Introduction

Today, developing countries are witnessing a growth of mobile telecoms in view of network coverage and tremendous impact on operating cost of running systems, since the electric power infrastructure and grid energy supply for remote telecom networks (RTNs) are available [1]. However, RTN shave enlarged to eloigned deserts and forests where connectivity is an exigency, and may not exist and/or power grids are unstable [2, 3]. Moreover, power system networks have suffered from problems as using fossil fuels and thermal generation that provide power with depleting fuel and pollution [4]. Cost and security speaking, diesel generators (DGs) for example, on which telecom companies have long relied in the above regions, operate at low efficiency, have become expensive to operate, and produce high CO2 emissions [5, 6]. So, it is necessary to introduce alternative renewable energy sources (like solar PV cells and small wind turbines [7]), implement these for RTNs as back-up energy source for telecom stations and new storage technologies, and overcome centralized power generations and distribution paradigms still predominating [8, 9]. But, integrating green energy resources and storage systems (GERSs) remains a big deal for RTNs when companies aim to not feed these by conventional energy resources [10]. Although power failure and load shedding are nowadays rare compared with years before, it is mandatory to prevent such situation harmful for mobile operators that need unremitting electrical power supply to keep RTNs continuously functional, ovoid their failure by interrupting supply electricity during load-shedding periods, and then deploy DGs in telecom base transceiver stations (BTSs) as backup power supply [11]. Aiming to improve network operation and reduce energy cost, strong efforts have been made in developing countries, to optimize energy cost, convert indoor BTS into outdoor one, eliminate using air conditioners, install energy-efficient equipment, and GERSs to feed telecom sites [1, 12,13,14,15].

Additionally, GERSs for RTNs involve efficiency, reliability/cost, energy conversion capability to forecast energy production, safe connection to electric grids, efficient and environment-friendly energy storage/ transport, developing advanced control and monitoring algorithms, networking of sources/consumers, and uptime of good tools for simulations and experiments [16, 17]. Since, resources originating from atmospheric conditions changes have been erratic at best, a standalone solar/wind system alone can in no way satisfy reliable power supply, or meet continuous load demands of BTSs during atmospheric conditions variations [18]. Hence, many energy sources need to be involved for extended usage of alternative energy, and different GERSs operating coordinately and independently as hybrid green energy systems (HGESs), are needed [19]. For instance, simulating photovoltaic (PV) arrays has attracted a great interest as key parts of power generation, and PV modeling has involved non-linear I-V curves approximations [20]. Modeling and simulation PV cells aims to produce energy using the well known one-diode (D) model, D connected with a light generated current source in parallel [21]. Predicting a performance analysis of such HRESs to power RTNs, as alternative to DGs, has been found to own higher degree of reliability and lower cost of energy production, as compared to systems consisting a unique GERS [22,23,24,25,26]. Although many research groups have privileged wind-based GESs on those preferring PV energy, [27,28,29] the drawback of “unpredictable nature” of these two resources can be partially overcame by integrating both in a proper combination to form a HRES, [30,31,32] and fix the issue of low efficiency due to such disadvantage [33].

Additionally, interface devices for PV systems used in RTNs should be single-stage inverters with buck-boost ability (required for proper maximum power point -MPP- of PV panels) in voltages below those of grids, to avoid needs for additional DC-DC converters [34]. There is a tendency to integrate PV/Wind HRES grids with MPP control algorithms and operation of the inverter using Fuzzy logic based controller, as Amir et al. [35] proposed, and Arkhangelski et al. [36] reported to control current and improve power quality (PQ). For PQ improvement and stability, however, Muthukumar et al. [37] developed a “three-level inverter” architecture that improves the power factor of the developed system [38]. Motivated by the fact that companies may avoid using wind energy because their turbines involve high upfront capital investment, and that PV source is especially more useful in rural areas where RTNs are built, we propose a BTS to be placed at a remote location without simple access to energy grids [39] (that require about 80% of the total power consumption to provide a network coverage [40]), fed by a MSG. This is provided with key analytics and an in-depth perspective of device power consumption form from smart meters, envisaged to have a user-friendly effect on the general dependability of the MSG and reduce the operational cost [41].

On the another hand, deploying GERS-based SMGs that consist of distributed energy resources, advanced power electronics devices,0 smart meters, microcontrollers, smart electrical appliances, and communication technology enablers [16, 17, 42], can reduce CO2 emissions and solve power provision problems [43,44,45,46,47,48]. In addition, through enabling power generation, consumption, and transmission control, SMGs offer an equitable solution and energy-efficient management for RTNs [49,50,51,52,53,54]. However, trusted centralized grid management is generally difficult and subject of subversion attacks aimed at power theft, but using distributed models should offer durable solutions based on 0.mis-recording informations on power consumption/generation [55]. In SMGs, cyber systems collect, transmit, and process data (with efficient, reliable, and timely flow) to control physical system operation [56]. Figure 1 shows a typical SMG with a cyber–physical networks, and focuses on cyber attack incidents in traditional power grids and attacks targeting smart metering networks, that may threaten system-level security, services and privacy in RTNs [57, 58]. The architecture of the proposed SMG contains three layers: the first “power system” representing the physical layer of the ecosystem, composed of four sublayers, the second layer “power flow” defining the role of “Generation-Transmission-Distribution-Consumption” sublayers, and the third one as an intelligent part of the MSG, comprised of Wide Area Network (WAN), Neighborhood Area Network (NAN) and Home Area Network (HAN) networks types as an that contains the information flow. Further, passive and active attacks are concerned with data theft or privacy subversion, and data destruction/subversion within networks [59]. To counteract such attacks creating fluctuations negatively impacting users trust in grids reliability and dependability, an architecture should be designed to operate efficiently over lossy mobile networks [60]. Denial of service (DoS) and distributed DoS (DDoS) are attacks on data availability that block or delay data communications, and transfer by exhausting the routers’ processing capacity, network bandwidth, or servers, malformed packets to targets or flooding network/ communication layers [61]. In our developing countries, traditional power grids feeding RTNs are suffering from unidirectional information flow, energy wastage, unreliability and limited security, whereas IoT in SMGs helps sensors, actuators and smart meters monitoring, analyzing and controlling grids, and providing connectivity, automation and tracking for such IoT devices [62]. Recently, Ciavarella et al. proposed the management of contingencies in SMGs through IoT, reporting security considerations for IoT in SMGs as a first priority [63, 34]. Gupta et al. [65] and Parra et al. [66] surveyed advances in security and cyber threats in IoT in SMGs, concluding that devices in SMGs and IoT ecosystem are more vulnerable to advanced persistent threats as SMGs and IoT devices provide attack surfaces to threat actors exposing information assets at all layers of infrastructure to critical risk. First, the study describes a PV model (as a part of a HGES for RTNs, and optimized to be used for meeting load demands, owing to the adaptability of input data in modeled PV-based energy generation systems for remote RTNs, using Matlab-Simulink approach. We focus on simulating an appropriate PV module for BTSs of RTNs, according to the PV cells fundamentals, and propose a cost energy-efficient management solution for SMGs. Since attacks -that system operators may be unaware of- are of disruptive to such SMGs, and hackers can enter in communication network without modifying the system observability, the second task on the paper provides intrusion detection solutions that seek to enhance the detection efficacy through some architectures to detect specific attacks. An individual attacking a SMG of an RTN can affect the real-time balance between energy production and consumption by influencing data that smart objects generate or that sent from the utility, or aims at power theft causing enormous financial loses to the utility and power assets of a telecom company. Thus, IoT-based SMG of such a RTN supports and improves network functions at stages of energy generation, transmission, energy-efficient management, and consumption. Moreover, the unexpected power outage in some developing countries caught their telecom infrastructure off guard. An RTN without an emergency power backup supply while power failure will go dark (customers will shift their business to another provider) and lost revenue. It is in this context that this part is being taken. The paper is organized as follows: After a brief review of GERSs for RTNs and SMGs with cyber–physical networks given first, section 2 is on how to evaluate the performance of a PV GERS for RTNs. Section 3 situates an energy-efficient management solution implemented to hack attacks threatening system-level security and services of SMGs. Finally, section 4 concludes this work.

Fig. 1
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Typical SMG with cyber physical networks

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Performance of the PV-Based Energy Generation System for an RTN

Conventional transformer-less grid-tied PV inverters suffer from hard switching, lack of buck-boost ability, and low efficiency: drawbacks overcame by recent topologies that eliminate leakage currents more and further enhance efficiency [34]. Due to lower cost, size and, weight, current PV transformer-less inverters are preferred in grid-tied applications, but concurred in owning higher efficiency and eliminating leakage currents [67, 68].

Added at inputs of Buck DC/DC step-up power converters (BCs) or at outputs as load-side filters, diodes, transistors and capacitors/inductors for energy storage, as supply-side filters, help reduce here the voltage ripple. Although the system contain a load profile representing a BTS, batteries for storing excess energy and improving the system reliability, a DG for backup power, and wind turbine as a GERS beside PV panels, we have focused, using Simulink first, on the latter circuit-connected to a 48 V DC bus. Needs for low power switching BCs are affected by demand for low-power and necessity of power management circuitry to connect varying voltage to the fixed high efficient voltage load [69]. Total irradiations on surfaces composed from three parts of insolations, are optimized by considering the surface tilt angle depending on diurnal and annual sun paths, as:Ht(β, δ) = Hdir(β, δ) + Hdif(β, δ) + Href(β, δ), where Ht, Hdir, Hdif, Href, β and δ are respectively the total irradiations on tilted surfaces, direct/diffused/reflected irradiations, and tilt/azimuth angles. The PV generator is assumed to operates always in modeled MPP. Its module data has been taken from SolarWorld250SW 250Mono modules’ datasheets. Relatively to solar radiations and temperatures, the PV module processes current and voltage, obtained by omitting the dust densities.

For PV cells, a modeling of output I-V characteristics, adopted in literature over five past decades [70,71,72,73], is an equivalent circuit-based model majorly utilized for MPP technologies: a one-diode PV cell modeling that contains a diode, a light-generated current, a parallel resistor expressing a leakage current, and a series resistor describing an internal resistance acting against the current flow (Fig.1). Its I-V characteristic equation is I = IPH − IS[exp (q(V + IRS)/kTCA − 1] − (V + IRS)/RSH, with IPH the photocurrent, IS the dark saturation current, q (1.6 × 10−19C) the charge of electron, k the Boltzmann’s constant (1.38 × 10−23 J/K), TC the working temperature of the cell, A the ideality factor, RSH the shunt path resistance, and RS the series resistance. Mainly depending on solar insolations, and the cell’s working temperature, IPH equals to [ISC + KI(TC − TRef)]λ, where ISC,KI, TRef and λ (kW/m2) are the cell’s short-circuit current (at 25 °C,and 1 kW/m2), the cell’s temperature coefficient under short circuit condition, the cell’s reference temperature, and the solar insolation, respectively.

Results and Discussions

The typical performance at different irradiations and temperatures and parameters of the modeled PV module are shown in Fig. 2, and listed in more details in Table 1. BCs are dedicated to convert an energy coming from PV-GERSs. The (I-V) and (P-V) curves of the PV panel are presented in Fig. 2 to visualize MPP at energy changes due to irradiation and temperature variations. Figure 2 also shows the PV panel parameters at MPP (corresponding optimal voltage and current: VM, IM, VOC, and ISC). Considering Solar World SW250 Mono module (MPP Pmax, Voc and Isc of 250.355 W, 37.8 V and 8.28A, respectively), the initial input irradiance of the modeled PV array is 103 W/m2when operating at 25 °C. When steady-state is reached (around t = 0.1 s), we get a PV voltage (VDC_mean) of 481 V and the power extracted (PDC_mean) from the array is 14.4 kW. Figure 3 shows the irradiance variations on short time scales, as follows: At t = 0.3 s, sun irradiance has ramped down rapidly from 1000 to 500 W/m2. For the control system and due to MPP condition, VDC reference is kept to 480 V to extract Pmax of7.2 kW from the PV array. The irradiance effect is observed on all of the phases of I and V at the AC side of the inverter. At t = 0.6 s,the solar irradiance was increased to 700 W/m2, and the extracted power increase to 9.6 kW as well. The irradiance variation (Fig. 3) shows also that while the chosen site fluctuates with much smaller fluctuations, which confirms anecdotally that such site will lead to a smoother output [74, 75]. As Figs. 2 above show, a PV panel of 72 cells and ideal I-V characteristic should own VOC and ISC of 0.667 V (48 V for the whole cells of the panel) and2.0A, respectively. A PV nonlinear nature of cells appears (Figs. 2) so that the PV panel outputs (I and P) depend on the cell’s terminal solar insolation, operating voltage and temperature. With sun insolations increase, ISC in the PV panel increases with increase of Pmax. This is due to the fact that VOC voltage depends logarithmically on solar irradiances, though a direct proportionality exits between ISC and the radiant intensity.

Fig. 2
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a PV module performance at various irradiance levels and temperatures b Irradiations linked to mean powers

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Table 1 Main parameters of the modeled PV module
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Fig. 3
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Variations of the sun’s irradiance on short time scales

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Energy-Efficient Management for RTNs

In SMGs, information/communication technologies play a key role in operating and control, cyber systems and physical processes are tightly coupled, but the cyber incidents can impact their reliable operations [76]. Many menaces are threatening transmission environment and wired connection, like information gathering, and weak encryption keys or authentication methods used: disadvantages that potential attackers exploit. For instance, IP telephony Net could be implemented to launch hacking attacks, and performed by a company having only one site, so that the Net used for ToIP is a LAN Net with WIFI access points and a router obliged to connect with an outside world. Since neither network speed is affected by adding firewall device (FD) nor dangerous effect on VoIP applications [77], FDs and hackers can be added to block outside-and-inside attacks, and test attacks on LAN users, respectively. Furthermore, wireless sensor networks (WSNs) have recently begun to be used in smart homes (SHs) monitored on mobile platforms or on web-based platforms, and such SHs are managed. Net topologies contain routers to connect LAN to Internet and access points to asterisk servers, so that SIP clients can call each other. To test the Net security, hackers that attack LAN entities are involved. To prevent threats from outside, a new generation ASA firewall between LAN and ISP PE routers was placed, that blocks attacks from outside to LAN and Net. If neither corresponding backup measures are taken nor preventive maintenance system is used to alert an administrator to an ongoing attack in emergency, hacking VoIP system and executing fraud attacks soon are possible. In multi-site companies, two LANs represent two sites, and a third LAN acting as Internet service provider. To fulfill a mobile platform for example, an 8 Gb RAM PC (i5 5200 processor), a TP-LINK WIFI modem (to connect mobile SIP clients), two smart phones (with Android iOS) used as mobile SIP clients, an i7 processor PC (of at least 16 Gb RAM to increase the speed of implementation execution) are needed, and the GNS3 [78] software (that can run on Windows, Linux and MacOS X platforms) is used. GNS3 allows the emulation or simulation of computer Nets for advanced functions, and connect different topology entities to the associated virtual machines (Asterisk FreePBX server and two machines to test windows 7 calls, kali Linux pirate, ubuntu IDS). Since GNS3 supports a broad range of routers and switches, allows endpoint clients connecting to virtual machines to best meet needs, it is used here mainly to test IOS features [79], while the open source operating system Kali Linux operating system environment is exploited an offensive security [80]. To detect LAN attacks on mobile platforms, pirate PCs can be added by using kali Linux that provides a plethora of programs to perform attacks targeting goals of cracking passwords, manipulating DNS servers, or intercepting data as man-in-the-middle. Since many attacks appeared and the implementation concerned ToIP, attacks that threaten it have been considered. Varied denial of service (DOS) attacks are found in literature to represent the bulk of disclosed vulnerabilities, and over 90% of these were due to implementation issues and 7% related to the configuration [81]. DOS attacks saturate the victims to block them by disconnecting elicit end-users from web servers, deny access to servers or interrupt email process diffusion in a company [82]. Usually, these attacks proceed by sending several simultaneous requests to the victims. When the PABX (Asterisk) server is attacked with DOS, so that the victim’s connectivity was first tested by pinging to the output router (Fig. 6). Next, msfconsole was run on a hacker machine kali Linux as a distribution, and DOS attacks were performed (Figs. 7 and 8). As an open source port scanner, Net Mapper (Nmap) is designed to shut down open ports, hosting services and information about a remote computer’s operating system. To launch it, we type “Nmap @ of the victim” (For example, the Asterisk server is a victim built with the address 192.168.1.4 [83]), as can be seen in Fig. 9. Ping of death has a data length greater than the maximum size. When sent, it will be fragmented into smaller packets that the victim PC rebuilds once received. Some systems do not manage this fragmentation, but freeze or crash it completely, hence attack names.

1st Proposed Task for Mobile Platforms

Two security measures have to be mentioned: security vulnerabilities from outside and inside the LAN. For outside, the security implemented consists in blocking all kinds of dangerous incoming flows. For that, we installed a new generation ASA firewall. The second case consists in securing the access to LAN Net from inside. Among many security policies, the appropriate case is so as a switch access ports according is limited to the users’ number, otherwise when a hacker has a connection ability to LAN, Snort will detect and then prevent intrusions.

2nd Proposed Task for Mobile Platforms

When added as IP backbone security, MPLS/VPN works correctly since after the traceroute 192.168.4.1 command line. The displayed result mention end interfaces beside that ISP routers interfaces in the MPLS cloud are discrete, which is among the main strengths of VPN. Since many security types have been implemented, a comparison between Cisco ASA Firewall, Cisco Netranger and Snort has been carried, for an efficient operation. The results are summarized in Table 2, below. It is worth noting that the security in next- generation mobile Nets is of capital interest. When Wi-Fi wireless access Net is chosen while adding mobile users and ASA firewall is added, the Net is secured. The gradual migration of protocols from traditional mobile Nets to new-generation Nets has brought significant improvements in communication very low latency and a high number of connected devices and a data exchanges security. Now, the trend towards fifth generation technology has become necessary, as it mainly provides the flexibility of its design to allow mobile operators to serve IoT and support low-latency connections, and an improved high-speed mobile connection. With regard to the 5G deployment, the NGNs control the core and access Net: the non-standalone mode [84, 85]. For security concepts currently proposed in 5G, these are built on the basis of a cloud-based approach for core and access Net. In other words, securities are based on very complex encryption algorithms that encrypt the carried data flow, despite wired radio or optical transmission technology. To secure the VoIP Net, using Snort remains the better choice to prevent attacks from inside LAN, as made in the middle sniffing and ASA firewall to inhibit DDOS attacks from outside [86, 87].

Table 2 Comparison between different types of security implemented in both proposed task for mobile platforms
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For web-based platforms, however, the attacks can be detected by performing tasks basing on two scenarios:

In the first shown Fig. 4, the third layer of the proposed SMG consists of a HAN network, however the SMG contains smart appliances, an automation controller and a WIFI modem. The RTN technician control the MSG remotely, and accesses the application with his account. All requests he send for monitoring or controlling the SMG are authorized by controller application servers before they are processed by the automation controller.

Fig. 4
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Schematic representation of the first cyber security scenario

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Hacker try to launch attacks on HAN network to manipulate the automation controller and gain control of the SMG, but fortunately this will not happen since the ASA firewall blocks all attacks. In a second cyber security scenario which part one is shows in Fig.5a, the intelligent layer consists of a NAN network. The sensors of all smart devices send information like power outlets to controller application servers via wireless transmission, to the automation controller, and then to the modem (that routes IP traffic to servers via a VPN tunnel provided by the MPLS cloud). The server sends the information to the house owner after a request. (the house owner has to access the application with his own user name and password). The RTN technician of the SMG sends requests to be received by the server of the SMG. The server forwards the request to the automation controller through the same VPN tunnel in the MPLS cloud, while this IP traffic is allowed to pass through the ASA firewall to the HAN network. The hacker launches a DOS attack to saturate the server but without success only the RTN technician can use the VPN tunnel to communicate with the server with encrypted data. To manage the power system level, shown in Fig.5b displaying part two of the second cyber security scenario in a WAN network, the monitoring of the energy-efficient generation/transmission, distribution and consumption is purely smart, and provided by the network operation center team. In this case, a WiMax and a satellite are used for a wireless access to the network. To conclude, since cyber incidents may have economic and physical impacts on operating MSGs (in which cyber system and physical process are firmly coupled) due to the cyber system’s vulnerabilities, and can negatively affect the stability of power electronics of SMGs, we have to prevent them.

Fig. 5
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Schematic representation of both parts of the second cyber security scenario in: a) NAN, b) WAN networks

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Fig. 6
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Capture showing bridge ping successfully

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Fig. 7
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Capture of launching DOS attacks

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Fig. 8
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Capture showing the pc in a locked state

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Fig. 9
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Capture of launching Nmap against attacks

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Conlusion

The power supply of a PV-based GERS in a SMG may drop or sharp increase. A Simulink model was used to design a standalone PV system power supplying an operating BTS in remote areas. When exploited PV-based GERSs can reduce operating costs and environment issues for RTNs, and provide advantages while tracking MMP such as constant voltage loads, direct PV module-battery connection at low light levels. The results indicate that PV panels playing a key role in GERSs, are of interest for the current electrical demand to power BTS in remote regions. The study has focused also on efficient monitoring and energy management control for RTNs, where an IoT based network was adopted to intercept attempts of frauds while using Internet to secure SMGs feeding RTNs. SMGs requiring cyber systems and communication networks are vulnerable to cyber-attacks affecting negatively their stability and operation. When designing and implementing SMGs, it is of great interest to secure them from threats. General requirements regarding the security and privacy challenges and solutions for SMGs are presented here, such as taking imperative decisions on whether and how services should be used to establish a secure VoIP system. It has been also shown that a VoIP system abused for fraud can be easily and quickly analyzed; this can be useful in detecting and preventing intrusions in promising SMG systems. Through simulation and implementation including low amounts of data available for validation, energy generation and consumption could be optimized and attack detection in SMGs feeding RTNs, and detection/defensive strategies to prevent false data injection attacks in SMGs should be boosted.