Country's Electricity Research Articles

Electricity security in Uganda: Measurement and policy priorities

Reliable, accessible, affordable, and sustainable electricity systems are fundamental to modern and progressive economies. For developing societies, particularly those with fragile power generation capabilities and electricity networks, the electricity security metrics are incomparable and remain untested. A Multi-Criteria Decision-Making (MCDM) method that follows an entropy-based weighting system is employed to quantitatively evaluate and construct an Electricity Security Index (ESI) for Uganda. Results reveal that Uganda is “moderately” electricity secure. Out of the maximum possible score of 100, a year-on-year analysis indicates that the ESI score was highest in 2007 (56) and the lowest was registered in 2015 (39). Based on the VIKOR technique, it is observed that electricity reliability contributes the most to the ESI, while electricity access contributes the least. Although expansion of electricity generation capacity is necessary, energy policies should, in equal measure, prioritize adequate investments in robust and modern transmission and distribution infrastructure. A riveting policy implication is that governance quality enhances a country's electricity system by reinforcing the other dimensions of electricity security.

Sustainability and Innovation in Green Energy: Biomass As A Renewable Energy Alternative

Objective: The objective of this research was to analyze the role of biomass as a renewable energy alternative. Methodology: To do so, an integrative literature review was carried out by surveying articles in the SciELO, Web Of Science and Google Academic databases. During the search, specific keywords and AND and OR search descriptors were used. As an inclusion criterion, only Brazilian scientific articles were selected, in Portuguese, available in full, free of charge and published between the years 2020 and 2023. Results and analysis of the data: As a result, it was found that the energy use of solid urban waste (MSW) in Brazil offers environmental, health and social benefits, in spite of not having sufficient potential to sustain the expansion of the country's electricity supply in the long term. Relevant public policies, such as the National Policy on Solid Waste (PNRS) and the Alternative Energy Incentive Program (PROINFA), are crucial, but the lack of clarity in the joint implementation makes it difficult to replicate initiatives. The management of MSW is the responsibility of municipalities, while energy planning is the responsibility of the Union, and the absence of clear guidelines and specific funding contributes to limited results. Projects such as those of ASJA and FURNAS show progress, but the greater dissemination of these projects requires integrated public policies and a normative framework that aligns the efforts of various actors to maximize the efficiency and benefits of using MSW in power generation. Conclusion: In conclusion, the energy use of solid urban waste (MSW) in Brazil offers environmental and social benefits, but is not sufficient to expand the supply of electricity in the long term. Existing public policies are important, but their effectiveness is limited by the lack of clarity in implementation and by the division of responsibilities between municipalities and the Union. Projects such as those of ASJA and FURNAS show progress, but greater dissemination and effectiveness require integrated public policies and a normative framework that aligns the efforts of the various players to optimize the use of MSW in power generation.

Electricity trade at exchanges of the world: Contextual analysis of Indian electricity exchanges

This study probes the relationship between price and traded volume in electricity exchanges worldwide. Deploying the generalised method of moments estimation on panel data from the day-ahead market of exchanges in 20 countries for the period 2015–2020, this study finds that an increase in the share of exchange-traded electricity in a country's total electricity consumption significantly reduces price. A critical analysis of the Indian electricity exchanges in this study reveals that even after 13 years of operations, consumers do not derive surplus as is expected from commodity exchanges.

Review of best practices for global cogeneration policy: Benchmarking and recommendations for Malaysia

Despite the Malaysian government's efforts to promote cogeneration technology, it constitutes a mere 4.2 % of the country's total electricity generation. To address this issue, this review article aims to identify and benchmark global best practices for bolstering cogeneration implementation in Malaysia. While previous studies in this domain have centered on examining government policies within the specific regions, this paper underscores the imperative for an updated and comprehensive literature review to systematically collect and categorise best practices from around the world. This work examines the adoption of cogeneration energy systems within nations characterised by a substantial presence in their energy composition, simultaneously exploring the roles of regulatory frameworks in promoting their uptake. The scope of the literature review includes statistical data, reports, and other relevant scholarly works on cogeneration policies. Based on the findings, the review paper concludes that well-crafted policies are instrumental in encouraging rapid technology advocacy. The legislative landscape pertaining to cogeneration implementation in Malaysia is scrutinised, followed by a comparative analysis against global best practices to identify opportunities for improvement. Three crucial elements emerge as paramount to expediting the adoption: (i) administrative recognition, (ii) financial initiatives, and (iii) regulatory improvements. Several recommendations for the Malaysian cogeneration roadmap are presented. Overall, this paper offers insights into the chronological evolution of cogeneration policy development and provides actionable guidelines for developing effective policies in Malaysia and other South-East Asian countries.

ABOUT SOME PROBLEMS OF THE ELECTRIC ENERGY SECTOR OF GEORGIA

In the article - "About some problems of the electric energy sector of Georgia" - the issue of the country's electricity production potential and how it is used is discussed. The article mentions that out of all the energy resources, Georgia has the most electrical energy resources. These are hydropower (water resources), wind and solar resources. A retrospective analysis of both total and individual production and consumption of electricity in the period 1990-2023 concluded that a 47.5% increase in individual consumption was caused by the catastrophic population decrease in Georgia during the same period. The article also mentions that the average consumption of electricity in Georgia is half of the corresponding indicator of Germany, the USA - Mesa-Med, and Norway - one-sixth. The electricity balance of Georgia is negative. A significant part of electricity is imported from Russia and Azerbaijan. Among the problems faced by the electrical energy system, the article discusses the possibility of causing danger by depending on external sources of electricity, giving preference to the construction of large hydroelectric power plants (the construction of which destroys wild nature) and less attention to the study of the issue of regional production and consumption of electricity. The article provides conceptual solutions to each of these problems. Keywords: electric energy; hydropower; wind and solar energy; large and small hydropower plants; Electrical energy balance.

Modeling of Brazilian Wind Power Generation Capacity: A Multivariate Analysis with Neural Networks

Over the last twenty years, Brazil has experienced significant changes in its electric energy matrix, notably with the expansion of wind and solar energy sources. In the early 2000s, hydroelectric plants with a capacity of 70 gigawatts (GW) were responsible for generating 90% of the country's electricity, while solar and wind sources contributed merely 1%. Today, the scenario has evolved, with wind and solar energy comprising approximately 25% of the national generation, indicating a departure from the previous hydro-dominated matrix. This research aims to apply specific types of neural networks to multivariate data to forecast Brazil's wind power generation capacity, providing insight into the potential for future energy strategies. This research contributes as a as a decision support tool contemplating relevant information for analysts, researchers, and participants in the renewable energy market. The monetary volume destined to import key components of the wind, considering specific time lags, was utilized to forecast the Installed capacity of the wind farms in Brazil. The Toda-Yamamoto Causality Tests revealed unidirectional Granger causality in the sense of the Import variable for the Brazilian Installed Capacity variable for wind energy production. Another result obtained was the finding that the variable that matters most in the multivariate configuration of the Neural Network is the variation in Installed Capacity in megawatts, followed by the import volume of wind energy components, which exhibited critical lags at 3 and 6 months.

Selection of renewable energy development path for sustainable development using a fuzzy MCDM based on cumulative prospect theory: the case of Malaysia

Malaysia's excessive energy consumption has led to the depletion of traditional energy reserves such as oil and natural gas. Although Malaysia has implemented multiple policies to achieve sustainable national energy development, the current results are unsatisfactory. As of 2022, only 2% of the country's electricity supply comes from renewable energy, which accounts for less than 30% of the energy structure. Malaysia must ensure energy security and diversified energy supply while ensuring sustainable energy development. This article uses the fuzzy multi-criteria decision-making(MCDM) method based on cumulative prospect theory to help decision-makers choose the most suitable renewable energy for sustainable development in Malaysia from four dimensions of technology, economy, society, and environment. The results show that solar power is the most suitable renewable energy for sustainable development, followed by biomass, wind, and hydropower, but the optimal alternative is sensitive to the prospect parameters. Finally, it was analyzed that efficiency, payback period, employment creation, and carbon dioxide (CO2) emissions are the most critical factors affecting the development of renewable energy in Malaysia under the four dimensions. Reasonable suggestions are proposed from policy review, green finance, public awareness, engineering education, and future energy. This research provides insightful information that can help Malaysian decision-makers scientifically formulate Sustainable development paths for renewable energy, analyze the problems encountered in the current stage of renewable energy development, and provide recommendations for Malaysia's future renewable energy transition and sustainable development.

Overcooling in UAE homes: health issues and implications for learning efficiency

From 1990 to 2016, , air conditioning usage in the UAE increased from 25 to 125 terawatt hours, making up 70% of the country's electricity consumption. Overcooling to 18°C in homes is common, leading to health issues and reduced learning efficiency during the Covid-19 pandemic. This study uses Electroencephalograms (EEG) to examine indoor thermal environments' impact on learning efficiency. An artificial climate chamber set at 24°C or 20.5°C monitored 64 healthy males aged 21–29 during a 70-minute EEG session. Participants took a Visual Continuous Performance test and had their academic performance evaluated. Seven brain areas were analyzed for attention and power frequency. Results showed lower temperatures (20.5°C) increased EEG frequency, indicating better attention than 24°C. Statistical analysis revealed that concentration was achieved faster at lower temperatures. This study highlights the importance of optimizing indoor temperatures for improved learning efficiency and well-being.

MATHEMATICAL APPROACH TO FORECAST THE ELECTRICITY CRISES IN PAKISTAN AND ITS MITIGATION

Electricity is widely recognized as the backbone of economic success and progress, playing a vital role in driving socioeconomic development. This comprehensive study conducted an in-depth analysis of Pakistan's electricity consumption and aimed to develop a suitable model for forecasting the country's future electricity consumption (E.C.). Due to the strong positive correlation between E.C. of different sectors with Population and Gross Domestic Product (GDP), multiple linear regressions were employed for the analysis of electricity consumption. To predict population and GDP different mathematical model such as linear, Exponential, Polynomial and logarithmic models were applied on population and GDP data. In order to get the best fitted model a number of goodness-of-fit tests Coefficient of Determination, Sum of Square Errors, Sums of Square Regression, Mean Square Error, Root Mean Square Error, And F- Statistics (Adj-R2, SSE, SSR, MSE, RMSE and F Statistics) applied and got the polynomial model to be the most effective one for population and GDP. According to the goodness-of-fit test-based models, Pakistan's population is on track for steady growth, with projections reaching approximately 244428310 in 2025 and further increasing to 319825879 in 2040. This indicates significant demographic changes on the horizon. At the same time, Pakistan's GDP per capita is expected to rise, starting at 1958.3 $ in 2025 and potentially reaching 3,210.9 $ in 2040, signifying a positive trajectory towards economic development and prosperity in the country. Based on the selected models suggested by goodness of fit tests, the study throws light on the expected future electricity consumption in Pakistan. According to these projections, the expected electricity consumption of Pakistan may reach 121,121.1 GWh in 2025, 138,861.8 GWh in 2030, 157,716.8 GWh in 2035, and 177,686.3 GWh in 2040 respectively.

Assessment of the energy saving potential by regions of Ukraine (methodology and predictive assessment)

The purpose of the research is the develop methods and tools for long-term forecasting of electricity consumption based on the improved comprehensive method of demand for energy resources, taking into account the peculiarities of electricity use in the regions of Ukraine and their impact on the country's electricity consumption. The scientific novelty of the obtained results is the consideration of the technological potential of regional electricity conservation by means of electricity conservation measures typical for the regions. Thus, a complex method, a mathematical model, and a methodology for determining the forecast demand for electricity for three hierarchical levels of the economy were further developed. In these levels, the following groups of indicators are distinguished for forecasting electricity consumption: country, region, local level, or types of economic activity in the region. The formed three-level model (level I, level II, level III) takes into account both the general potential of electricity conservation (from structural and technological changes) in the country as a whole, and peculiarities at the regional level (region, city, village, settlement, territorial community) in certain (selected) types of economic activity in production (service provision). In the course of the work, material was collected on energy-saving measures in energy-intensive industries and forecasts of the development of certain types of production and service provision. These estimates determined the technological potential of energy saving in the regions. The 12 regions with the largest electricity consumption are highlighted, and the other regions are combined. In the region, the potential of electricity saving was distributed according to the structure of electricity consumption according to the types of economic activity inherent in this region. The technological potential of electricity conservation in the country will reach 10.35 billion kWh. Keywords: region, electricity-saving, electricity-saving potential, forecasting, energy efficiency, electricity.

Implications of a smart grid-integrated renewable distributed generation capacity expansion strategy: The case of Iraq

The rapid growth of electricity demand in Iraq has consistently outstripped the country's electricity infrastructure, leading to frequent blackouts, especially during peak summer demand. With a heavy reliance on oil 93 % and gas 7 % for electricity generation, the nation is exposed to economic fluctuations associated with global oil prices and environmental impacts from burning fossil fuels. This study explores the implications of integrating smart grids and expanding renewable distributed generation capacity in the country's energy system. Drawing upon the projection of the energy demand by 2035 across four scenarios (Business as Usual, Sustainable Development, High Growth, and Low Carbon), the study underscores solar energy, backed by abundant solar and wind energy, as a key player in the country's renewable transition. However, challenges persist, including the need for technical expertise in renewable energy technologies, financing hurdles, and concerns about policy stability. With the country's policies targeting 25 % renewable electricity by 2030 and the establishment of significant renewable projects, there tangible momentum. The results have drawn out a roadmap for an estimated addition of up to 10 GW of renewable energy capacity by 2030 and 14 GW by 2035. In addition, strategies for distributed generation capacity expansion were highlighted, underscoring the crucial role of solar and wind energy and other renewables in the country's sustainable energy future.

Sub-segment-based approach for assessing growth and energy transition trajectories of Indian two-wheelers

The transition trajectory of India's two-wheeler (2W) vehicle segment is studied using a sequential modelling framework for projecting sub-segment-wise 2W fleet, energy demand, and associated CO2 emissions. Road density per capita was identified as a more significant explanatory variable than GDP per capita in estimating 2W fleet size in India. The elasticity method was used to evaluate the 2W vehicle saturation level based on five different indirect parameters. It was found that population density had the highest impact (48%), followed by urbanization (31%) and adult population share (16%). The impact of the total cost of ownership was negligible. The mean 2W vehicle saturation level was calculated to be 314 while the ownership was found to be 207, 265, and 297 vehicles per 1000 people by 2030, 2040, and 2050, respectively. Scooters were found to be leading the e-transition of 2Ws but a successful e-transition of India's 2Ws would not be achieved without transitioning the motorcycles. Two motorcycle clusters were identified that offer economies of scale towards e-transitioning. Closer scrutiny of six plausible e-transition scenarios showed that a 50% penetration of E−2Ws is unattainable before 2045. The biggest obstacle in achieving high E−2W penetration in India would be the limited capacity to supply indigenously produced vehicles. A high import dependence on battery technology and critical raw materials would limit the energy transition and diversification of the Indian road transport sector. India should follow the mass adoption-driven diffusion pathway in the short-to-medium term and the affordability-constraint diffusion pathway in the long term to achieve the best results in terms of reduction in energy demand and associated emissions for the 2W segment. The gains from the e-transition of the road transport sector would not be substantial without a simultaneous transition in the country's electricity generation mix away from coal-based thermal power.

Assessing the potential of solar power generation in Turkey: A PESTLE analysis and comparative study of promising regions using PVsyst software

Renewable energy sources have a tremendous amount of potential in Turkey. In the previous year, 43.2% of the country's electricity was generated from renewable energy sources. Solar photovoltaic (PV) energy accounted for 4.7% of the electricity generation and the installed capacity was 9.425 GW with 9353 solar power plants of various types. This paper provides an overview of the current state of solar PV potential in Turkey, evaluates its capacity to meet the country’s energy demand, and discusses its future prospects. The PESTLE analysis is performed based on political (P), economic (E), social (S), technological (T), legal (L), and environmental (E) factors to study the sustainable development of solar energy potential in Turkey. Furthermore, a comparative analysis of the solar energy potential between the Konya and Diyarbakır regions which are recognized as promising areas for harnessing the country's abundant solar resources has been conducted using the PVsyst software. The electricity consumption in Turkey will be 380.2 TWh in 2025, 455.3 TWh in 2030, and 510.5 TWh in 2035, according to the Turkey National Energy Plan. Hence, it is essential to maximize the use of solar energy capacity in the production of electricity tomeet the increased energy demand. The main objective of this study is to help strategic and systematic evaluation of the solar energy resource potential affecting large and small-scale solar power projects in Turkey.

Phasing out steam methane reformers with water electrolysis in producing renewable hydrogen and ammonia: A case study based on the Spanish energy markets

Deploying renewable hydrogen presents a significant challenge in accessing off-takers who are willing to make long-term investments. To address this challenge, current projects focus on large-scale deployment to replace the demand for non-renewable hydrogen, particularly in ammonia synthesis for fertiliser production plants. The traditional process, involving Steam Methane Reformers (SMR) connected to Haber-Bosch synthesis, could potentially transition towards decarbonisation by gradually integrating water electrolysis. However, the coexistence of these processes poses limitations in accommodating the integration of renewable hydrogen, thereby creating operational challenges for industrial hubs. To tackle this issue, this paper proposes an optimal dispatch model for producing green hydrogen and ammonia while considering the coexistence of different processes. Furthermore, the objective is to analyse external factors that could determine the appropriate regulatory and pricing framework to facilitate the phase-out of SMR in favour of renewable hydrogen production. The paper presents a case study based in Spain, utilising data from 2018, 2022 and 2030 perspectives on the country's renewable resources, gas and electricity wholesale markets, pricing ranges, and regulatory constraints to validate the model. The findings indicate that carbon emissions taxation and the availability and pricing of Power Purchase Agreements (PPAs) will play crucial roles in this transition - the carbon emission price required for total phasing out SMR with water electrolysis would be around 550 EUR/ton CO2.

Climate and health benefits of a transition from gas to electric cooking

Household electrification is thought to be an important part of a carbon-neutral future and could also have additional benefits to adopting households such as improved air quality. However, the effectiveness of specific electrification policies in reducing total emissions and boosting household livelihoods remains a crucial open question in both developed and developing countries. We investigated a transition of more than 750,000 households from gas to electric cookstoves-one of the most popular residential electrification strategies-in Ecuador following a program that promoted induction stoves and assessed its impacts on electricity consumption, greenhouse gas emissions, and health. We estimate that the program resulted in a 5% increase in total residential electricity consumption between 2015 and 2021. By offsetting a commensurate amount of cooking gas combustion, we find that the program likely reduced national greenhouse gas emissions, thanks in part to the country's electricity grid being 80% hydropower in later parts of the time period. Increased induction stove uptake was also associated with declines in all-cause and respiratory-related hospitalizations nationwide. These findings suggest that, when the electricity grid is largely powered by renewables, gas-to-induction cooking transitions represent a promising way of amplifying the health and climate cobenefits of net-carbon-zero policies.

Investigation into the Development of Waste to Energy as an Alternative Energy Source

Pakistan, a developing nation, is facing a critical crisis regarding its fossil fuel resources and the production of electrical energy. The country's electricity demand has reached approximately 29,000 MW, while the generation capacity is only 22,000 MW. This significant gap between generation and demand has led to load-shedding. To address this issue, we are considering the development of waste-to-energy plants, which are waste management facilities that utilize combustion to generate electricity. Instead of relying on traditional fossil fuels like coal, oil, or natural gas, waste-to-energy plants use trash as a fuel source. By burning this fuel, heat is produced, which heats water to generate steam that drives a turbine, ultimately creating electricity. While waste-to-energy is often portrayed as a viable method for extracting energy from available resources, it does pose challenges to the circular economy. This approach generates toxic waste, contributes to air pollution, and exacerbates climate change. These plants emit chemicals such as mercury and dioxins, which pose risks to human and environmental health. To address these concerns, we aim to investigate the development of waste-to-energy as an alternative energy source while prioritizing creating a healthy environment. As part of this effort, we intend to implement a sensor network to detect the heat generated during incineration and monitor the emission of pollutants. Our overarching goal is to generate electricity while recycling waste materials as much as possible, thus promoting a sustainable and eco-friendly approach.

Investigation into the Development of Waste to Energy as an Alternative Energy Source

Pakistan, a developing nation, is facing a critical crisis regarding its fossil fuel resources and the production of electrical energy. The country's electricity demand has reached approximately 29,000 MW, while the generation capacity is only 22,000 MW. This significant gap between generation and demand has led to load-shedding. To address this issue, we are considering the development of waste-to-energy plants, which are waste management facilities that utilize combustion to generate electricity. Instead of relying on traditional fossil fuels like coal, oil, or natural gas, waste-to-energy plants use trash as a fuel source. By burning this fuel, heat is produced, which heats water to generate steam that drives a turbine, ultimately creating electricity. While waste-to-energy is often portrayed as a viable method for extracting energy from available resources, it does pose challenges to the circular economy. This approach generates toxic waste, contributes to air pollution, and exacerbates climate change. These plants emit chemicals such as mercury and dioxins, which pose risks to human and environmental health. To address these concerns, we aim to investigate the development of waste-to-energy as an alternative energy source while prioritizing creating a healthy environment. As part of this effort, we intend to implement a sensor network to detect the heat generated during incineration and monitor the emission of pollutants. Our overarching goal is to generate electricity while recycling waste materials as much as possible, thus promoting a sustainable and eco-friendly approach.

Solar-Powered Solutions for the Water and Energy Shortage Problem: The Case Study of Nahr El Bared, Lebanon

Solar power is an effective way to reduce the dependency on conventional fuels and mitigate the water and energy shortage issue. The main aim of the current paper is to assess and compare the techno-economic feasibility of rooftop grid-connected photovoltaic energy systems for generating electricity and generating drinkable water in Nahr El Bared, Lebanon. To this aim, the present paper first reviews previous scientific studies associated with the water resources and energy situation to summarize the current status in Lebanon. According to this review, Lebanon's water resources are highly polluted, domestic and industrial sewage is largely untreated, and intolerable agricultural practices further exacerbate the situation. Furthermore, population and economic growth and the continuous utilization of old power plants have led to an increase in the number of hours of power outages in the country. Accordingly, the proposed project aims to evaluate the viability of using solar energy as an alternative solution to the shortage of water and energy in the country. Secondly, the techno-economic performance of the proposed system in the selected region was evaluated based on the variations in financial parameters using RETScreen Experts software. The results demonstrate that 11770–13451kWh/yr could be generated from the solar system, which can help reduce the energy shortage and generate drinkable water. Furthermore, the investment was found to be economically viable and attractive for investors. This paper concludes that solar energy can be able to solve the energy shortage of electricity, reduce the country's electricity costs, and produce freshwater for drinking and domestic use in the country.

Microwave-aided pyrolysis and fragmentation of tar-rich coal and rocks for in situ coal conversion and clean utilization

British Petroleum predicts that coal will account for the largest share in energy resources for power generation until 2040. The U.S. Energy Information Administration forecasts that coal will remain a key component of the country's national electricity portfolio at least until 2040. However, due to serious issues including high carbon emissions, environmental pollution, surface subsidence, resource wastage, and mining accidents associated with traditional coal mining and utilization patterns, international communities have called for the abandonment of coal use and adoption of renewable resources. To overcome the disadvantages, we proposed a novel approach for achieving in situ conversion and power generation using subsurface coal. An earthworm-shaped intelligent unmanned mining machine (IUMM) was designed to use high-power microwave energy to pulverize and pyrolyze coal into particles that can be used for power generation via chemical conversion. In this study, we used IUMM-based technology for in situ conversion and utilization of tar-rich coal and recovery of oil and gas from the coal. We quantified the pyrolysis efficiency of the tar-rich coal and the surrounding sandstone as well as the gas–liquid overflow rate of the coal under various high-power microwave irradiation conditions. The critical microwave energy threshold for discriminating tar-rich coal from the surrounding sandstone was determined, which will help to realise automatic pyrolysis of tar-rich coal by IUMM and minimise the damage caused by high-energy microwave radiation to the surrounding rock. This work aids in the production of cleaner energy, while ensuring energy security.

Short-Term Load Forecasting using Artificial Neural Network in Indonesia

Short-term Load Forecast (STLF) is a load forecasting that is very important to study because it determines the operating pattern of the electrical system. Forecasting errors, both positive and negative, result in considerable losses because operating costs increase and ultimately lead to waste. STLF research in Indonesia, especially the State Electricity Company (PLN Sulselrabar), has yet to be widely used. Methods mainly used are manual and conventional methods because they are considered adequate. In addition, Indonesia's geographical conditions are extensive and diverse, and the electricity system is complex. As a result, the factors affecting each country's electricity demand are different, so unique forecasting methods are needed. Artificial Neural Network (ANN) is one of the Artificial Intelligent (AI) methods widely used for STLF because it can model complex and non-linear relationships from networks. This paper aims to build an STLF forecasting model that is suitable for Indonesia's geographical conditions using several ANN models tested. Based on several ANN forecasting models, the test results obtained the best model is Model-6 with ANN architecture (9-20-1). This model has one hidden layer, 20 neurons in the hidden layer, a sigmoid logistic activation function (binary sigmoid), and a linear function. Forecasting performance values obtained mean squared error (MSE), mean absolute error (MAE), and mean absolute percentage error (MAPE) of 430.48 MW2, 15.07 MW, and 2.81%, respectively.