Electricity Demand In Countries Research Articles

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.

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.

Forecasting Electricity Demand by Neural Networks and Definition of Inputs by Multi-Criteria Analysis

The planning of efficient policies based on forecasting electricity demand is essential to guarantee the continuity of energy supply for consumers. Some techniques for forecasting electricity demand have used specific procedures to define input variables, which can be particular to each case study. However, the definition of independent and casual variables is still an issue to be explored. There is a lack of models that could help the selection of independent variables, based on correlate criteria and level of importance integrated with artificial networks, which could directly impact the forecasting quality. This work presents a model that integrates a multi-criteria approach which provides the selection of relevant independent variables and artificial neural networks to forecast the electricity demand in countries. It provides to consider the particularities of each application. To demonstrate the applicability of the model a time series of electricity consumption from a southern region of Brazil was used. The dependent inputs used by the neural networks were selected using a traditional method called Wrapper. As a result of this application, with the multi-criteria ELECTRE I method was possible to recognize temperature and average evaporation as explanatory variables. When the variables selected by the multi-criteria approach were included in the predictive models, were observed more consistent results together with artificial neural networks, better than the traditional linear models. The Radial Basis Function Networks and Extreme Learning Machines stood out as potential techniques to be used integrated with a multi-criteria method to better perform the forecasting.

The effect of a nuclear baseload in a zero-carbon electricity system: An analysis for the UK

This paper explores the effect of having a nuclear baseload in a 100% carbon-free electricity system The study analyses numerous scenarios based on different penetrations of conventional nuclear, wind and solar PV power, different levels of overgeneration and different combinations between medium and long duration energy stores (hydrogen and compressed air, respectively) to determine the configuration that achieves the lowest total cost of electricity (TCoE).At their current cost, new baseload nuclear power plants are too expensive. Results indicate the TCoE is minimised when demand is supplied entirely by renewables with no contribution from conventional nuclear.However, small modular reactors may achieve costs of ∼£60/MWh (1.5× current wind cost) in the future. With such costs, supplying ∼80% of the country's electricity demand with nuclear power could minimise the TCoE. In this scenario, wind provides the remaining 20% plus a small percentage of overgeneration (∼2.5%). Hydrogen in underground caverns provides ∼30.5 TWh (81 days) of long-duration energy storage while CAES systems provide 2.8 TWh (∼8 days) of medium-duration storage. This configuration achieves costs of ∼65.8 £/MWh. Batteries (required for short duration imbalances) are not included in the figure. The TCoE achieved will be higher once short duration storage is accounted for.

Evaluating floating photovoltaics (FPVs) potential in providing clean energy and supporting agricultural growth in Vietnam

Vietnam's promising economic growth has led to energy shortage, growing coal imports, and increasing carbon emissions. The country's electricity demand annual growth rate has been 12% in recent years and is projected to be 8–9% by 2030. In Vietnam 40% of the land is dedicated to agriculture and thousands of inland water bodies are used for agriculture/aquaculture. Utilising even a small portion of them for Floating Photovoltaics (FPVs) would mitigate land-use conflicts and benefits agriculture and aquaculture. To demonstrate FPVs' potential, we selected a hydropower dam reservoir in the North and six irrigation reservoirs in the South. System Advisor Model (SAM) software was used to simulate the electricity generated if we cover 1%, 5%, and 10% of surfaces of these reservoirs. The results show a potential capacity close to 1 GWp and annual potential generation of 1.4 TWh if 1% of these surfaces were covered by FPVs. We also evaluated FPVs potential for four different types of water bodies in Vietnam: Lake, Lagoon, River and Without Classification. The results showed that the potential capacity, considering use of only of 1% of these water surfaces for FPVs is 3.7 GWp, and provides 5385 GWh generation, which highlights the significant contribution that FPVs can make to the renewable energy sector in this country. However, FPVs face some socio-technical barriers, including regulatory ambiguity about water rights, uncertainty about economic policies and limited information about their environmental impacts that could hamper the expansion of this technology, and need to be addressed through further research.

Combined solar power and storage as cost-competitive and grid-compatible supply for China’s future carbon-neutral electricity system

As the world's largest CO2 emitter, China's ability to decarbonize its energy system strongly affects the prospect of achieving the 1.5 °C limit in global, average surface-temperature rise. Understanding technically feasible, cost-competitive, and grid-compatible solar photovoltaic (PV) power potentials spatiotemporally is critical for China's future energy pathway. This study develops an integrated model to evaluate the spatiotemporal evolution of the technology-economic-grid PV potentials in China during 2020 to 2060 under the assumption of continued cost degression in line with the trends of the past decade. The model considers the spatialized technical constraints, up-to-date economic parameters, and dynamic hourly interactions with the power grid. In contrast to the PV production of 0.26 PWh in 2020, results suggest that China's technical potential will increase from 99.2 PWh in 2020 to 146.1 PWh in 2060 along with technical advances, and the national average power price could decrease from 4.9 to 0.4 US cents/kWh during the same period. About 78.6% (79.7 PWh) of China's technical potential will realize price parity to coal-fired power in 2021, with price parity achieved nationwide by 2023. The cost advantage of solar PV allows for coupling with storage to generate cost-competitive and grid-compatible electricity. The combined systems potentially could supply 7.2 PWh of grid-compatible electricity in 2060 to meet 43.2% of the country's electricity demand at a price below 2.5 US cents/kWh. The findings highlight a crucial energy transition point, not only for China but for other countries, at which combined solar power and storage systems become a cheaper alternative to coal-fired electricity and a more grid-compatible option.

Solar photovoltaic power generation in Iran: Development, policies, and barriers

Iran holds 10% of the global oil reserves and 15% of the natural gas. It is the second largest producer and exporter of oil and gas in Organization of the Petroleum Exporting Countries (OPEC). The consumption of energy in Iran is 4.4 times higher than the global average, placing it among the world's top ten greenhouse gas (GHG) emitters. According to the published statistics, renewable energy (RE) has faced a considerable growth in Iran due to the strategies of the sixth development plan, which aims at generating 5000 MW from REs by 2021, and an additional 2500 MW by 2030. The other reason is that under the “Paris Agreement” terms, Iran obliged to reduce its GHG emissions by at least 4% and at most 12% by 2030. Among RE resources, Iran has the remarkable potential for solar energy with the average annual rate of 4.5–5.5 kWh/m2. Under these conditions, solar photovoltaic (PV) power plants can play a crucial role in supplying a significant portion of the country's electricity demand. Although there is a high tendency of the government and policy makers for deployment of PV technology in Iran, there are still some impediments to turn potential into reality in this sector due to insufficient industry growth, financing problems, deficient of governing rules, and lack of a sustainable development roadmap. Solving these issues requires long-term and persisting policies to gain technical and industrial development to achieve mass progress in this sector during the next decades.

Forecasting Indonesia's electricity load through 2030 and peak demand reductions from appliance and lighting efficiency

Indonesia's electricity demand is growing rapidly, driven by robust economic growth combined with unprecedented urbanization and industrialization. Energy-efficiency improvements could reduce the country's electricity demand, thus providing monetary savings, greenhouse gas and other pollutant reductions, and improved energy security. Perhaps most importantly, using energy efficiency to lower peak electricity demand could reduce the risk of economically damaging power shortages while freeing up funds that would otherwise be used for power plant construction. We use a novel bottom-up modeling approach to analyze the potential of energy efficiency to reduce Indonesia's electricity demand: the LOAD curve Model (LOADM) combines total national electricity demand for each end use—as modeled by the Bottom-Up Energy Analysis System (BUENAS)—with hourly end-use demand profiles. We find that Indonesia's peak demand may triple between 2010 and 2030 in a business-as-usual case, to 77.3 GW, primarily driven by air conditioning and with important contributions from lighting and refrigerators. However, we also show that appliance and lighting efficiency improvements could hold the peak demand increase to a factor of two, which would avoid 26.5 GW of peak demand in 2030. These results suggest that well-understood programs, such as minimum efficiency performance standards, could save Indonesia tens of billions of dollars in capital costs over the next decade and a half.

The Status and Future Prospects of Hydropower for Sustainable Water and Energy Development in Tanzania

Tanzania is among the countries with the fastest growing economy in Africa and therefore the need for affordable, clean, and most importantly sustainable electrical energy to meet her ever growing demands is pressing. In recent years, the country’s electricity needs have been largely dominated by thermal generations despite the fact that Tanzania is gifted with huge hydropower resource potential approximated at 38,000 MW with only a very small portion exploited to date. However, the exploited potential is expected to grow by commissioning of identified large and medium-scale hydropower projects with a total installed capacity of 4,765 MW currently under various stages of implementation. Moreover, the geographical location of Tanzania has several benefits to support development of small hydropower projects essential for appropriate utilization of available water resources as a way of mitigating climate challenges effects. Over the last decade, the country electricity demand along with end-use of energy has witnessed significant increases as economic development spreads towards achieving Vision 2025 goals. Proposed hydropower developments are projected to have enormous benefits in the acceleration of economic growth while contributing to greenhouse gas emissions reduction. In this paper, hydropower, which is one of the domestic options for clean energy development path, its present and future potential status, and water resources are explored based on a comprehensive review of energy sector relevant documents and polices.

Study of Geothermal Energy Resources of Pakistan for Electric Power Generation

Pakistan is an energy deficient society and is facing a severe shortage of electric power. The country's electricity demand is rising 11% annually, while production is far less than the demand. The energy sector relies heavily on the imports of fossil fuels to satisfy their energy needs, while development of hydropower is very slow. Renewable energy development in the country is almost negligible and no major policy exists to exploit the renewable resources. This study discusses the scope of power production from geothermal energy. Geothermal energy is now considered one of the promising alternate energy resources. It is renewable, reliable, clean, and safe for the environment. Pakistan has enough economically and technically exploitable geothermal potential that can be harnessed and utilized. Geothermal reservoirs in the northern areas of Pakistan have been identified long ago, however, no serious effort has been made to use this potential for electric power production. This study not only encompasses the availability of such resources but also suggests the means to convert this energy into a useful form. In the end, the social, economical, and environmental impacts of this form of energy have also been discussed.

Indications for a changing electricity demand pattern: The temperature dependence of electricity demand in the Netherlands

This study assesses the electricity demand pattern in the relatively temperate climate of the Netherlands (latitude 52°30′N). Daily electricity demand and average temperature during the period from 1970 until 2007 are investigated for possible trends in the temperature dependence of electricity demand. We hypothesize that the increased use of cooling applications has shifted the temperature dependence of electricity demand upwards in summer months. Our results show significant increases in temperature dependence of electricity demand in May, June, September, October and during the summer holidays. During the period studied, temperature dependence in these months has shifted from negative to positive, meaning that a higher temperature now leads to an increased electricity demand in these months, rather than a decreased demand as observed historically. Although electricity demand in countries with moderate summer temperatures such as the Netherlands generally peaks in winter months and shows a minimum in summer months, this trend may signal the development of an additional peak in summer, especially given the expected climatic change. As power generating capacity may be negatively influenced by higher temperatures due to decreasing process cooling possibilities, an increasing electricity demand at higher temperatures may have important consequences for power generation capacity planning and maintenance scheduling.

An analysis of Grenada's power sector and energy resources: a role for renewable energy technologies?

Presently, Grenada's power sector is fully dependent on fossil fuel imports for meeting the country's electricity demand. Electric utilities in Small Island Developing States (SIDS), in general, face high cost of electricity generation due to diseconomies of scale in production, consumption and logistical aspects. Grenada's private power monopoly is no exception and the high cost of import dependent electricity generation places an increasing burden on economic development. In light of rapid technological and economic improvement of renewable energy technologies (RETs), the country's abundant sources of renewable energy should be harnessed. Benefits are envisaged to include lower electricity cost, better environmental performance and a safer and diversified supply of energy. However, barriers for shifting power production towards meaningful contributions from RETs exist, both in government and industry. This work analyses important economic interactions between the power sector and economic development, bringing to attention the importance of power sector reform. Further, present problems of integrating RETs into the grid, ranging from technical and regulatory issues to shareholder interest are investigated. A summary and analysis of past research into renewable sources of energy (RES) underscore the potential for power production from RETs in Grenada.