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The choice of solar collector type to employ and the number of chosen collectors to subsequently deploy, are important planning decisions, which can greatly influence the economic attractiveness of solar water heating systems. In this paper, a thermo-economic model is developed for the computation of a suitable metric that can aid in choosing the most cost-effective collector to use in a solar water heating system and to determine the optimal sizing of the solar water heater components once the choice collector has been picked. The energy-per-dollar comparison metric, calculated as the annual heat energy output of the collector in an average year, at the so-called “sweet-spot” size of the collector array, divided by the annualized life-cycle cost, based on warranty life and collector initial cost, was recommended as instructive for comparing cost-effectiveness of different solar collectors. For the determination of the sweet-spot size of collector to use in a particular solar water heating system, at which the energy-per-dollar is calculated, the Net Present Value of Solar Savings was used as the objective function to maximize. Ten (10) different models of liquid solar thermal collectors (5 flat plate and 5 evacuated tube type), which are rated by the Solar Ratings & Certification Corporation (SRCC), were ranked according to the energy-per-dollar criterion through the thermo-economic model described in this study. At the sweet-spot collector area for the solar water heating system, the corresponding volume of hot water storage tank and the optimal solar fraction are also simultaneously determined. The required hot water storage volume decreases as the deployed collector area increases while the solar fraction increases, with diminishing marginal increase, until it saturates at a value of unity. For the present case study where the required load temperature is 50 °C and the solar water heating system is located in central Zimbabwe (latitude 19° S and longitude 30° E), the selected collector model happened to be a flat-plate type, which achieved the highest energy-per-dollar score of 26.1 kWh/$. The optimal size of this collector model to deploy in the solar water heating system at the case-study location is 18 m per m of daily hot water demand; with a hot water storage volume of 900 l/m; at an optimal solar fraction of 91%. Although the method of this paper was applied only for a solar water heating application of specified operating temperature, at a specified location, it can be applied equally well for any other solar water heating application and at any other location.

With a growing impetus to meet energy demand through decentralized hybrid mini-grids in rural and semi-urban locations in Sub-Saharan Africa (SSA), the need to accurately assess the market drivers, policy requirements and job creation impacts of this energy system typology within this region cannot be ignored. This work provides a techno-economic impact analysis of decentralized hybrid energy systems in selected locations in SSA. To optimally satisfy an electricity demand time-series for a year and minimize all cost components amortized over a period of 20 years, a least-cost modelling approach and tool is applied. An Employment Factor approach was used to calculate the direct employment impacts across the value chain of different hybrid mini-grid types. Additionally, the Leontief Inverse Input–Output model is used to determine the backward linkage economy-wide-jobs (gross jobs) created. The preliminary results show that the “Solar + Wind + Diesel + Battery” hybrid system (SWDB) has the lowest Levelized Cost of Electricity (LCOE), thus it provides the cheapest means of meeting the electricity demand in the modelled regions. However, the highest locally created direct and net employment impact in the model locations is provided by the “Wind + Battery” (WB) system. Two major sectors, manufacturing and agriculture have the largest number of gross jobs in the local economy for all decentralized hybrid systems analysed. This occurs due to higher linkages between these two sectors and the productive energy use in the area. Conversely, despite higher employment impacts obtained for WB, the cost and duration needed for wind resource mapping and assessment serve as a major bottleneck to WB systems market access in the regions. The results of the sensitivity analysis suggest that by de-risking economic factors, such as discount rates, market access for decentralized renewable energy mini-grids can be improved in SSA.

Clean renewable electric power technologies are important in human life, a great number of thermal solar power plants with different configurations are being considered for deployment all over the world. In this work, we propose a feasibility study of concentrated solar power plant to be set up in different sites of Algeria. It is essential that the plant design will be optimized to each specific location. Among the CSP technologies, we will emphasize on the Fresnel solar power plants at different areas of Algerian Sahara. These areas have been chosen for comparison by shifting the plant to different locations; namely Hassi R’mel, Tamanrasset, Beni-Abbes, and El Oued. Direct Normal Irradiance (DNI), solar field surface, block number, the block surface, block panels’ number, absorber surface, and finally thermal power losses in the absorber are the key parameters for optimization and performance evaluation. The calculation results have been depicted for each site. Indeed, the calculation of performance varies from one site to another with DNI mean values of 788.4, 698.7, 671.7, and 636 W/m, respectively for Tamanrasset, Beni-Abbes, El Oued and Hassi R’mel sites. The surface of solar field, block number, absorber surface and power loss have been also evaluated for the same sites.

Today most of the electrification grids in sub-Saharan Africa (SSA) are found in urban areas. However, these grids experience erratic and frequent power outages for long hours, on average 4.6 h in a day. Due to this problem, many of the African population rely on cheaper but unclean options like backup diesel/petrol generators for lighting, phone charging and other electrical appliances. In Nigeria, millions of people own power generators. These generators are not only noisy but the fuel they use is also costly and result into emissions that pollute the environment. In order to optimize fuel consumption and gradually reduce use of backup generators while increasing share of renewables, a strategy is proposed in this paper to interconnect the existing backup infrastructure to form a bottom-up swarm electrification grid with step by step integration of alternative storages and renewable energy sources. In the swarm-grid excess energy can be generated, sold among grid participants and even at later stage to the national grid. This study focused on a swarm grid hybrid node consisting of a solar PV system integrated with the existing individual backup generators for households and retail shop end users. The hybrid system designed was found to be a suitable system with fuel savings of 39%, excess energy of 27% and reduced cost of backup electricity by 34% for the household end user. For the retail shop end user, the hybrid system was found to be a suitable system with a fuel cost saving of 53%, excess energy generation of 28% and reduced cost of backup electricity by 45%. The study showed that integration of a solar PV system has a high potential to reduce fuel costs for backup generator end users and presents a great opportunity for hybrid swarm electrification approach.

Africa is endowed with a very important renewable energy potential. Exploited, this potential permits the continent not only to get out of the energy poverty it is suffering from but also to ensure a sustainable development. In the present work, the economic viability of renewable power generation is assessed and analyzed. Then an identification and discussion of the impacts that the renewable energy deployment could have on socio-economic progress, health, education, gender equity and rural development are carried out.

The outstanding solar potential in Sub-Saharan Africa (SSA) enables significantly cheaper levelized costs of electricity for decentral solar systems compared to the commonly used diesel generators. Yet, the limited purchase power in SSA impedes rural electrification by solar systems due to their high investment costs. Decentralized Energy-Water-Food systems (EWFS) have the potential to solve this problem. Using solar-powered water pumps, rural communities can supply water for drinking and irrigation. Thereby, agriculture does not depend on rainfall solely and can be done all over the year, which leads to increasing productivity. The increased crop production reduces the community’s expenses for nutrition and enables profit by sales, which in turn enables a payback of the initial investment costs of the solar system. The increased amount of biomass waste enables economically feasible small-scale biogas production. The biogas can be used for electricity production by biogas motors. These can supply private, social or small commercial loads, which enhance the local productivity even more. To identify the least-cost system design regarding the supply of electricity, water and food for the rural village of St. Rupert Mayer, Zimbabwe, the linear optimization model was adapted. was developed for energy system modelling, yet its sector coupling feature allows to add processes like water pumps and commodities such as biogas. The modelling results show that a holistic system including photovoltaics (PV), water pumps, enhanced agriculture and biogas production reduces the levelized costs of electricity (LCOE) from 0.45 USD/kWh by power supply from diesel generators to 0.16 USD/kWh. The modelling results shall support local governments and entrepreneurs in their decision-making.

Access to energy remains a challenge in many regions of Africa. In Zambia, only approximately 28% of the total population of 17 million has access to electricity, with even lower access rates of 5% in rural areas. One of the first challenges in providing these regions with reliable electricity is identifying the location of small settlements that still lack access to electricity. Systematic electrification planning requires in detail information about the current extent of electrification and the spatial location and distribution of villages and households without access. If this is available, transparent planning mechanisms can assess different electrification options such as stand-alone systems, mini-grids or grid extension. This paper aims at detecting a sample of Zambian villages without electricity through remote sensing techniques. These techniques involve applying various machine learning algorithms to classify medium resolution Sentinel 2 multispectral imagery. As results show, it is possible to identify the location and spatial extension of rural settlements in the research area. However, for an accurate assessment of the population in the respective areas, more information, such as population distribution is needed. These results will support official bodies such as the Rural Electrification Authority (REA) as well as private project developers with an entrepreneurial interest in the region. Thereby, this knowledge enables improved legal and regulatory decisions as well as increased private sector participation.

Despite serious efforts of the Lesotho Government, Lesotho Electricity Company (LEC) and other stakeholders, the level of rural household electrification and affordability are still low. Whereas in 2015 about 72% of urban households were grid-connected, this was only true for 5.5% of rural households. Furthermore, the vast majority of rural households use fuel wood, while electricity use, where available, represents a small share of the domestic energy consumption. The LEC data shows that the average consumption per household has decreased by over 60% between 2001 and 2016 in urban households. This indicates that the bulk of new connections are to the rural poor households. This is plausible given that majority of households perceive electricity and other commercial sources of energy to be more expensive than the traditional biomass. Therefore, the paper discusses this existing status quo with regard to rural electrification using data from the major players such as LEC, Rural Electrification Unit and Bureau of Statistics.

Rugged hills and mountain ranges with sparsely populated rural villages characterize the vast majority of Lesotho’s landscape, making it prohibitively expensive and financially unviable to connect these remote villages to the national electricity grid. This lack of access to electricity has hampered many social and economic developments due to insufficient provision of much-needed power to homes, schools, police stations, clinics and local businesses. This paper proposes a renewable energy hybrid power generation system for one such remote town of Semonkong, in Maseru district, Lesotho. The study models, simulates and optimizes the hybrid power system using the load profile of Semonkong town and the available renewable resources data of solar radiation, wind speeds and water flow rates from the nearby Maletsunyane River. The HOMER software is used to provide an optimal system configuration in terms of the minimum levelized cost of electricity (LCOE) and the maximum renewable energy fraction, based on various renewable and alternative energy sources of solar photovoltaic, wind turbine, mini-hydro turbine, diesel generator and battery storage. Sensitivity analysis on solar radiation, wind speed, stream flow, diesel price and energy demand is undertaken to evaluate the feasibility of a completely-renewable power system suitable for this remote area application. Simulation results for the isolated optimized hydro/wind/PV/diesel/battery hybrid system configuration achieves LCOE of US$0.289/kW at a renewable energy fraction of 0.98. Thus, the diesel generator will always be required to augment power supply for Semonkong especially during the dry and cold winter months of May to September when the energy demand is at its peak but the solar radiation and stream flow are at their lowest.

Biomass such as wood, straw or agricultural wastes are a worldwide abundant resource offering high potential for a decentralized energy production and supply which is especially interesting for rural areas. However, substance and energy loss caused by microbial degradation is one major reason for high feedstock costs. As a consequence of the microbial activity and further exothermic processes, heat is produced inside stored piles, leading to temperatures >200 °C, causing partial pyrolysis and self-ignition. This work investigates the degradation process of spruce forest residues in order to generate a better knowledge about underlying processes and possible counteractions. Therefore, the microbial metabolic activity has been described in dependency on the moisture content (MC), particle size distribution and pH by respirometric tests. Respirometric tests revealed the microbial activity over time showing a maximum within the first few days of storage. Our results show that the moisture content is a key factor during wood degradation. No microbial activity could be verified for a MC < 20%. A moisture content of 46% led to a monthly dry matter loss of 5.4%. Raising the pH to an alkaline environment reduced the monthly dry matter loss from 3.1 to 1.8% per month proofing it´s influence on microbial metabolic activity. Further investigations have to be conducted to clarify underlying mechanism and countermeasures.