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The use of machine learning and data-driven methods for predictive analysis of power systems offers the potential to accurately predict and manage the behavior of these systems by utilizing large volumes of data generated from various sources. These methods have gained significant attention in recent years due to their ability to handle large amounts of data and to make accurate predictions. The importance of these methods gained particular momentum with the recent transformation that the traditional power system underwent as they are morphing into the smart power grids of the future. The transition towards the smart grids that embed the high-renewables electricity systems is challenging, as the generation of electricity from renewable sources is intermittent and fluctuates with weather conditions. This transition is facilitated by the Internet of Energy (IoE) that refers to the integration of advanced digital technologies such as the Internet of Things (IoT), blockchain, and artificial intelligence (AI) into the electricity systems. It has been further enhanced by the digitalization caused by the COVID-19 pandemic that also affected the energy and power sector. Our review paper explores the prospects and challenges of using machine learning and data-driven methods in power systems and provides an overview of the ways in which the predictive analysis for constructing these systems can be applied in order to make them more efficient. The paper begins with the description of the power system and the role of the predictive analysis in power system operations. Next, the paper discusses the use of machine learning and data-driven methods for predictive analysis in power systems, including their benefits and limitations. In addition, the paper reviews the existing literature on this topic and highlights the various methods that have been used for predictive analysis of power systems. Furthermore, it identifies the challenges and opportunities associated with using these methods in power systems. The challenges of using these methods, such as data quality and availability, are also discussed. Finally, the review concludes with a discussion of recommendations for further research on the application of machine learning and data-driven methods for the predictive analysis in the future smart grid-driven power systems powered by the IoE. [ABSTRACT FROM AUTHOR]

The transformation of the energy sector, based on the development of low-carbon technologies, is essential to achieve climate neutrality. The Life Cycle Assessment (LCA) is a powerful methodology for assessing the environmental impact of energy technologies, which proves to be a useful tool for policy makers. The paper is a review of the main LCA studies of power generation systems performed over the past ten years aiming at comparing the energy technologies to identify those with the lowest impact on the environment, evaluated in terms of gCO2eq/kWh emissions. Screening criteria were established to include only studies of the highest qualitative significance. The authors decided to assign greater weight to emission values reported in more recent studies. For nuclear and renewable energy technologies, most of the emissions are related to the pre-operational phases. Notably, both nuclear and wind technologies, along with other renewable sources throughout their entire life cycle, exhibit significantly lower and less variable emissions compared with conventional gas- and coal-fired technologies. [ABSTRACT FROM AUTHOR]

Solar energy for water pumping is a possible alternative to conventional electricity and diesel-based pumping systems, particularly given the current electricity shortage and the high cost of diesel. The literature survey includes a comparison between previous studies of pumping systems using photovoltaic cells, and the extent of the influence of external factors such as radiation intensity and temperature on the efficiency of the system. Additionally, the use of water storage to generate electrical energy through potential energy by means of hydraulic generators and the effect of the amount of flow and height on the amount of energy generated, as well as the types of hydraulic generators are discussed in this paper. Nowadays, solar power is a major contributor to the world's electrical energy supply, either by generating electrical energy directly from solar cells or through water storage, which will be covered in this review. When compared to electricity or diesel-powered systems, solar water pumping is more cost-effective for irrigation and water supply in rural, urban, and remote areas. This paper also highlights the challenges that must be overcome to develop high-quality, long-lasting solar power technology for future use. [ABSTRACT FROM AUTHOR]

Summary: In light of the increasing share of renewable energy sources (RES) in electricity generation, the research community is directing their attention toward developing highly efficient DC‐DC high‐gain step‐up converters. These converters are designed to exhibit reduced voltage stress on the switching devices (semiconductors). This paper presents a comprehensive study of a switch voltage stress‐reduced step‐up converter that offers a range of additional features, including the availability of a common ground point, continuous input current, simple two‐mode continuous conduction mode (CCM) operation, wide duty cycle range, and quadratic boosting factor. To achieve the aforementioned features, the converter utilizes two switches with the same operating modes, eliminating the need for complex switching circuitry. Operational modes, steady‐state analysis, and design considerations have been presented in detail. Comparative analysis indicates that the voltage conversion ratio per number of devices in the proposed topology is significantly higher than that of similar topologies. In addition, the voltage stress of switches is considerably less than the topologies addressed in the literature. The study further includes detailed mathematical and experimental analyses, small signal analysis, and hardware implementation to support the theoretical findings. The converter's efficiency has been thoroughly analyzed along with thermal analysis to ensure its reliability. [ABSTRACT FROM AUTHOR]

To overcome its reliance on burning fossil fuels for energy generation and water desalination, Kuwait has pioneered research and cutting-edge projects in renewable energy since the 1980s. This paper examines the power sector in Kuwait and emphasizes the government’s keenness to diversify the country’s electric power supply. It provides a comprehensive overview of Kuwait’s efforts, to emerge as a leading example in the region, fostering collaboration and matchmaking within renewable energy industries. The country’s goal is to meet 15% of the demand for power from renewable energy by 2030, including a reduction in energy use in the building sector by 12% and a decrease in CO2 emissions by 33%. The country’s initiatives revolve around harnessing renewable sources, particularly emphasizing the exploration of solar photovoltaic (PV) systems. Challenges and opportunities are presented to provide information for international institutions, technology companies, designers, researchers, and decision makers, aiming to increase the effectiveness and efficiency of PV project implementation in the country and the region. [ABSTRACT FROM AUTHOR]

A dependable and cost-effective energy distribution scheme is the need in the current scenario of distributed generation of electricity. In the recent past, different economic dispatch techniques are proposed to address this challenge of cost-effectiveness. The fossil fuels issue of pollutant emission and the limited stock has pushed the research community to focus on the direction of renewable energy generation. The aim of this paper is to present a multi-objective cost-emission-based dynamic economic dispatch (MOCEDED) algorithm, which includes thermal, solar, and wind-based power plants. Moreover, the uncertainty of solar and wind power in terms of curtailment is also included in the formulation of the algorithm. The formulated objective function is quadratic constrained programming, which is implemented in General Algebraic Modeling System software. Two paradigms, i.e. only cost-based DED and MOCEDED algorithm, have been analyzed. The outcome of the proposed MOCEDED algorithm shows more promising results than cost-based DED. [ABSTRACT FROM AUTHOR]

Renewable energy sources are a promising hope for avoiding many environmental and economic problems such as the problems of climate change and environmental pollution resulting from fossil fuels combustion, in addition to the problems of oil derivatives high prices and their absence in many countries, which in turn affected the rise in electricity prices. Yemen is considered one of the countries most affected by electricity prices rise due to lack of oil derivatives as a result of the ongoing wars in Yemen. This paper presents a technical and economic study of renewable energy sources for producing and storing electricity. It gives a clear scientific and economic vision for implementation of these projects in one of the Yemeni islands, Socotra. This study has proven the high efficiency of energy sources in this region, which encourages their use to produce electricity to cover the region needs at low prices compared to the current prices of electricity in Yemen., where the cost of electricity from renewable energy sources ranges between 0.073 to 0.25 $ / kWh. The study also provides an assessment of the expected decline in electricity prices until 2030. It should be noted that this study can be applied to many coastal cities and other islands in Yemen at a cost close to this cost. [ABSTRACT FROM AUTHOR]

Solar power occupies a significant position among global renewable energy sources due to its abundant energy potential. Consequently, its contribution to electricity generation is steadily increasing. However, obtaining peak efficiency from fixed solar photovoltaic (PV) panels is a formidable task due to their limited ability to consistently tap into solar energy. To tackle this issue and mitigate energy efficiency losses, the utilization of solar tracking systems has emerged as an exceptionally effective solution. These systems enable continuous adjustment of the panels' position to align with the sun's trajectory, optimizing energy absorption and enhancing overall performance. This paper presents the performance and cost analysis of three distinct solar panel tracking systems, namely, a fixed system, a single-axis system, and a dual-axis system. The systems are operated under identical coordinates and conditions. The production data are collected over a period of 15 days for comparative analysis. The tracking movements of the systems are controlled using Arduino. The mechanical components are specifically designed for the establishment of each system. The findings of this study indicate that both single-axis and dual-axis solar tracking systems outperformed fixed systems in terms of power generation. The single-axis system demonstrated a 24.367% increase in power production, while the dual-axis system showed a 32.247% increase compared to the fixed system. Moreover, a cost analysis was carried out considering the installation expenses and power production data of the three systems. It was determined that the single-axis tracking system achieved payback in 0.39 years less compared to the fixed system, while the dual-axis system achieved payback in 1.48 years less compared to the fixed system. Overall, this study underscores the advantages of implementing solar tracking systems, particularly in the single-axis and dual-axis configurations, as they contribute to higher power generation and cost-effectiveness compared to fixed systems. [ABSTRACT FROM AUTHOR]

Decarbonization of the power sector in China is an essential aspect of the energy transition process to achieve carbon neutrality. The power sector accounts for approximately 40% of China's total CO2 emissions. Accordingly, collaborative optimization in power generation expansion planning (GEP) simultaneously considering economic, environmental, and technological concerns as carbon emissions is necessary. This paper proposes a collaborative mixedinteger linear programming optimization approach for GEP. This minimizes the power system's operating cost to resolve emission concerns considering energy development strategies, flexible generation, and resource limitations constraints. This research further analyzes the advantages and disadvantages of current GEP techniques. Results show that the main determinants of new investment decisions are carbon emissions, reserve margins, resource availability, fuel consumption, and fuel price. The proposed optimization method is simulated and validated based on China's power system data. Finally, this study provides policy recommendations on the flexible management of traditional power sources, the market-oriented mechanism of new energy sources, and the integration of new technology to support the attainment of carbon-neutral targets in the current energy transition process. [ABSTRACT FROM AUTHOR]

The feasibility and potential assessment (PA) of solar PV energy is one of the key factors in identifying the most promising areas for the installation of solar PV stations. It determines the useful energy generated in the given area. This paper assesses the solar energy distribution and PA in the North Shewa administration zone. Based on the data collected and analysis made, it is found that more than 80% of the North Shewa areas are suitable for the solar energy generation for off-grid and on-grid systems. Hence, the solar potential of the North Shewa zone completely fulfills the standards of sunshine, solar radiation, and temperature. That is, most of the areas have solar radiation of 5.2 kWh/m2, and daily sunshine is greater than 7 h. The maximum energy production is found in December in Shewa Robit, Mehal Meda, Eneware, Debre Berhan, Alem Ketema, and Sela Dengay with 175.35 kWh, 188.18 kWh, 180.78 kWh, 189.54 kWh, 175.78 kWh, and 189.63 kWh, respectively. This is a good opportunity for investors to invest in solar PV electricity generation. It will solve the issue of electricity supply to the community, which currently relies on wood and fossil fuels. It also highlights the positive opportunities for the future implementation of solar energy. [ABSTRACT FROM AUTHOR]

Real-time hybrid simulation (RTHS) divides a structural system into an analytical and experimental substructure. The former is based on a well-established analytical model while the latter consists of a physical model in the laboratory, for which there is not a well-established analytical model. This paper extends real-time hybrid simulation to monopile-type Offshore Wind Turbines (OWTs) to enable the investigation of their behavior considering the response of pile foundations under operational and more severe conditions. The embedded foundation and surrounding soil of the OWT are modeled physically in a soil box in the laboratory while the remaining parts of the system and loading are modeled analytically. The program OpenFAST, developed by the National Renewable Energy Laboratory (NREL), is linked to the RTHS coordinator to determine the hydrodynamic and aerodynamic loads acting on the OWT, along with modeling the dynamics of the electric power generation equipment and associated controller for the OWT. The RTHS framework along with its initial implementation and validation are described in this paper. RTHSs of a 5 MW OWT subjected to operational and more severe conditions are performed to experimentally validate the framework. The framework offers a realistic approach to investigate the behavior of OWT structures supported on monopiles. This approach accounts for the coupled response of the OWT structure with its foundation, while experimentally capturing the nonlinearities of the soil-foundation interaction in real-time. • RTHS is extended to offshore wind turbine monopile structures. • OpenFAST software is modified and integrated into a RTHS framework. • Validated RTHS framework that incorporates the complete system into the simulation. • RTHS enables experimental assessment of offshore wind turbine foundation behavior. • RTHS computational challenges of offshore wind turbine structures are presented. [ABSTRACT FROM AUTHOR]

Renewable Energy Communities (RECs) are emerging as an effective concept and model to empower the active participation of citizens in the energy transition, not only as energy consumers but also as promoters of environmentally friendly energy generation solutions, particularly through the use of photovoltaic panels. This paper aims to contribute to the management and optimization of individual and community Distributed Energy Resources (DER). The solution follows a price and source-based REC management program, in which consumers' day-ahead flexible loads (Flex Offers) are shifted according to electricity generation availability, prices, and personal preferences, to balance the grid and incentivize user participation. The heuristic approach used in the proposed algorithms allows for the optimization of energy resources in a distributed edge-and-fog approach with a low computational overhead. The simulations performed using real-world energy consumption and flexibility data of a REC with 50 dwellings show an average cost reduction, taking into consideration all the seasons of the year, of 6.5%, with a peak of 12.2% reduction in the summer, and an average increase of 32.6% in individual self-consumption. In addition, the case study demonstrates promising results regarding grid load balancing and the introduction of intra-community energy trading. [ABSTRACT FROM AUTHOR]

The global drive to achieve the climate change mitigation targets set during the Paris Agreement and COP26 necessitates sustainable electricity generation from renewable energy sources. However, renewable energy systems face economic challenges due to unattractive feed‐in‐tariffs (FiT). This paper presents a mathematical programming model to optimise the participation and electricity generation by biomass power plants in a FiT programme. A disjunctive fuzzy optimisation approach is adopted in this work due to the presence of several biomass power plants, thus resulting in a multi‐objective optimisation. The newly developed mixed‐integer linear programming (MILP) model maximises the overall satisfaction extent of biomass power plants in power generation. The optimisation model ensures the satisfaction of all biomass power plants' technical and economic constraints. A base case study of seven power plants utilising various palm biomass is used to demonstrate the disjunctive fuzzy optimisation approach for the MILP model. This is followed by a scenario investigating the impact of demand variation. The optimisation of the case studies favours the utilisation of empty fruit bunch (EFB), palm oil mill effluent (POME), and palm mesocarp fibre (PMF) for sustainable electricity generation. Palm kernel shell (PKS) is the least preferred palm biomass due to its lowest net availability of useful energy from biomass combustion. This work provides a decision tool for the selection of biomass type during electricity generation. The MILP model in this work may be readily extended for any number of power plants, handling a variety of biomass feedstocks. [ABSTRACT FROM AUTHOR]

Green technology or renewable energy system (RES) is an advancement of the electricity generation which creates pollution free environment. Since last 15–20 years, renewable power plant works in the traditional way over the world and needs technology enhancement. This paper presents a complete review of application of recent advanced technology in the field of RES. The paper analyses and discusses the potential application of artificial intelligence, the internet of things, cloud computing, big data, blockchain and game theory in the area of RESs such as solar energy, wind energy, biomass energy, etc. At the end of this paper, the ordinal assessment of application of recent technology for different objectives of RES is presented. [ABSTRACT FROM AUTHOR]

At present, energy represents a key element in the social and economic development of a territory. This is particularly true for fragile territories that are not interconnected, such as small island states. As is true for many of the Small Island Developing States (SIDS) worldwide, the energy situation of the Comoros is substantially based on fossil fuel imports. The socioeconomic development of this archipelago is overwhelmingly dependent on energy security from sustainability, availability and affordability perspectives. As a forward-looking response to energy vulnerability, the deployment of renewables to diversify the generation of electricity appears to be an essential prerequisite for guaranteeing a sustainable future. Nevertheless, despite a high potential for renewable energy, only 3.8% of the electricity supply in the Comoros is provided by hydropower. This paper provides a comprehensive overview of the energy situation throughout the Comoros and focuses on renewable energy opportunities to facilitate the supply of green power. This study ultimately shows that renewable energies are rarely exploited despite the powerful potential of different resources. Finally, this paper attempts to provide recommendations for the Comoros to pursue a more sustainable future. • Analysis of the current energy situation of Comoros. • Defining renewable potential and ongoing actions. • Analysis of the specific barriers and policy to the development of RES in the Comoros. [ABSTRACT FROM AUTHOR]

In the era of high energy demand caused by rapid population growth, renewable energy is required in the energy mix for the sustainability of both human and industrial development. This paper investigates the potential of extracting heat energy from abandoned oil and gas wells for electricity production. Four wells located in the Niger Delta were considered. Each well has its properties and steam flow rates. The geothermal reservoir was modeled as a liquid-vapor-dominated system at in situ reservoir conditions. The fluid temperature in the reservoir was determined to be 170oC in the reservoir. Equations describing geothermal resource potentials, energy flow in a wellbore, and gross electrical power production using turbines were presented. A Single-flash turbine system was used because steam was produced in the reservoir. MATLAB software was used in the simulation of the heat transfer process. The results showed that the geothermal energy corresponding to the reservoir considered was 2.45 x 1012 Joules. The electricity production result showed that there was a reduction in gross electrical power output due to an increase in sink temperature, while the relationship between gross electrical power output and separator temperature was such that there was an initial increase in gross electrical power output due to an increase in separator pressure until an optimum point was reached wherein further increase in separator pressure progressively decreased the value of the gross electrical power output. The optimum separator temperatures for well 1, well 2, well 3, and well 4 were 120oC, 120oC, 110oC, and 105oC respectively at a sink temperature of 45oC. Because of the high reservoir pressure used, the separator pressure was higher than the actual reservoir pressure. Proper understanding of heat flow which enables accurate estimation of heat production is necessary to maximize heat extraction from the reservoir. The simulation conducted reveals that geothermal resources holds great potentials for electrical energy generation and should be put to developmental use in Nigeria as a means to increase the total power generation and increase the portion of renewables in Nigeria energy value chain. [ABSTRACT FROM AUTHOR]

In recent years, one of the key postulates in the European Union's policy has become the development of renewable energy sources. In order to achieve the desired synergy effect, the idea of combining two selected sources of energy appeared. This article presents a technical and economic analysis of a hybrid connection of a ground source heat pump with a photovoltaic installation. Taking into account the heat demand of the building, a ground heat pump with a catalog nominal heating power of 25 kW was selected. This article presents the problem of the economic profitability of using a hybrid combination of a heat pump and photovoltaic panels in domestic hot water and central heating systems. The justification for the use of such heat sources in these installations is due to global trends and the gradual departure from conventional energy sources such as oil or gas boilers. This paper presents the economic and ecological results of using the pump heat connected together with photovoltaic panels. In the economic analysis, with the assumed installation costs related to the use of the considered heat pump and PV, two parameters commonly used in the investment analysis (static and dynamic) were used, namely, the simple payback period and the net present value of the investment. For the adopted assumptions, the usable area of the facility and the number of years of use were indicated, at which the investment in question is competitive with other alternative investment interest methods and will start to bring tangible benefits. The performed analysis also has measurable environmental benefits in the form of a reduction in carbon dioxide emissions at the level of 2893 kg/year into the atmosphere. The presented solution will help future investors understand the investment profitability mechanism for their households. [ABSTRACT FROM AUTHOR]

This paper presents an inerter-integrated wave energy converter (WEC) for vibration mitigation of offshore floating structures. The proposed WEC complies a floating buoy and an upper structure placed over the floating buoy connected by a spring and a ball screw with a rotational mass, which converts linear motion to rotational one, and the ball screw is connected to a rotating generator. As the two bodies move separately, the inertial force proportional to the relative acceleration of the two bodies called inerter is produced. This mechanism, similar to passive vibration reduction systems in automobiles and civil structures, not only produces electric power but also mitigates the vibration induced by the wave disturbances acting on the floating buoy. In this research, its analytical model was developed based on the two-degree-of-freedom dynamic model and the circuit equation of the generator. Numerical studies considering only the heave direction showed that the proposed WEC can achieve electric power generation and vibration mitigation of the upper structure at the same time. Moreover, to verify the efficacy experimentally, a small-scaled prototype was designed, and wave flume testing was conducted, which demonstrated a response reduction of more than 40% compared to the device without the proposed mechanism. • An WEC with inerter is proposed for vibration mitigation of floating structures. • The WEC achieves both vibration suppression and power generation simultaneously. • An analytical model is developed to evaluate the performance numerically. • Wave flume testing is conducted to validate the concept of the proposed WEC. [ABSTRACT FROM AUTHOR]

Conventional petrol vehicles emit a substantial quantity of greenhouse gases, leading to increasingly serious global warming problems. The expansion and development of renewable power generation technologies is conducive in promoting the use of electric vehicles, which are more environmentally friendly. This paper proposes a multi-objective power expansion model considering renewable energy policy objectives. The model regards the problem as a multi-period optimisation task, taking the newly installed capacity and the power generation capacity of each power generation technology as decision variables, and simulating the uncertain factors in the planning process using Geometric Brownian Motion and Monte Carlo approaches. The optimisation objective of the model is to minimise expected costs, reduce risk and environmental impacts, and incorporate changing policy objectives into the constraints to meet policy makers' expectations for renewable energy development. Then, a decentralised target search-based multi-objective evolutionary algorithm is proposed to solve the model. Its effectiveness is verified by a numerical example using real data from the Chinese power system. The experimental results show that the proposed algorithm exhibits improved performance compared with benchmark algorithms and provides high quality and diverse Pareto-optimal solutions to decision makers. Finally, the optimal plans for power expansion and generation mix under different preferences and policy objectives are discussed and corresponding recommendations are made. [Display omitted] • Planning for the expansion of power generation under uncertainties is determined. • Strategies for the expansion of power generation towards renewable energy are optimised. • A novel multi-objective evolutionary algorithm with a constraint handling method is developed. • The impact of multiple renewable energy policies on power generation expansion planning is discussed. [ABSTRACT FROM AUTHOR]

This paper investigates the challenges isolated islands face in transitioning from fossil fuel-based electricity generation to renewable energy sources. The Canary Islands serve as a case study, where photovoltaic and wind power are the primary renewables, but their variability requires a deep techno-economic analysis. The island's energy demand is predicted to rise by 100% due to economic growth, electrification and electric vehicles. However, implementing renewable systems encounters obstacles, such as limited suitable sites and protected areas. The study uses Wilks' methodology and Monte Carlo sampling to explore 59 combinations of randomly selected inputs of the uncertain variables, aiming for a 95/95% coverage and confidence level in the results. In most cases, they experience energy shortages, failing to meet electric demand. Even though a new generation mix appears to cover demand under all circumstances, the uncertainty unveils a different reality, leading to an approximate 25% increase in system costs. Surpluses in energy generation, while seemingly positive, can pose challenges. The new system's Levelized Cost of Energy increases from around 14 to 17c€/kWh. These cost increases are contingent upon future performance and the variability of uncertain parameters, leading to excesses ranging from slightly below 25% to over 40%. • Demand coverage scenario designed to meet electric demand through renewable sources. • Uncertainty analysis of a scenario for the complete electrification of the economy. • Best Estimate Plus Uncertainty analysis implementing the Wilks' methodology. • Resizing the system to cover the demand with 95% coverage and confidence levels. • Differences in using deterministic and stochastic methods for electric demand coverage. [ABSTRACT FROM AUTHOR]

The share of wind-based electricity generation is gradually increasing in the world energy market. Wind energy can reduce dependency on fossil fuels, as the result being attributed to a decrease in global warming. This paper discusses and reviews the basic principle parameters that affect the performance of wind turbines. An overview presents the introduction and the background of energy consumption, following the order of the elaboration of wind turbines, including mathematical models, categories of wind turbines were critically discussed. Moreover, it also focuses on materials that are commonly considered for wind turbine manufacturing, and the process used to recycle them. The scale of recycling methods for fiberglass and thermoplastic is presented in the respective section. Various parameters that reduce the function of wind turbines are explained in depth. This review also discusses various environmental impacts of wind turbines. Future research studies are suggested in the conclusion section. [ABSTRACT FROM AUTHOR]

Climate change motivated by human activities constitutes one of the main challenges of this century. To cut carbon emissions in order to mitigate carbon's dangerous effects, the current energy generation mix should be shifted to renewable sources. The main drawback of these technologies is their intermittency, which will require energy storage systems to be fully integrated into the generation mix, allowing them to be more controllable. In recent years, great progress to develop an effective and economically feasible energy storage systems, particularly motivated by the recent rise of demand for electric transportation, has been made. Lithium-ion (Li-ion) battery prices have fallen near 90% over the past decade, making possible the affordability of electric vehicles and transforming the economics of renewable energy. In this work, a study on storage capacity demand previously presented as conference paper is expanded, including a deep analysis of the Spanish generation mix, the evaluation of the energy storage requirements for different low-carbon and carbon-free scenarios in Mainland Spain, and the calculation of the CO2 emissions' reduction and the associated storage costs. [ABSTRACT FROM AUTHOR]

Short-term forecasting of electricity generation from variable renewable energy sources is not an end in itself but should provide some net benefit to its user. In the case of electricity trading, which is in the focus of this paper, the benefit can be quantified in terms of an improved economic outcome. Although some effort has been made to evaluate and to improve the profitability of electricity forecasts, the understanding of the underlying effects has remained incomplete so far. In this paper, we develop a more comprehensive theoretical framework of the connection between the statistical and the economic properties of day-ahead electricity forecasts. We find that, apart from the accuracy and the bias, which have already been extensively researched, the correlation between the forecast errors and the market price spread determines the economic implications - a phenomenon which we refer to as 'correlation effect'. Our analysis is completed by a case study on solar electricity forecasting in Germany which illustrates the relevance and the limits of both our theoretical framework and the correlation effect. • The economics of short-term electricity forecasts are studied analytically and empirically. • The value and the risk of forecast-based electricity trading are evaluated. • We find that the economics depend on the correlation of forecast errors with prices. • Hence, the most accurate forecast is not necessarily the most accurate. [ABSTRACT FROM AUTHOR]

Penetration of renewable energy resources into grid is necessary to meet the elevated demand of electricity. In view of this penetration of solar and wind power increasing immensely across the globe. Solar energy is widely expanding in terms of generation and capacity addition due its better predictability over wind energy. Electricity pricing is one of the important aspects for power system planning and it felicitates information for the electricity bidder for accurate electricity generation and resource allocation. The important task is to forecast the electricity price accurately in grid interactive environment. This task is tedious in renewable integrated market due to intermittency issue. In this paper, investigation has been done on the effect of solar energy generation on electricity price forecasting. Different state of the art Machine learning (ML) models have been applied and compared with LSTM model for electricity price forecasting and the evaluation of the impact of solar energy generation on electricity price has been done. During the investigation it was found from the results that the LSTM model outperform all other models and impact of solar energy generation on electricity price is evaluated using forecasting metrics. The forecasted electricity price considering the factor of solar energy generation was lower as compared with the forecast without solar energy generation. The reliability test of the MAPE values has been performed by calculating confidence interval for proposed model. [ABSTRACT FROM AUTHOR]

This paper aims to assess the implications of an increased electricity generation from renewable energy on the Thai electricity generation sector with a particular focus on energy security and CO2 emissions mitigation potentials. For this purpose, three scenarios (REF, AEDP2015 and AEDP2018), developed in this paper, represent penetration levels of electricity generated from renewable energy. The implications have been analyzed through the application of LEAP model for the period 2018-2037. The analyses revealed that high penetrations of renewable energy would have positive impacts on the Thai electricity generation from several perspectives including improving the diversification of electricity supply, decreasing fossil fuel imports for generating electricity, less dependency on fossil fuel, environmentally friendly power generation, utilizing agricultural wastes, and build-up of local capabilities in electricity generation. Moreover, the energy transition due to disruptive innovations would make renewable energy more attractive. However, the transition would raise several challenges for the Thai electricity system, for example, capital-intensive investment, centralized electricity system, traditional regulatory framework and a lack of social involvement. In order to address the transitional challenges, the Thai government has initiated a number of policies including the upgrade of the grid to smart grid, the development of energy storage and the revision of the regulations to support local energy business. In addition to the initiation of the government's policies, this paper suggests that a structural change in the form of a separation between generation and transmission functions of the state electric utility, the development of new infrastructure and network regulation, and collaborations among stakeholders by increasing more participation and governance as well as aligning regulatory arrangement taking into account more on social objectives would provide a robust pathway to efficiently integrate renewable energy into the Thai electricity system. [ABSTRACT FROM AUTHOR]

This paper performs a concept on a new exploration of electricity generation by harvesting the kinetic energy from landing aircraft. Firstly, this paper analyzes and tabulates the current status of renewable energy sources and the conventional power generations in Malaysia's electric supply until 2017. It has been reviewed based on the demand, availability, and power production of the sources. At the same time, the locations and providers for several energy supplies have been identified with the evidence of its rated power being generated. Next, this paper also highlights the plan for achieving a low-carbon country based on the plans which have been in place between 1970 until 2017 in order to create a zero-carbon generation by 2030 for Malaysia's energy sector. Toward the end of this paper, the authors suggest a new method on decarbonization technologies for clean energy in order to reach zero-carbon generation earlier than 2030. It is by introducing a new topology of electrical power generation system using waste energy, which is kinetic energy based on landing aircraft, for the possibility of power generation for a new Malaysia. [ABSTRACT FROM AUTHOR]

Renewable energy production is constantly growing worldwide, and some countries produce a relevant percentage of their daily electricity consumption through wind energy. Therefore, decision support systems that can make accurate predictions of wind-based power production are of paramount importance for the traders operating in the energy market and for the managers in charge of planning the nonrenewable energy production. In this paper, we present a decision support system that can predict electric power production, estimate a variability index for the prediction, and analyze the wind farm (WF) production characteristics. The main contribution of this paper is a novel system for long-term electric power prediction based solely on the weather forecasts; thus, it is suitable for the WFs that cannot collect or manage the real-time data acquired by the sensors. Our system is based on neural networks and on novel techniques for calibrating and thresholding the weather forecasts based on the distinctive characteristics of the WF orography. We tuned and evaluated the proposed system using the data collected from two WFs over a two-year period and achieved satisfactory results. We studied different feature sets, training strategies, and system configurations before implementing this system for a player in the energy market. This company evaluated the power production prediction performance and the impact of our system at ten different WFs under real-world conditions and achieved a significant improvement with respect to their previous approach. [ABSTRACT FROM AUTHOR]

• This paper presents the Survey of AI Methods for Renewable Energy Forecasting. • Taxonomy of AI for solar and wind renewable energy is presented. • Combinations of ML and metaheuristic methods for renewable energy are discussed. • Prospects of improved metaheuristic algorithms for renewable energy forecasting are presented. The efforts to revolutionize electric power generation and produce clean and sustainable electricity have led to the exploration of renewable energy systems (RES). This form of energy is replenished and cost-effective in terms of production and maintenance. However, RES, such as solar and wind energies, is intermittent; this is one of the drawbacks of its usage. In order to overcome this limitation, studies have been undertaken to forecast its availability and power output. The current trending method of forecasting availability and the power generated by the RES is the artificial intelligence (AI) method. However, with all its potential, traditional AI, such as Artificial Neural Network (ANN), Support Vector Machine (SVM) and many more, does not have it all. Because of this, metaheuristic algorithms are being explored as optimization techniques to increase the performance accuracy of these AI forecasting methods and overcome some challenges of traditional AI models. This study presents an insightful survey of AI (traditional AI and metaheuristic) methods explored to forecast the availability of solar and wind renewable energy systems. A survey of the existing surveyed literature was presented. The taxonomy of the explored AI in RES was formulated, and the theoretical backgrounds of some of the traditional AI algorithms were presented. Also, the various forms of metaheuristic algorithms and the improved versions applied to optimize classical AI methods to forecast RES systems' availability and power output were surveyed. A conceptual framework of the hybrid AI application in RES was formulated. Finally, the survey discussion, insight, challenges of the existing models and future directions were presented. [ABSTRACT FROM AUTHOR]

Despite the importance of cost of capital and expected returns from investing on renewable electricity generation in Africa on one hand and the implications of such investments on economic, social and environmental factors on the other. These concepts are not well understood by non-finance and finance actors respectively. Studies that analyze renewable energy-growth nexus at regional and global level are lacking. Instead, existing studies emphasize on individual countries or panel of countries. The paper undertakes comparisons of costs and returns of selected renewable energy technologies in Africa and presents estimates of its impact on Africa's economic growth between 1990 and 2014. Even with abundant renewable resources and well performing technologies measured using levelized cost of electricity and expected internal rate of return, investment on renewable electricity generation is quite low. Findings from Autoregressive Distributed Lag approach and cointegration established a long run relationship among hydro power generation, carbon emissions and electricity consumption. Error Correction Model results suggest that investment in renewable generations excluding hydro power generation is boosted by economic growth, so long as development of such renewables corresponds with lesser carbon emissions. To accelerate renewable development, SSA countries will need to deploy initiatives that enhances national economic growth. [ABSTRACT FROM AUTHOR]

According to statistical reports, thermal power plants have long played a critical role in supplying electricity using fossil fuels. However, due to the high investment and operation costs of these power plants and their destructive effects on the environment, renewable energy sources (RESs) in power networks have been considered an effective alternative to traditional power plants. Optimal scheduling of microgrid in smart grids has a significant impact on reducing energy consumption, environmental pollutants and end-user's energy prices. In this paper, the influence of plug-in hybrid electric vehicles (PHEVs) charging on microgrids' optimal operation is evaluated. To assess the behaviour of PHEVs, three various charging patterns consisting of uncontrolled, controlled and smart charging methods are considered. Uncertainties due to forecast error in the PHEVs, loads, prices and renewable source output power are also considered in microgrid modelling energy management. To deal with the optimisation scheduling of microgrid considering uncertainty, a modified harmony search (MHS) algorithm is used. The suggested scheme is validated using simulations and without the PHEV charging effects compared with the conventional methods. [ABSTRACT FROM AUTHOR]

Considering the broad range of applications, efficient retrieval and storing electrical energy methods are still challenging. Besides the load variations, the ever‐increasing intermittent renewable energy penetration into the grid system has witnessed the system complexities. In off‐grid applications, energy storage can balance electricity consumption and electricity generation to avoid voltage and frequency deviations. This research paper focuses on the energy management of an off‐grid climate refuge system used for hot and arid locations with a system comparison for two routes of different storage techniques, namely flywheels and a lithium‐ion battery. The proposed system can generate its power from photovoltaics and provide cooling and other auxiliaries through vapor compression cycle and water misting units with an operation of about 16 hours (ie, from 7:00 am to 11:00 pm) on the weekdays and 12 hours on the weekends. A comparison of levelized costs is conducted for the evaluation using HOMER software. The annual energy production by solar photovoltaics for the proposed system is 20 MWh, and the annual consumption is 16 MWh. The photovoltaic‐battery storage system has shown the lowest cost of electricity, corresponding to 0.761 $/kWh, and net present cost of $66 238 and is optimum in all sensitivity analysis cases. [ABSTRACT FROM AUTHOR]

To moderate global warming, conventional fossil fuels are depleted. As the population increased with the rising standard of living and industrial growth, the global environment is affected and cause the greenhouse gases occurrence, which are frequently increased by unlimited use of fossil fuels. The generation of electric power loads increases the power demand on the basics of modern power technology development. Several benefits can be attained by installing the distribution generation with the quality and reliability of power delivered. However, the global energy problem can be resolved by renewable energy sources as an alternative energy generation. Technological developments in the last decade have increased the use of renewable energy sources. In worldwide, several renewable energy sources are used to attain their own power demand. The photovoltaic (PV) generation is the essential renewable energy source to serve the increasing electrical loads. The fastest-growing PV system has the naturally available energy sources of robust evolution with elegant benefits. The foremost objective of this paper is to examine the performance of the PV system with various Maximum Power Point Tracking (MPPT) algorithms. The solar irradiance and temperature make it complex to track the MPPT of PV systems. This review is about various MPPT algorithms like online, offline, and hybrid methods. The selected algorithms from each discussion are simulated in MATLAB/Simulink environment to match their performance in footings of the dynamic response and efficiency of the PV system under the variations of solar irradiance and temperature. An explanation and discussion of the PV system are achieved with the study of different types of MPPT algorithms of PV systems. [ABSTRACT FROM AUTHOR]

Renewable energies (RE) in Chile and around the world have experienced outstanding growth in recent years. However, RE technologies such as solar photovoltaic and wind generate an imbalance between generation (offer) and consumption (demand) because of their intermittent and variable nature. Moreover, RE's natural variability makes it necessary for conventional technologies to play a significant role in adjusting for the imbalance in the electric system frequency. As variable RE penetration grows, the need for frequency regulation will increase and, depending on how those higher costs are financed, this could lead to a disincentive to invest in conventional plants that provide that service. In this paper we study the impact of increased photovoltaic energy penetration, the leading RE in Chile, on the profitability of different conventional generation technologies. Specifically, we analyze the role that the frequency control remuneration mechanism has on that impact. For this purpose, four different solar photovoltaic penetration scenarios are simulated in Chile's Northern System, comparing two payment criteria for frequency regulation services: i) a cost-based pricing system whose payments relate to the incurred costs and ii) a market-based pricing system where the marginal cost of providing the services is paid. The results show that as installed photovoltaic capacity increases, the average marginal cost of energy (operation cost) decreases due to a displacement of more expensive power plants, but at the same time, investment cost may increase. In the long run, contract prices change as a result of falling operational costs and rising investment cost, resulting in changes in the profitability of all technologies. Finally, while both cost-based and market-based systems reward the ability to regulate frequency, the technologies performing the regulation receive different payments for the service, affecting both their profitability and the incentives for investment. • High penetration rates of intermittent renewable energies require more frequency regulation services. • Depending on the type of regulation, incentives to invest in technologies providing ancillary services might diminish. • Incentives to invest do not change between a regulatory scheme markedbased compare to one cost-based. • Profitability of the natural gas power plants is the one increasing most under market-based regulation. • Under market-based regulation the profitability of photovoltaic and eolic power plants decreases. [ABSTRACT FROM AUTHOR]

Abstract The use of renewable energy resources, especially wind power, is receiving strong attention from governments and private institutions, since it is considered one of the best and most competitive alternative energy sources in the current energy transition that many countries around the world are adopting. Wind power also plays an important role by reducing greenhouse gas emissions and thus attenuating global warming. Another contribution of wind power generation is that it allows countries to diversify their energy mix, which is especially important in countries where hydropower is a large component. The expansion of wind power generation requires a robust understanding of its variability and thus how to reduce uncertainties associated with wind power output. Technical approaches such as simulation and forecasting provide better information to support the decision-making process. This paper provides an overview of how the analysis of wind speed/energy has evolved over the last 30 years for decision-making processes. For this, we employed an innovative and reproducible literature review approach called Systematic Literature Network Analysis (SLNA). The SLNA was performed considering 145 selected articles from peer-reviewed journals and through them it was possible to identify the most representative approaches and future trends. Through this analysis, we identified that in the past 10 years, studies have focused on the use of Measure-Correlate-Predict (MCP) models, first using linear models and then improving them by applying density or kernel functions, as well as studies with alternative techniques, like neural networks or other hybrid models. An important finding is that most of the methods aim to assess wind power generation potential of target sites, and, in recent years the most used approaches are MCP and artificial neural network methods. Graphical abstract Image 1005 Highlights • This paper provides an overview of how the analysis of wind energy has evolved over the last years. • We employed an innovative and reproducible literature review approach called Systematic Literature Network Analysis. • From 145 articles was possible to identify the most representative approaches and future trends. • Developing countries will reach the same level of investment in the field of wind energy. [ABSTRACT FROM AUTHOR]

Abstract African countries are in a unique position to reap the socio-economic and environmental benefits of renewable resources as a means for meeting increasing energy demand in a sustainable way. A critical obstacle for the deployment of renewable energy technologies in Africa is the difficulty of attracting sufficient and affordable finance. This paper compares the impact of financial conditions on the cost of electricity generation across six renewable and three fossil-based technologies in 46 African countries. The results show large cost variations and highlight the extent to which renewables are disadvantaged by current financial practices. The energy-economy-environment model TIAM-ECN is used to show how lowering financing costs results in a much higher deployment of renewables. For example, solar PV could account for 10–15% of total electricity generation by 2050, even without explicit climate policy, thanks to financial de-risking programmes. The results demonstrate that changes in financing schemes could outweigh the impact of technology learning. This paper also demonstrates that, once ambitious climate policies are in place, reducing financing costs for renewables could be an efficient way to lower greenhouse gas emissions. Financial de-risking is thus a key ingredient for unlocking the renewable energy potential in Africa. Highlights • We show how renewables are disadvantaged by today's financial practices in Africa. • We show how lower financing costs result in a higher deployment of renewables. • PV can account for 10–15% of electricity generation by 2050 without climate policy. • Changes in financing schemes could outweigh the impact of technology learning. • Financial de-risking is key for unlocking the renewable energy potential in Africa. [ABSTRACT FROM AUTHOR]

Abstract Tidal energy is one of the most abundant renewable energy sources. Due to its intermittent nature, the integration of tidal energy within a Microgrid (MG) requires appropriate energy management strategies. Some important considerations are tidal energy generation prediction, energy storage requirements, load profile and demand within the Microgrid, and energy pricing structures. This paper considers an MG scenario that includes a small scale tidal farm near Darwin in north of Australia. A tidal power prediction model is introduced using tidal current speed data. Then, for a fixed-size energy storage system (ESS), an optimal scheduling strategy is devised using Particle Swarm Optimization (PSO) to achieve minimum operating costs in the MG. The work presented in this paper provides a framework for the planning of MGs that include tidal generation in their energy mix. Highlights • Visibility of tidal power in the North of Australia. • Tidal power prediction based on tidal current speed observation. • Optimal scheduling for a tidal Micro-grid using Particle Swarm Optimisation. [ABSTRACT FROM AUTHOR]

Although FRT capability is claimed in Japanese grid code for RE, DVS capability is not. In some European countries, not only FRT but also DVS is claimed. Whether this choice of our grid code is pragmatically adequate or not? To answer the question, it is necessary to evaluate FRT and DVS capabilities. But the past studies only evaluated qualitative merit of FRT and DVS, or evaluated quantitative merit on fictional system models. Since the authors intend to evaluate FRT and DVS capabilities in existing power system of Japan, some method for the evaluation must be invented. For the evaluation, values of FRT and DVS capabilities are evaluated by reduction amount of stabilizing equipment (i.e. SVC in the paper). The evaluation based on strict optimal SVC disposition is quite difficult, because existing power system must be adequately modeled, because number of SVCs is large and because every power flow conditions must be considered. However, semi‐optimal SVC disposition can be calculated as shown in the paper. As the result, value of FRT is quite larger than value of DVS. And then, our grid code is proved as pragmatically adequate, except some flaw in claimed FRT design that is introduced in the paper. [ABSTRACT FROM AUTHOR]

Abstract The transition to a 100% renewable energy system based on variable renewable energy raises technical but also institutional questions. The smart energy system concept integrates variable renewable energy by addressing the technical challenges through the integration of different energy sectors, but integration of variable renewable energy also entails a change in the cost structures, especially related to electricity. The effect of this change in cost structures on market prices is investigated. This is done through simulation of a 100% renewable energy system that utilises a large degree of cross-sector integration but maintaining the current electricity market structure. The paper uses a 100% renewable energy system scenario for a 2050 Danish energy system. This is reflected in the use of wind energy as the primary renewable energy source. It is concluded that the current electricity market structure is not able to financially sustain the amounts of wind power necessary for the transition to a 100% renewable energy system. Since earlier research shows that neither electricity production costs nor the total system costs is higher for the renewable path than the fossil-based alternatives, the conclusion in this paper points towards a need for reshaping the institutional structure of electricity trade. Highlights • Calculates electricity prices in a renewable energy system with current market design. • Calculates private profitability of wind power investments within such system. • The market design cannot financially sustain wind power in a renewable energy system. [ABSTRACT FROM AUTHOR]

Transitioning electricity generation sectors to renewable energy is a necessary element of climate change mitigation but a challenging one with years of technical and social lock-in creating considerable inertia and a pace of change insufficient to meet the task. Transition management has emerged as a promising approach to proactively manage and accelerate transitions in sectors like energy and water and has the potential to do so in manner that would help secure energy justice. However, the approach has been criticised for ignoring the political dynamics of transitions, risking procedural and recognition injustice for traditional energy production regions while increasing opposition to a transition. This paper uses a qualitative case study approach to understand how a transition to renewable energy generation could be achieved in a way that secures energy justice for traditional energy production regions like those of Gladstone in the Australian state of Queensland. The paper augments the transition management approach with the “just transitions” concept, which has emerged from labour movements as a means to mitigate negative impacts on workers and communities in traditional energy production regions, to create a “Just Transition Management” framework that is applied as a diagnostic tool to the case study. While results suggest a transition is imminent within Queensland, a lack of: consistent, supportive federal policy; long-term visions, and a clear process leaves it at risk of being captured by the powerful incumbent resources sector utilising an “environment vs. jobs” narrative. Yet, the results also suggest that adopting a just transition management approach has the potential to successfully resist the influence of the resources sector, by providing cheap, secure renewable energy and supporting affected workers into roles in the renewable energy sector using a reflexive, representative network governance approach. Data analysis reveals how the application of just transition principles has already engaged communities and unions that were previously sceptical of renewable energy. Overall, this study suggests that the just transition management framework assists in identifying the political barriers to transitions and energy justice more broadly, while also providing a management approach which creates powerful niche actor-networks to counter the narratives and influence of the incumbent resource sector. Thus it could support successful transitions that achieve the distributional, recognition and procedural justice needed for energy justice globally. [ABSTRACT FROM AUTHOR]

Electrical energy becomes necessary for human being. Generation of electrical energy mostly depends on fossils fuel, they are limited in nature and also responsible for environmental pollution. Renewable energy resources provides a better alternative for future,In comparison to conventional energy resources economical aspect is a major issue of renewable energy sources with the feasibility and efficiency. These limitations are tried to overcome by deployment hybrid renewable energy resources. There are certain criteria to analyze and implement the sized, optimized and cost efficient system. This paper focus on hybrid energy systems based on solar photovoltaic (PV) and wind resources. This paper shed lights on various parameters of economic feasibility, sizing strategies with logical advancements to enhance their utilization, future prospects, and their arrangement. Strategies to develop an effective storage system is also presented here.A brief review on developments in optimization techniques, reliability index and cost analyzing techniques for hybrid renewable energy systems are also presented. [ABSTRACT FROM AUTHOR]

This paper introduces a scheme for hedging and managing production costs of a risky generation portfolio, initially assumed to be dispatchable, to which intermittent electricity generation from non-dispatchable renewable sources like wind is further added. The proposed hedging mechanism is based on fixing the total production level in advance, then compensating any unpredictable non-dispatchable production with a matching reduction of the dispatchable fossil fuel production. This means making no recourse to short term techniques like financial hedging or storage, in a way fully internal to the portfolio itself. Optimization is obtained in the frame of the stochastic LCOE theory, in which fuel costs and CO 2 prices are included as uncertainty sources besides intermittency, and in which long term production cost risk, proxied either by LCOE standard deviation and LCOE CVaR Deviation, is minimized. Closed form solutions for optimal hedging strategies under both risk measures are provided. Main economic consequences are discussed. For example, this scheme can be seen as a method for optimally including intermittent renewable sources in an otherwise dispatchable generation portfolio under a long term capacity expansion perspective. Moreover, within this hedging scheme, (1) production cost risk is reduced and optimized as a consequence of the substitution of the dispatchable fossil fuel generation with non-dispatchable CO 2 free generation, and (2) generation costs can be reduced if the intermittent generation can be partially predicted. [ABSTRACT FROM AUTHOR]

India has set aggressive targets to install more than 400 GW of wind and solar electricity generation by 2030, with more than two-thirds of that capacity coming from solar. This paper examines the electricity and carbon mitigation costs to reliably operate India's grid in 2030 for a variety of wind and solar targets (200 GW to 600 GW) and the most promising options for reducing these costs. We find that systems where solar photovoltaic comprises only 25 to 50% of the total renewable target have the lowest carbon mitigation costs in most scenarios. This result invites a reexamination of India's proposed solar-majority targets. We also find that, compared to other regions and contrary to prevailing assumptions, meeting high renewable targets will avoid building very few new fossil fuel (coal and natural gas) power plants because of India's specific weather patterns and need to meet peak electricity demand. However, building 600 GW of renewable capacity, with the majority being wind plants, reduces how often fossil fuel power plants run, and this amount of capacity can hold India's 2030 emissions below 2018 levels for less than the social cost of carbon. With likely wind and solar cost declines and increases in coal energy costs, balanced or wind-majority high renewable energy systems (600 GW or - 45% share by energy) could result in electricity costs similar to a fossil fuel-dominated system. As an alternative strategy for meeting peak electricity demand, battery storage can avert the need for new fossil fuel capacity but is cost effective only at low capital costs (USD 150 per kWh). [ABSTRACT FROM AUTHOR]

Summary: Growth in global energy demand, with major fossil fuel consumption, has induced detrimental environmental and social impacts. Therefore, in recent years, technologies focused on renewable energy utilization, including biomass energy, have evolved to meet the energy requirements. Bioenergy‐based power generation systems are among the best‐unutilized configurations to diminish reliance on fossil fuels. However, it is difficult to select a biomass‐based configuration for economical, sustainable, and reliable power generation. Understanding different possible configurations of biomass‐based energy systems, design parameters, system research gaps, and integration challenges in biomass‐based energy systems are important for further development and propagation. This paper presents a critical review of biomass‐based different hybrid configurations with solar, wind, fuel cell, micro‐hydro, geothermal, and diesel generator, and various designing parameters, challenges, and gaps with future scope. To restrict the scope of the review, only the gasification and anaerobic digestion related biomass electricity generation systems are considered. The analysis indicates that the biomass‐based hybrid energy systems can provide an eco‐friendly and cost‐effective solution, especially for off‐grid rural electrification. The solar radiation, load demand, fuel price, capacity shortage, interest rate, wind speed, biomass quantity, and electricity rate are among the most critical designing parameters in biomass‐based energy systems. The study provides valuable information to designers, researchers, and policy makers on the latest design constraints and relevant policies relating to biomass‐based hybrid energy systems. [ABSTRACT FROM AUTHOR]

Solar energy contributes a major share in sustainable energy-based electricity generation. The solar power transfer system (SPTS) has emerged to integrate solar energy into the distribution network. Moreover, the adverse effects and exhaustible nature of fossil fuels have made the control and design of the SPTS significant. This paper presents a novel grid integration control, named frequency adaptive generalized integral (FAGI) algorithm for a three-phase four-wire SPTS to compensate the reactive power, harmonics and DC offset demands of the sinks connected at the common point, and also eliminates the grid neutral current along with maximum PV array power injection to the grid. The narrow bandwidth bandpass filter property of the FAGI algorithm with adaptive corner frequency improves the fundamental component quality without compromising the response time at adverse operating conditions. The two-stage SPTS uses a DC–DC boost converter for peak power extraction. An enhanced incremental conductance (EIC) algorithm is utilized for its control, which gives simple and dynamic performance over other conventional maximum power point tracking techniques. The system control is developed to meet the load requirements, even at zero irradiance by importing the active power from the grid. Therefore, the major objectives of this work are extracting maximum power, meeting the load demands, and maintaining the grid power quality at any operating conditions. Comparison of FAGI with other common controls, is carried out and the results are produced. The system performances are analyzed at PV-side, load-side, and grid-side disturbances in the MATLAB/Simulink model, and examined the grid power quality compliance with the IEEE-519 standard. An experimental prototype of the system is developed in the laboratory and tested rigorously for multiple dynamic scenarios for validating the reported claims. • Novel frequency adaptive generalized integral control for grid integration. • Compensates load reactive power, unbalanced currents, harmonics and neutral current. • FAGI enhances dynamic response at fluctuating loads and rejects input DC offset. • System has bi-directional power transfer capability at the grid coupling point. • Performance confirmed from experimental results on developed prototype. [ABSTRACT FROM AUTHOR]

This paper is an exploratory study on the Bangladesh and Thailand rural electricity transition. This study compares the Bangladesh microgrid policies with that of Thailand microgrid policies. The comparative study in several areas considers electricity security, electricity access, environmental sustainability, economic development and growth of the countries. Public data related to microgrid policies in Bangladesh and Thailand had been collected, analyzed and discussed. The comparative case brings out the significant differences while also exploring the range of possible synergies across different dimensions and sectors. Concisely, the transition of rural electricity, driven by microgrid policy in both countries can be achieved by adopting new electricity market structure and regulation. The private sector would play a key role in electricity generation. [ABSTRACT FROM AUTHOR]

Only 40% of Zimbabwe's population has access to electricity. The greater proportion of the power is generated from thermal stations, with some from hydro and solar energy sources. However, there is little investment in the use of wind for electricity generation except for small installations in the Eastern Highlands, as Zimbabwe generally has wind speeds which are too low to be utilised for electricity generation. This paper presents the use of vertical wind profile extrapolation methods to determine the potential of generating electricity from wind at different hub heights in Zimbabwe, using the Hellman and exponential laws to estimate wind speeds. The estimated wind speeds are used to determine the potential of generating electricity from wind. Mangwe district in Matabeleland South province of Zimbabwe was used as a test site. Online weather datasets were used to estimate the wind speeds. The investigation shows that a 2.5kW wind turbine installation in Mangwe can generate more than 3MWh of energy per annum at hub heights above 40m, which is enough to supply power to a typical Zimbabwean rural village. This result will encourage investment in the use of wind to generate electricity in Zimbabwe. [ABSTRACT FROM AUTHOR]

The energy situation of the African island states which include Cape Verde, São Tomé and Príncipe, Comoros, Guinea-Bissau, Madagascar, Mauritius and Seychelles are overwhelmingly dependent on fossil fuels with paradoxically high potential of renewable energy which are sparsely developed. This paper lay emphasis on the present electricity situation in these countries and highlights the potential of renewable energy resources on their territories. Among Africa islands, demographic and economic features are dissimilar and their power sector is complex by unique challenges. It is seen that there is a critical lack of electricity in Guinea-Bissau and Madagascar, which are 21% and 13% respectively, due to political instability and high spending on diesel. Moreover, the electricity consumption per capita is alarming in Guinea-Bissau, Comoros and Madagascar where it is below the average consumption for low income countries. Sustainable energy supply can be achieved by renewable energy sources, however, not all renewable resources are technically and economically feasible for development in these countries, for example wind in Comoros and hydro in Mauritius have little potential – which this paper elaborated further. Based on these analysis, a roadmap was developed, on to how to address some of the energy issues in these countries and accelerate the uptake of renewable energy. Through energy governance reform, political decision makers can drive change within their government, especially when a reform entails opening market opportunities and stimulating private participation and exerting pressure on existing government agencies to work efficiently. [ABSTRACT FROM AUTHOR]

South Africa is promoting renewable energy such as wind power to address the objectives of both energy security and sustainable development. This paper reviews the nature of policies, institutional set-up and programmes in place to upscale especially onshore wind energy uptake, as reflected in publicly available documents. It shows that South Africa has put in place critical policies, institutions and programmes for wind energy uptake. Among key policy documents and policies are the White Paper on Energy (1998), Renewable Energy White Paper (2003), Energy Act of 2008, and National Climate Change Response White Paper (2011). There is also the Integrated Energy Plan, the Integrated Resource Plan (2010, revised 2013) and Environmental Impact Assessment Guidelines for Renewable Energy Projects of 2015. Key institutions noted include the South African National Energy Development Institute, the South African Renewable Energy Council and the South African Wind Energy Association. The main programme is the Renewable Energy Independent Power Producers Procurement Programme, which resulted in more than 30 installed wind energy projects. Overall, wind energy promises to be among the viable and acceptable technologies in the renewable energy sector in South Africa. [ABSTRACT FROM AUTHOR]

Power production by conversion of salt gradient energy (osmotic power production) has the potential for global commercialization. Research on the net-power output and osmotic power plant configurations could result in viable methods for improvement of plant efficiency. In this paper, a novel equivalent electric-circuit model of the pressure-retarded osmosis (PRO) process is described and is used to develop a power-hardware-in-the-loop (PHIL) emulator to represent the osmotic power plant. The model considers many dynamics involved with PRO including reverse salt leakage, concentration polarization, and the salt storage capacity of water. The proposed model facilitates real-time dynamic simulation and analysis of the PRO power plant, and its interaction with the rest of the PRO power system, namely the impulse turbine and the synchronous generator supplying power to off-grid or isolated loads. The response of the multidomain system including hydraulic, mechanical, and electrical components of the system is observed, given changes in the input parameters such as source flow rate. The proposed PHIL emulator provides insight into the operational dynamics and behavior of the PRO system. The proposed real-time emulator serves as a powerful tool that can advance research and development of PRO power generation systems. Simulation and experimental results are presented in this paper to validate the PRO plant model and the operation of the proposed real-time PHIL PRO emulator. [ABSTRACT FROM PUBLISHER]