse and complex impact of extreme weather on the integrated energy system in ports is also a key issue that needs to be studied in the future.

1.6 Conclusion

This chapter provides an overview of research on low-carbon technologies for port energy systems both domestically and internationally. Existing methods were analyzed from three perspectives: the current state of low-carbon technology development, coupling of energy-logistics systems in ports, and port energy management. Based on this analysis, future research directions for green port integrated energy systems were explored. The low-carbon development of future ports requires not only advanced technologies in the energy field, but also interdisciplinary development support in areas such as the environment, economy, and management. In the environmental field, continued research is needed on carbon emission measurement standards and development and utilization of ocean carbon sink resources. In the economic field, it is necessary to clarify the distribution of low-carbon development rights and responsibilities among multiple stakeholders in port areas, and further optimize carbon tax schemes. In management, exploration of top-down and bottom-up carbon emission management methods such as carbon quotas and verification of voluntary emission reductions, as well as research into low-carbon emission reduction mechanisms involving the government, ports, and ship owners, is needed.