Keywords

Introduction

The purpose of meeting human basic needs and curbing climate change by reducing greenhouse gas emissions both at local and global levels has led to search for and establishment of energy policies for promoting renewable energy (Samuel and Owusu 2016; Sanchez-Lozano and García-Cascales 2014). The energy policies not only emphasized on promoting renewable energies but also on protecting natural resources and supporting natural environmental sustainability (Ivan 2015). Electricity generation from solar energy is in constant increase across the globe, but its share in the total energy production locally and globally still remains low as compared to fossil fuels. However, due to continual PV price decrease, increase in efficiency and maturity of technology in the last decades, feed-in tariffs including other incentives in many countries, has led to remarkable boom in photovoltaic (PV) technologies deployment and development both at utility-scale and residential levels across the globe (Robert 2014). According to International Energy Agency (IEA), the production of electricity from solar energy is expected to continue growing up to between 20% and 25% by 2050 (SEFI/UNEP 2009; Yassine 2011; Yassine and Adel 2012).

Despite of the remarkable boom in the application of solar PV technologies across the world, the application of these technologies in the electricity production in many developing countries like Zambia is still very negligible (Bowa 2017). However, there are only a few examples of small isolated solar systems used by communities, schools, companies, private households, hospitals, and health centers. These systems are often used to meet the daily energy needs and to cover up energy needs during load-shedding period (MMWED 2008; Bowa 2017). One of the largest solar systems installed by government so far through Rural Electrification Authorities (REA) was built in 2010 in Samfya district Northern Province (installed capacity of 60 kW) (Bowa 2017). According to Bowa (2017), the estimated total installed capacity of solar photovoltaic-based power plants as of 2016 was more than 2 MW (small off-grid systems). Hence, despite of the country being located in most favorable solar belt (MMWED 2008) and receiving significant higher solar irradiation than most of world’s largest solar energy utilizing countries, solar energy application for electricity generation has remained negligible. According to Meteorological Department of Zambia, the country has monthly average solar radiation incident rate of 5.5 kWh/m2-day (Gauri 2013; MMWED 2008; Walimwipi 2012; IRENA 2013). The solar radiation intensity across the country varies with western part of country having the highest annual average of approximately 5.86 kWh/m2-day and the eastern part with the lowest of 5.68 kWh/m2-day as shown in Fig. 1. Therefore, Zambia has a favorable climate conditions for utilization of solar energy for both production of electricity and thermal use. The total annual average global solar radiation ranges from 1981 kWh/m2 in parts of North-Western, Eastern, Northern, Central, and Southern provinces to 2281 kWh/m2 in parts of Luapula, Northern, and Western provinces of Zambia as illustrated in Fig. 2.

Fig. 1
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Annual average horizontal solar irradiation

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Fig. 2
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Annual total global solar radiation intensity (Mwanza et al. 2016a)

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In order to increase access to electricity for all, the Government of Republic of Zambia has set targets and plans to encourage deployment and development of renewable energy facilities across the country, with hydropower and solar energy based on photovoltaic technologies expected to experience the greatest growth. However, despite of several tools being available across the globe for estimating the solar energy potential for particular location, these tools do not fully take into consideration the environmental and social issues. In addition, the surface land areas and the natural environment are some of the world scarce natural resources that require selection of the best use of these rare resources (Ronald 2016). Therefore, in order to safeguard the natural environment and consider best use of available surface land areas, energy planning and site selection for promotion and deployment of renewable energy technologies in individual countries has become one of the most challenging aspect more especially in developing countries like Zambia.

In addition, unified planning and poor site selection for intermitted renewable energy source based power plant have resulted in mismatch between the grid capacity and PV power plant output during peak time in some parts of the world (Siheng et al. 2016; Ming 2015). On the other hand, arbitrary site selection and neglecting the transmission line available reserve margin in the procedure have resulted in some PV power plant exceeding the local transmission line reserve margin and grid unable to transmit the energy to the load centers during peak hours (Chinairn 2013; Aly Sanoh 2014; Quansah 2016). Therefore, preliminary estimation and mapping of potential sites, available areas, and technical energy yield potential for intermitted renewable energy source based power plant deployment while considering social acceptability and supporting natural environmental sustainability can be helpful to overcome these problems (Siheng et al. 2016). Doing so also helps to avoid and minimize potential negative environmental and social impacts associated with deployment of these technologies. The preliminary estimates and mapping of potential sites and technical energy yield potential for solar photovoltaic power plant development, however, have not been made in most developing countries like Zambia due to various reasons.

However, selection of potential site and evaluation of technical electricity generation potential requires a number of finer spatial resolution data, since not all locations of any particular country are suitable for deployment of these technologies due to local landscape terrain, climate, and environmental regulations (Suri 2005).

This chapter aims at providing a method for identifying and mapping a series of the potential sites and the available land areas suitable for solar energy harvesting in Zambia. The chapter further provides a method for assessing the electricity generation potential from solar energy based on commercially available solar photovoltaic technologies and available land areas. The evaluations in this chapter considered the modules of the solar PV systems mounted at optimal tilt position to the ground. The analysis focused on solar radiation, available areas, and typical energy that can be generated from the PV system considering the solar PV module characteristics and available solar radiation of the potential sites. The results of this study are important as it provides summarized information with regard to suitable potential sites, available land area, and technical electricity generation potential that can be attained from using solar photovoltaic technologies across Zambia.

Geographical Description

Zambia is unique country endowed with variety and abundant nature resources, such as wildlife resources, watercourse resources, forests resources, minerals resources, and renewable energy resources. Its abundant renewable energy resources such as solar energy are heavily untapped. The country is also blessed with unique climate and geography of flatland in most part of the country. It is situated between latitudes 80 and 180 south of the equator and longitudes 220 and 340 east of prime meridian. The country is landlocked by eight countries, Zimbabwe and Botswana to the South, Angola to the West, Democratic Republic of Congo and Tanzania to the North, Malawi and Mozambique to the East, and Namibia to the Southwest (Mwanza et al. 2016a).

Solar Photovoltaic Power Plant Sitting Considerations

Environmental and Social Issues

Solar energy is clean, free, and unlimited renewable energy sources that can be used for variety of purposes including pumping water for irrigations, drying and preparing food, and most importantly for electricity generation. However, just like any other alternative energy supply option, solar photovoltaic technology deployments at utility-scale are not free from imposing negative effects on both the environment and society (www.energy.gov) (Wang and Prinn 2010; Union of Concerned Scientists 2015). Most of these effects depend on development size, site, and the type of technology deployed and also site selection and environmental guidance procedure. The envıronmental and socıal impacts associated with renewable energy technology development are mainly grouped as listed in Table 1 (Ahmed Aly 2017; Turlough 2017; Shifeng and Sicong 2015; Kaoshan et al. 2015; Fylladitakis 2015; Saidur et al. 2011; Gipe 1995; Interior Department 2010; Damon and Vasilis 2011; U.S 2016; Geoffrey and Tidwell 2013; England 2011; Tsoutsos 2005, 2009).

Table 1 Summarized environmental and social impacts induced by solar photovoltaic power Plants
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Restricting Issues

The potential impacts associated with utilization of renewable energy technology have potential to hinder or delay deployment and development of solar photovoltaic technologies or facilities in potential sites. Table 2 and Figs.3, 4, 5, 6, 7, 8, 9, 10, 11, and 12 list solar PV systems deployment restricting issues that have, among others, been considered for inclusion, as appropriate, in the available land area, technical electricity generation potential, and potential sites assessment for sustainable solar photovoltaic facilities development in Zambia based on highlighted environmental and social impacts (www.energy.gov; Abdolvahhab Fetanat 2015; Alami et al. 2014; Ahmed et al. 2017; Arthur Bossavy 2016; Addisu and Mekonnen 2015; Marcos Rodriques 2010; Anthony Lopez 2012). Restricting criteria data are features that pose restrictions or limitations, that is, unsuitable or not preferred areas based on legislative laws of the country and nature.

Table 2 Restricting issue datasets
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Fig. 3
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Administrative boundary map

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Fig. 4
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Land digital elevation map

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Fig. 5
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Zones of agriculture production potential

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Fig. 6
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Wildlife areas: national parks

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Fig. 7
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Settlement and community interest sites

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Fig. 8
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Airports and airfield

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Fig. 9
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Road and railroad networks

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Fig. 10
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Existing electrical network

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Fig. 11
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Surface watercourses and streams

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Fig. 12
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Land aspects

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Potential Site Identification and Mapping

Solar PV Potential Site Identification and Mapping

In order to assess the potential sites suitable for utility-scale solar photovoltaic deployment based on literatures surveyed and the laws of Zambia on environmental for development of any industry or plant on a particular site and restrictions datasets summarized in Table 2. Thus, the following environmental and social impacts and issues illustrated in Table 3, among others, are considered for inclusion, as appropriate, in the selection of suitable sites for solar energy facilities (ECZ 1994).

Table 3 Environmental and social consideration for site selection in Zambia (ECZ 1994)
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These maps included land elevation map (DEM), land use/cover layer map, town and village location map, community interest sites map, national parks map, surface water bodies map, roads and railway map, study area boundaries, and transmission line maps (Nazli Yonca 2010; Sanchez Lozano et al. 2013, Brewer 2014, Chao-Rong Chen 2014, Charabi and Gastli 2011, Lopez 2012, Janke 2010; Uyan 2013). The rationale used for each restrictions are as follows:

  • Land Use/Cover (C6, C9): This dataset has 10 classes including bare land, closed to open shrubland, open shrubland, sparse grassland, croplands, urban settlement, water courses, wetland, and forest sites; low need-leaved deciduous forest and moderate evergreen forest. For deployment of solar PV power plants only bare lands, sparse grassland and open shrubland were considered suitable due to easy accessibility considering an emerging economy and also to reduce land clearing costs.

  • Wildlife Sites (C2): this dataset considers areas such as national parks, game reserves, and other natural resources since development in these sites will have adverse impact on birds, animals, and ecology, thus any construction in these areas may face public and international resistance. Therefore, these areas and the surrounding areas within the buffer of 2 km were considered not suitable (Nazli Yonca 2010).

  • Settlement and Community Interest Sites (C4, C1): The dataset consists of settlement areas for both rural and urban such as airfields, airports, towns, villages, and other dwelling areas and community interest sites. Here a buffer of 3 km is considered to avoid aforementioned impacts and increase public safety and acceptance. All areas outside the buffer were considered suitable (Joss and Watson 2015).

  • Land Elevation (C7): As it is expected that no one will install solar PV power plants in gorges or higher elevation due to construction costs. Thus, this dataset considered all higher and lower elevations such as mountains and gorges with steeper slopes above 50 as unsuitable areas.

  • Surface Water Bodies (C8): In this dataset all surface water bodies such as rivers, streams, lakes, including waterfalls, and wetlands were considered as protected areas in order to avoid water pollution. Thus, a buffer of 2 km was considered with all areas outside buffer being suitable.

  • Roads and Railways Network (C3): The dataset considers roads and railway network to be restriction since no one is supposed to build on roads or railway and also for the safety of the public. Hence, a 0.5 km buffer has been considered in order to increase public safety and also reduce cost of constructing access road which usually leads to land use/degradation, wildlife and habitat loss, fugitive dust, and air and soil pollution to the site and surrounding areas. Thus, the areas outside the buffer are considered suitable.

  • Transmission Line Network (C5): In this dataset the right of way for transmission line were considered as unsuitable area for solar PV power plants, thus a 0.5 km buffer was used. Any areas within the buffer were considered unsuitable. The 0.5 km buffer were considered so that the cost of constructing new transmission lines is reduced, but at the same time to avoid conflict with right of way for transmission lines and avoid land use/degradation, wildlife and habitat loss, fugitive dust, water, and air and soil pollution to the site and surrounding areas .

After creating buffers, and changing some features from vector to raster, in order to evaluate available areas and identify/map feasible potential sites, the created buffers for the restricting layers were overlaid on each other using GIS spatial analysis. Figure 13 below shows the summarized analysis procedure .

Fig. 13
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Analysis Procedure

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Available Land Area

In order to estimate the available suitable areas for solar photovoltaic power plant development based on aforementioned restrictions issues, a new factor called Area Suitability factor ƒSF was introduced. It is defined as the ratio of total grid cells of suitable surface area to the total cells of the study surface area. The factor is estimated based on study area grid cells; here the total grid cells for study surface area are evaluated considering the sum of restricted and suitable surface areas’ cells. Hence the factor depends on the ratio of available suitable area and surface area of the study area and it is calculated using the expression below.

$$ {f}_{SF}=\left(\frac{C_{CSA}}{C_{CSA}+{C}_{CRA}}\right)=\frac{C_{CSA}}{C_{TSSA}} $$
(1)

where CCSA is the total number of cells of suitable areas, CCRA is the total number of cells of restricted areas, and CTSSA is total number of cells of study area.

Therefore, the total available suitable land areas for each district and for Zambia were evaluated using expression 2 given below

$$ {A}_{ADS}={f}_{SF}\cdot {A}_{TSA} $$
(2)

where AADS is total available suitable areas (km2), and ATSA is total surface area of the study area (km2) .

Electricity Generation Potential

Solar Energy Potential in Zambia

According to the literature and data undertaken by Meteorological Department of Zambia, the country has a significant potential of solar energy for both electrical power production and thermal from solar energy technologies. The country has average peak sunshine of about 6–8 hours per day and monthly average solar radiation of 5.5 kWh/m2-day throughout the year (MMWED 2008; Walimwipi 2012). According to International Renewable Energy Agency (IRENA 2012), the country has the highest total yearly solar radiation of 2,750 kWh/m2-year with the highest average temperature of 30 °C, which presents good opportunity for solar systems deployment (IRENA 2012).

Performance of PV System

In order to evaluate the performance of grid connected PV power plants, the following performance indices are normally used: yields, normalized losses, and system efficiencies, performance ratio, and capacity factor – (British Standard 1998). However, in this chapter final yield, performance ratio and capacity factor have been adopted for analyzing the PV system performance of the various types of PV technologies commercially available on the market (Table 3) considering Zambia’s weather condition. In addition, several PV technologies have been considered in the evaluation of technical electricity generation and power potential: firstly, because the energy generation by PV power plants with same peak power and receiving same amount of solar irradiation differs depending on the type of technology employed in the power plants, and secondly, the amount of peak power that can be installed at a given land area differ with PV technologies as shown in Table 4. Hence, it can be concluded that the type of cell technology has greater influence in the amount of land area needed for a peak power installation, the higher the efficiency the lower the land requirements for the peak power capacity installation (Martin-Chivelet 2016).

Table 4 PV technology parameters
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Energy Model of PV Array

The solar energy resources are the key determinants of PV system electricity generation (IRENA 2012). The higher the solar energy resources, the more output yield of a PV systems per kilowatt. However, higher temperatures, dust, shading, balance of system inefficiencies, and PV technology characteristics have negative impact on the PV system energy yield (Didler 2012). Therefore, the electricity generated and supplied to grid by PV system considering these negative impacts has been estimated using Eq. 3:

$$ {E}_A={A}_{PV}\cdot {H}_R\cdot {\eta}_P\left(1-{\lambda}_p\right)\left(1-{\lambda}_{\cdot C}\right) $$
(3)

where EA is energy output of PV system (MWh/year), HR is solar radiation on the surface of module (kWh/m2-day), APV is PV system active area (m2), ηP is module efficiency under STC condition, λp is miscellaneous module losses due to dusty covering, and λC is losses due to power conditioning unit and cable losses. Module efficiency is a function of its nominal efficiency, ηr, which is measured at STC Tr = 25 °C (Didler 2012). İt has been calculated as:

$$ {\eta}_p={\eta}_r\cdot \left[1-\beta \left({T}_c-{T}_r\right)\right] $$
(4)

where β is a temperature coefficient for module efficiency, Tc is a module temperature due to air temperature, and Tr is STC reference temperature.

Module temperature is related to the average monthly ambient air temperature, Ta, for a local condition has been calculated using Eq. 5 (Didler 2012).

$$ {T}_c;={T}_a+\frac{G_T}{G_{T. NOCT}}\left(\frac{9.5}{5.7+3.8{V}_W}\right)\left({T}_{c, NOCT}-20\right)\left(1-{\eta}_m\right) $$
(5)

where GT is solar irradiance (W/m2), Ta is ambient air temperature (°C), and VW is wind speed(m/s) for the location, Tc,NOCT is nominal operating cell temperature (Table 3), it depends on type of PV technology, ηm is the factor less than 1 and normally neglected and GT,NOCT is 800 W/m2.

Performance Ratio Model

Performance ratio is denoted by PR, this factor is important as it shows the overall effect of losses on the PV array’s rated output power due to the PV array temperature, incomplete use of the solar irradiation, and PV system component inefficiencies or failures. It is calculated as (British Standard 1998).

$$ {PR}_{.}=\frac{Y_F}{Y_R}=\frac{E_{AC}}{G\;{\eta}_{STC}} $$
(6)

where G-standard test condition solar radiance (1 kW/m2) and ηSTC-array efficiency at standard test condition given as.

$$ {\eta}_{STC}=\frac{P_{PV}}{GA_{PV.A}} $$
(7)

where APV,A-Active array area (m2) and PPV,A- array rated power (kWP) .

Capacity Factor Model

This is a model used to show the amount of energy delivered to the grid by an electric power generation system (Ayompe 2014). It is defined as the ratio of the output actual annual energy generated by PV system to the amount of energy the PV system would generate if it is operated continuously at full rated power for 8,760 hours in a year and it is expressed as (Ayompe 2014; Kynakis 2009; British Standard 1998).

$$ {CF}_{.}=\frac{E_{AC}}{8760\times {P}_{PV}}=\frac{PR\times {H}_t}{8760\times {P}_{PV}} $$
(8)

where CF is capacity factor (%), EAC is Actual annual energy output (kWh/year), and PPV is Full rated PV power (kWp) .

Solar Energy Potential Model

Theoretical Solar Energy Potential Model

Theoretical solar energy potential involves the assessment of the total solar energy that is received at the surface of the study area. This potential involves identifying the study area boundary and the size of the study land area, including total annual average solar radiation magnitude. The theoretical potential has been calculated using Eq. 9:

$$ {E}_{TH}={A}_S\cdot {H}_P $$
(9)

where ETH is theoretical solar energy potential (MWh/year), As is study area active surface area (km2), and HR is total annual average solar irradiance (MWh/km2-year) .

Geographical Solar Energy Potential Model

Geographical solar energy potential involves assessing the solar energy that is received on the available and suitable land area of the active surface land area of study area (Lopez 2012). Hence, the process of assessing this potential involved firstly excluding all the protected and restricted areas from the active surface area of the study area under consideration (Yan-wei 2013; Lopez 2012).

Therefore, the remaining surface land area is taken as the most suitable land area of the total study area surface land area for solar energy technologies development. In this study, the geographical solar energy potential has been estimated using Eq. 10 given below:

$$ {E}_G={A}_{AOS}.{H}_R. $$
(10)

where EG is geographical solar energy potential (kWh/year), AADS is Available Suitable Area (m2), and HR is total annual average solar radiation (kWh/m2-year) .

Solar PV Technical Power Potential Model

The process of assessing the feasible solar PV technical potential, that is, the maximum power capacity that can be installed for any country without environmental and social impacts involves firstly by excluding restricted areas and areas not suitable for utility-scale PV systems development within the defined boundaries. Furthermore, considering technical characteristics of solar PV technologies (Table 3) to convert the solar energy to electrical energy, the total solar energy that is received at the surface of the solar PV module and the area required by the PV system and its supporting infrastructures. Hence, the technical solar PV potential has been estimated using Eq. 11 (Yan-wei 2013; Lopez 2012):

$$ {P}_{TP}=\left(\frac{A_{ADS}}{A_{PV SA}}\right).={P}_{PD}{A}_{PV} $$
(11)

where PTP is Solar PV Power Potential (MW), APVSA is Solar PV system and Supporting Infrastructure Occupied Area per MW (km2/MW), AADS is Available Suitable Area for Study Area (km2), APV is total geographıcal occupied area by PV system and supporting infrastructure (km2), and PPD is solar power density of the area (MW/km2) .

Solar PV Systems Electricity Generation Technical Potential Model

The total AC electricity generated by the PV system is the sum of the electricity produced by all array in the PV power plant measured at the point where the system fed to utility grid. The total daily EAC,DP and monthly EAC,mP AC energy generated by plant are expressed as (Ali et al. 2016; Tripathi et al. 2014; Siyasankari and Babu 2015):

$$ {E}_{AC, DP}=\sum \limits_{t-1}^{24}{E}_{AC,t} $$
(12)
$$ {E}_{AC, mP}=\sum \limits_{d-1}^N{E}_{AC, DP} $$
(13)

where N is number of days in the month, and EAC,t is energy produced by PV power plant per hour (kWh).

Utility-scale photovoltaic are large-scale solar PV power plant that can be deployed within the boundaries of the country on an open space land area (Lopez 2012). Several studies have considered that the modules covers the available suitable areas on horizontal; however, the method proposed in this study seeks to consider the active area of PV arrays only and also the supporting infrastructures in the evaluation of technical potential. The process of assessing the extractable electricity generation potential from the sun for any country involves firstly by excluding areas not suitable for utility-scale PV systems within the defined boundaries, and secondly, considering technical characteristics of PV systems to convert the solar energy to electrical energy and the area required by the PV system and its supporting infrastructures. In this study the technical solar energy potential was estimated using Eq. 14 (Yan-wei 2013; Lopez 2012):

$$ {E}_T={P}_{TP}. CF.{T}_{TSH} $$
(14)

where ET is Solar PV Electricity Generation Potential (MWh/year), PTP is the technical power potential (MW), CF is Study Area Capacity factor (%), and TTSH is the hours of the whole year (8,760 hours/year).

Potential Site and Electricity Generation Potential

Solar PV Potential Sites and Mapping

Figure 14 presents the map of solar PV potential suitable sites evaluated for Zambia, which indicates that the country has large land areas suitable for solar PV power plant development both at district and provincial levels. The aim of this case was focused on mapping the potential sites suitable for PV power plant installation with minimized or no environmental and social impacts. Therefore, all limiting factors considered not suitable for PV systems and those areas likely to have environmental and social issues were eliminated in the analysis using GIS spatial analysis. Hence, the Solar PV Potential Sites atlas shows that the country has the largest suitable site for solar PV power plant development in the Southern Province with Lusaka Province having the least. However, it can be observed that the available suitable areas are distributed throughout the country, hence providing opportunity for wide deployment of the solar PV technologies across the country. In addition, the atlas also shows that regions near to the national power grid contain suitable sites for easy integration of these technologies into the national energy mix and national power grid. The atlas provides essential information for sites close to villages and towns far from the grid offering opportunity for mini off-grid systems. Therefore, the atlas offers vital information for setting targets for electrification of both rural and urban areas of the country.

Fig. 14
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Potential suitable sites for utility-scale solar PV power plant deployment

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Available Suitable Land Area

Table 5 shows the annual average solar irradiation, total surface area and the available suitable areas for each district of Zambia. This reveals significant differences in suitable available areas within the 75 districts and 9 provinces across the country due to the availability of the aforementioned restricting factors considered in the evaluation. It can be observed that the districts in Eastern Province have lowest ratios of suitable area to surface areas in the ranges of 1.57 to 11.61% mainly due to the availability of restricting factors such as escapement, protected areas (e.g., National Parks, Zones of higher Agriculture Potential), and agriculture activities.

Table 5 Available suitable areas in the districts of Zambia
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The provincial total suitable areas available for utility-scale solar photovoltaic power plants development as shown in Table 6 ranged from 2,151.70 km2 (Lusaka) to 16,593.56 km2 (Southern). As earlier stated, Eastern Province has the lowest annual average solar irradiation and also the overall percent suitable area (6.61%) whereas Southern Province has the largest (19.33%). However, Lusaka Province due to its size and population has the lowest overall suitable area (2,151.70 km2) followed by Copperbelt (4,475.66 km2) and highest being the Southern Province (16,593.56 km2) (Fig. 15a, b). In short, comparing only available suitable areas where installation of PV system is suitable, Southern province has about 7.71 times more suitable area than Lusaka Province. However, there are large differences in surface area size between the two provinces, with Lusaka having 3.92 times less surface area than Southern Province. The country has approximately 10.97% equivalent to 82,564.60 km2 of the total suitable surface land area for development of utility-scale solar PV power plant (Table 6).

Table 6 Provincial total suitable areas for utility-scale solar photovoltaic power plants
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Fig. 15
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(a) Provincial total suitable areas for utility-scale solar photovoltaic power plants. (b) Comparison of provincial total surface areas and suitable areas for utility-scale solar photovoltaic power plants

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Electrical Power and Electricity Generation Potential

Table 7 shows district solar energy theoretical and geographical energy potential. Since these potentials depend on the solar irradiation and available surface area and available geographical suitable areas. Hence areas with larger surfaces and receiving the higher solar irradiation such as Northern, Western, and North-Western have the highest overall theoretical potential whereas areas with larger suitable areas such as Southern, Western, Northern, North-Western, and Central Provinces have higher geographical solar energy potential (Table 8 and Fig. 16).

Table 7 District solar energy theoretical and geographical potential
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Table 8 Provincial solar energy theoretical and geographical potential
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Fig. 16
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Provincial solar energy theoretical and geographical potential

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The district-based solar PV technical power potential by technology (Table 9) shows that crystalline silicon based solar PV technologies possess large potential due to less land requirements for installation, with monocrystalline-silicon technology having the largest technical power potential of 5,897.46 GW whereas amorphous-silicon having the lowest potential of 2,752.16 GW due to huge land requirements. The variation in power potential per district is highly depended on the available suitable areas in each district which is as a result of local geographical and terrain features.

Table 9 District solar PV technical power potential by technology
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The provincial solar PV technical power potential per technology (Table 10 and Fig. 17) shows that Southern Province, followed by Western have the highest potential and Lusaka Province being the lowest. Figure 18 shows the comparison of solar PV technologies peak power potential for Zambia, with monocrystalline silicon having the largest whereas amorphous silicon having the lowest potential.

Table 10 Provincial solar PV technical power potential per technology
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Fig. 17
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Provincial solar PV technical power potential per technology

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Fig. 18
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Comparison of solar PV technical power potential per technology of Zambia

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In absolute numbers, the highest electricity generation can be generated in the Southern, Western, Northern, North-Western, and Central Provinces due to large available suitable land areas for utility-scale solar PV system development (Table 12 and Fig. 19). Table 11 illustrates the district solar PV technical electricity generation potential by technology. Just like technical power potential it can be observed that districts with large suitable areas have the largest electricity generation potential.

Fig. 19
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Provincial solar PV technical electricity generation potential

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Table 11 District solar PV technical electricity generation potential by technology
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Table 12 and Fig.19 show that Southern Province, followed by Western Province have the highest potential while Lusaka province has the lowest potential for electricity generation from solar PV based technologies due to aforementioned issues. Figure 20 shows a comparison of the provincial theoretical and geographical solar energy potential and the technical solar electricity potential. It is worth noting that due to technical characteristic of the solar cell technologies and land requirements the technical solar electricity generation potential is lower as compared to the solar energy received on these potential sites. Hence, this presents the need to select suitable solar cell technology for application in the solar energy harvesting systems for optimal solar energy utilization.

Table 12 Provincial solar PV technical electricity generation potential by technology
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Fig. 20
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Comparison of theoretical, geographical, and technical solar energy potential

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Figure 21 shows the comparison of solar PV technologies for electricity generation potential for Zambia considering the available suitable areas and the technology characteristics. İt is observed that monocrystalline provides the highest electricity generation potential followed by polycrystalline and least amorphous. This is mainly due to the differences in amount of land area requirements for the same peak power and the ability of the technology to convert the solar energy into electrical energy (efficiency).

Fig. 21
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Comparison of solar PV cell technologies electricity generation potential

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While Zambia has abundance suitable areas (Fig. 14) and almost evenly distributed sunlight (Figs. 1 and 2) across the country, the focus on surface and suitable areas in the nine provinces and solar irradiation levels, the following can be identified. These factors however should be considered in the planning of national energy mix and also for management of electricity in the national grid once the penetration of solar PV technologies increases and becomes a significant part in the national electricity generation.

  • The highest theoretical solar energy potential is in Northern Province (313,025.37TWh/year) due to large surface areas of the province.

  • However, the highest geographical and technical solar energy potential for solar electricity generation is in Southern Province (35,117.56TWh/year) due to large available suitable areas.

  • From highest yield point of view, due to abundance of sunlight received by Western province (5.89kWh/m2-day), the annual yields per installed solar PV systems peak are expected in Western province as compared to the rest of the country.

  • Comparing the PV technologies, large electricity generation differences can be observed not only at district level but also at provincial levels. Table 13 indicates crystalline silicon based PV technologies have higher electricity generation potential as compared to thin film per square kilometer.

Table 13 National solar PV technical electricity generation potential
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Table 13 summarizes the estimated solar PV technical electricity generation and solar PV power capacity potential in Zambia for each nine (9) provinces investigated in this chapter.

Conclusion

This chapter provides an approach for identifying and mapping the potential sites for sustainable development of solar PV technologies based power plants using GIS spatial analysis. The chapter has integrated the geographical and technological factors as well as the Laws of Zambia on environmental protection and pollution control legislative framework for evaluating the electricity generation potential and feasible sites suitable for sustainable PV systems deployment across Zambia.

Thus, this chapter shows that Zambia has vast available solar energy technical potential for PV electricity generation. The larger PV electricity generation potential variability at district and provincial level is highly linked with the local geographical features and terrain which affect the availability of suitable area and also local solar energy resource. Therefore, integration and generation of electricity from PV systems has greater potential to mitigate the current energy shortage and increase access to energy for all in Zambia. Furthermore, the suitable land areas in almost all districts and provinces is large enough for solar energy harvesting at utility-scale PV system capable of covering the present and future total electricity demands for Zambia. The identified potential sites have a total of available suitable area of 82,564.601 km2 representing 10.97% of Zambia’s total surface area equivalent to 5,897.46 GW technical power potential. This translates to 10,240.73TWh/year electricity generation potential considering annual average solar irradiation of 5.78 kWh/m2-day and monocrystalline silicon solar PV technology mounted at optimal tilt angle. This potential has capacity to reduce CO2 emission and contribute to achieve energy access for all and Sustainable Development Goals (SDGs).

The identification of potential sites and solar energy potential analysis will help improve the understanding of the potential solar energy, and PV technology can contribute to achieving sustainable national energy mix and increasing energy access for all in Zambia. Furthermore, it will help the government in setting up tangible energy targets and effective integration of solar PV systems into national energy mix. Hence, it is hoped that the suitability map established and the technical potential evaluated will help guide the decision makers and also the investors for planning future electricity generation targets and investment across the country and achieve the 2030 development goals.