Location Of Power Plants Research Articles

Application of simultaneous evaluation of criteria and alternatives for prioritization of photovoltaic power plant location

AbstractThis research contributes to the ongoing efforts to transition towards clean and renewable energy sources by providing a practical framework for decision‐making in energy resource planning. Hence, a recently developed multi‐criteria decision making technique tool is proposed for simultaneous evaluation of criteria and alternatives (SECA) to find an optimal site for establishing photovoltaic power stations in Iran. The proposed SECA method provides a systematic and comprehensive approach to evaluating renewable energy resources, taking into account technical, economic, environmental, and social factors. The data required for this research has also been collected from the Global Solar Atlas as well as the Iran Meteoritical Organization. The results show that despite the main influence of the solar radiation factor, it should be noted that among all the climatic and environmental indicators, “cloudiness factor” by weight of 0.2339 and “annual temperature” by weight of 0.2320 have been selected as the most important criteria. It was also found that among the ten candidate cities, Zahedan (w = 0.8939), Shahrekord (w = 0.8341) and Kerman (w = 0.8112) have the highest potential for building a solar power plant. The results of the study highlight the potential for solar energy resources to meet Iran's electricity needs in a sustainable manner.

Wind Power Plant Location Selection with Fuzzy Logic and Multi-Criteria Decision-Making Methods

This study aims to examine the effectiveness of the fuzzy multi-criteria decision-making methods, especially Fuzzy Weight by Envelope and Slope (F-WENSLO) and Fuzzy Ranking Alternatives with Weights of Criterion (F-RAWEC) for evaluating the potential locations for wind power plants. The study's objective is to provide a solid framework for deciding which locations are most suitable for wind energy projects, taking into account various criteria and expert opinion. The study includes the evaluation of five potential places including Gürün, Kangal, Divriği, Ulaş and Zara in Sivas province of Turkey. The evaluation criteria include wind speed and direction, altitude, land use, environmental impacts, infrastructure proximity, social acceptance, economic costs, security and risk factors, climatic conditions and legal and permit requirements. Scores from experts from various fields and weights of criteria were determined. The analysis revealed that Ulaş and Kangal got the highest point for the wind power plant installation. As Ulaş gets the highest point due to favorable wind conditions, favorable altitude and advantageous land use; Kangal stood out as a strong candidate because of its acceptable wind speed, positive social acceptance and low economic costs. The study highlights the importance of integrating multiple criteria and expert assessments in the decision-making process. The findings suggest that fuzzy multi-criteria decision-making methods can be effectively supportive of wind power plant site selection. The study provides valuable information for project managers and policy makers, emphasizing the importance of criteria such as security in the choice of location, legal requirements and social acceptance. Future research may expand these findings to examine the integration of additional criteria, alternative locations, and other multi-criteria decision-making techniques.

Environmental Limitations of the Use of Solar Energy in the Carpathian Region

Abstract. The purpose of the work is to study the environmental limitations of using solar energy in the Carpathian region of Ukraine. Problem. A number of main restrictions affecting the location of solar power plants are highlighted, which are analyzed in the process of carrying out a strategic environmental assessment and are substantiated by calculation in the process of the environmental impact assessment procedure. For solar power plant projects, the main environmental limitation is the use of land areas. In the Carpathian region, plots under solar power plants must bypass agricultural land, recreational and touristic use, buffer zones of nature reserves. An important technical limitation is the ability to connect solar power plants to electrical networks. Methodology. In the course of the research, the regression analysis of the dependence of the amount of electricity produced by the experimental solar power plant at the Ivano-Frankivsk National Technical University of Oil and Gas on meteorological parameters was further developed using statistical processing of a series of observations. Results. Originality. It was determined that the air temperature has the greatest influence on the production of electrical energy with a correlation coefficient of 0.919. A direct linear relationship indicates an increase in power generation with an increase in air temperature up to +250C. Relative humidity has a fairly significant effect on the generation of solar energy. The resulting correlation coefficient of 0.776 indicates a close relationship between the two data series. When the humidity increases to 76%, the production of electricity by solar photovoltaic panels increases and decreases with a further increase in humidity from 75 to 100 %, which is associated with an increase in cloudiness under such weather conditions. Wind speed also has a strong correlation with solar power generation. Electricity production increases in conditions of low wind or almost windless weather with a wind speed value of up to 2.9 m/s and decreases with a further increase in wind speed. Practical value. The obtained significant regularities will be of practical importance for the justification of environmental restrictions when using solar energy for the conditions of the city of Ivano-Frankivsk.

Assessment of water quality in the Great Zab River (Erbil city, Iraq) exposed to wastewater from different industries using the WQI and GIS-based Python script approaches

ABSTRACT This study was conducted to assess the water quality of the Great Zab River (GZR) under potential pollutant pressure from some industries. The Water Quality Index (WQI) was used to evaluate the results of the water quality monitoring study. WQI and Geographical Information System (GIS)-based Python scripts were used to evaluate the results. Results indicate varying water qualities, ranging from moderate to poor, with fluctuations attributed to pollution from industrial plants mixing with river water. The WQI rating of the GZR before industrial discharges was 57.48, and in the lower part, after discharges, the WQI rating was 56.00, indicating marginal water quality. In contrast, the areas near the Cola Factory, where the river confluence occurs, have WQI values of 43.32 and 44.97, representing unacceptable, poor water quality. The study highlights that the refinery, Cola factory, and power plant locations significantly impact the river's water quality. These findings underscore the urgent need to adopt ecological practices, establish environmental regulations, and implement sustainable technologies to preserve the river's natural state. Concise measures aimed at eliminating pollutant sources and enhancing environmental awareness within communities are essential for the conservation of the GZR and the the protection of its surrounding ecosystems. surrounding ecosystems.

Analytic network process (ANP) based decision support tool for nuclear power plant location and reactor type selection

The nuclear energy industry has seen a resurgence due to interest in sustainable energy. Regulatory agencies are evaluating innovative technology and facility designs for the first time in a long time. The nuclear energy business needs a workable instrument for decision-making in light of the shift in public and regulatory opinion. This study has two main motivations. The first is to determine the set of criteria to be used in determining suitable locations for a nuclear power plant (NPP) to be established in Turkey and to determine suitable regions with Analytic Network Process (ANP) based analyzes in the light of these criteria. The second is to select the most suitable nuclear reactor type for the specified location. Plant efficiency and lifetime vary depending on the reactor type used. For this reason, in the study, both the location of the nuclear power plant and the selection of the appropriate reactor type for the plant were evaluated together. In this context, a criterion set consisting of 3 main criteria and 20 sub-criteria to be used in NPP installation location and reactor selection was determined. In the study, site selection was made by focusing on economic, social and technical factors, and reactor selection was made by focusing on technical factors. Giresun, Trabzon, Rize and Artvin provinces located in the Eastern Black Sea region were evaluated for NPP installation. For reactor selection, we focused on reactor types according to their coolants and in this context, PWR, PHWR, GCR and BWR reactors were examined. NPP location and reactor selection in the study; It was realized as Giresun (PWR) > Rize (PWR) > Trabzon (BWR) > Artvin (BWR).

Predicting power and solar energy using neural networks and PCA with meteorological parameters from Diass and Taïba Ndiaye

The excessive reliance on conventional fossil fuel-based resources poses a significant threat to our environment. To mitigate this impact, it has become increasingly crucial to increase the integration of intermittent and non-polluting energy sources into our electrical grids. However, while this higher penetration rate brings benefits such as improved producer satisfaction and reduced fossil fuel consumption, it also presents challenges for traditional non-smart electrical networks. To promote intermittent energy sources effectively and maintain a balance between consumption and production, accurate forecasting of these energy outputs plays a vital role. This research paper focuses on studying the application of artificial neural networks for predicting the power and energy output of the Diass solar power plant in the short and medium term. The proposed approach utilizes not only the meteorological data from the city where the power plant is located but also data from a nearby city with a data acquisition station. Principal component analysis (PCA) is employed to select the relevant variables for the prediction model. Furthermore, the results obtained from our approach are compared to existing literature that solely uses meteorological data from the power plant's location. The comparison shows that our method achieves more satisfactory results, with mean absolute errors and root mean square errors of 0.0223 KWh and 0.003 KWh, respectively, and a prediction accuracy of 94.57% in terms of energy and power. It is worth noting that the computational resource requirements for our approach are higher, with simulation times ranging between 1788 seconds and 2201 seconds. By utilizing a broader range of data sources and employing advanced techniques like artificial neural networks, this research contributes to improving the accuracy of solar power generation forecasts. The findings highlight the potential of incorporating additional data inputs and advanced modeling techniques to enhance the performance of renewable energy systems, paving the way for a more sustainable and efficient energy future.

Offshore and onshore renewable energy system modelling to meet the energy demand of megacity Istanbul

In this study, a renewable energy system was designed using offshore and onshore energy sources to meet the electricity demands of the megacity Istanbul. Istanbul spends about 11 % of Turkey's consumption according to 2022 data, this electricity fee is generally supplied from fossil fuels, which cause large amounts of greenhouse gas emissions. In this study, to increase the usage of clean energy sources, a detailed analysis of the appropriate land was performed to install the necessary wind farms and solar farms, considering the electricity consumption of both the European and Anatolian sides of Istanbul. A new integrated approach using Geographic Information Systems (GIS), Multi-Criteria Decision Making (MCDM) and Analytical Hierarchy Process (AHP) was presented to determine the locations of offshore and onshore power plants to be installed. The analysis with a new approach took into account important criteria such as land cover, power transmission lines, substations, and settlements of the location. Moreover, HOMER software optimized the power plant’s energy production potential and components to be installed on the European and Anatolian sides. The megacity was considered as two sides, the overall power output on the European side was obtained as 2874.6 GWh/yr in HOMER; however, the Anatolian side was 158 GWh/yr. It was obtained that wind energy had a significant potential to produce electricity throughout the entire megacity. According to the results of the cost analysis, the European side with a cost of electricity (COE) of 0.0105 $/kWh is conspicuous, and the COE of the Anatolian side is 0.015 $/kWh.

A comparison on the critical success factors of MSW and RDF power plant development in Thailand: Using an interpretive structural modelling and cross-impact matrix multiplication applied to classification analysis

Waste-to-energy (WtE) power plants, supplied mainly with municipal solid waste (MSW) and refuse-derived fuel (RDF), which convert waste into electricity, have emerged as a solution to Thailand's waste management problems. This study focused on identifying and studying the critical success factors (CSFs) that influence the success of MSW and RDF power plants in Thailand. This study employed interpretive structural Modelling and cross-impact matrix multiplication applied to a classification analysis to evaluate the impact of these CSFs on the development of WtE projects. The results showed that, for MSW, most CSFs were related to energy and waste management policies, followed by waste quality for electricity generation. In addition, strong financial resources and appropriate power plant locations are important for MSW management success. Conversely, for RDF, most CSFs were sufficient waste quality for electricity generation and performed well according to licensing conditions. In this study, high-level CSFs indicated that these factors were crucial for MSW and RDF development. CSFs differ based on specific technologies and regulations. However, sufficient waste quality (heating value and moisture content) is a common CSF in the MSW and RDF technologies. This study provides valuable insights into the CSFs that affect the development of WtE. Understanding and addressing these CSFs is essential for the development and operation of WtE power plants in Thailand and other countries with similar conditions. Thus, policy-makers and other stakeholders can make informed decisions to ensure the success of WtE projects.

Determining the Location of Solar Power Plant in Indonesia Using Fuzzy-AHP TOPSIS

Solar is a promising renewable energy source for Indonesia's increasing electricity demand, which grows at the rate of 3.3% annually. However, high investment costs and unclear policies hinder Solar Power Plant (SPP) development. Considering the potential for growth in energy demand and the low long-term operational costs, it is imperative to foster SPP expansion in Indonesia. This study aims to identify location criteria and potential SPP development sites in Indonesia. We employ Multi-Criteria Decision-Making (MCDM) combining Fuzzy-AHP and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) methodologies to assign criteria weights and prioritize alternative SPP locations. Results show that, from all respondents using the geometric mean in the Fuzzy Analytic Hierarchy Process (AHP), it is found that the Economic criteria give the highest weight at 31%, and subcriteria of Land Availability, Peak Sun Hours, Geographic Location, Distance from Transportation Networks, Construction Costs, and Government Regulations contribute significantly. The ranking of alternative solutions indicates that South Sumatra Province holds the highest priority for SPP development with a 0.572 score, closely followed by North Sumatra at 0.571

Sistem Monitoring Berbasis IoT pada Pembangkit Listrik Tenaga Mikrohidro Tangsijaya

The Micro Hydro Power Plant of Gunung Halu was established in 2007. While electricity from the national power grid is available in the village of Gunung Halu, not all hamlets receive a consistent power supply, particularly those with hilly topography and areas surrounded by forests like Dusun Tangsijaya. The existence of the micro hydro power plant in Tangsijaya is supported by a stable water flow from the river. However, one of the challenges faced by the operator is the lack of a monitoring system for the micro hydro power generator that can provide information about its condition, such as power output and electric current. Until now, the operator has checked the data by visiting the location of the micro hydro power plant directly, which is located outside the residential area. Manual recording relies on the existence of human resources and produces results with a low level of accuracy. In this community service activity, a monitoring system was installed at the Tangsijaya's micro hydro power plant. Leveraging Internet of Things (IoT) technology, this system can display data in real time, so that data visualization can be monitored by relevant parties. With a monitoring system, micro-hydro operators can control the usage and distribution of the generated electricity. In addition to obtaining records of daily electricity usage data, recorded data provide very valuable information in assessing current and potential electricity usage for making decisions related to electricity production. After the implementation of the monitoring system, the main benefits are felt by microhydro operators where the work processes they do become more efficient. Efficiency is obtained in terms of travel distance where operators do not need to visit the PLTMH location directly, and also efficiency in the recording process which no longer needs to be done manually.

Decision-Making Approach to Design a Sustainable Photovoltaic Closed-Loop Supply Chain Considering Market Share for Electric Vehicle Energy

This study aims to develop a model for the closed-loop supply chain of photovoltaic (PV) systems. The primary objective addresses strategic and tactical decision-making using a two-stage approach. To pinpoint suitable locations for solar power plants, the PROMETHEE II method is utilized, which is a component of multi-attribute decision making (MADM) approaches. Next, a multi-objective modeling of the closed-loop PV supply chain is conducted. This model aims to minimize total supply chain costs, reduce environmental impacts, mitigate adverse social effects, maximize the on-time delivery (OTD) of manufactured products, and maximize market share. Additionally, a robust fuzzy mathematical model is introduced to examine the model’s sustainability under various uncertainties. An evaluation of the effectiveness and utility of this model is conducted in Tehran city. Furthermore, a comprehensive analysis of various supply chain costs indicates that production centers have the highest costs, while separation centers have the lowest costs.

Zoning of Degraded Areas Suitable for Implementation of Renewable Energy Generation Systems: Systematic Review

Objective: The objective of this study is to investigate and carry out a systematic review of the literature, with the aim of delving deeper into the topic of zoning and selection of areas for the implementation of renewable energy generating plants. Theoretical Framework: In this topic, the main concepts and theories that underpin the research are presented. The elaboration of the research protocol in four stages: elaboration of questions, choice of databases, definition of the search strategy and inclusion/exclusion criteria, providing a solid basis for understanding the context of the investigation. Method: The methodology adopted for this research comprises the choice of databases and definition of the search string based on the research protocol. Data collection was made by searching Scopus, Science Direct, Web of Science and Energy Citations Database - OSTI. Results and Discussion: The results obtained revealed that 309 studies met the research protocol, of which only 29 studies, after reading the abstract, were ready for the full article reading stage. Seven of these were accepted as relevant to the objective, being classified as accepted and participating in the information gathering to meet the proposed objective. Research Implications: The practical and theoretical implications of this research are discussed, providing insights into how the results can be applied or influence practices in the field of georeferencing. These implications may include public and private enterprises that aim for a less environmentally aggressive methodology for selecting sites for renewable energy generation. Originality/Value: This study contributes to the literature by showing the most relevant points and the main gaps in current selection methodologies. The relevance and value of this research are highlighted by representing a new way of thinking about choosing new locations for power plants.

Off-design performance analysis of supercritical CO2 mixture Brayton cycle with floating critical points

The thermodynamic performance of supercritical CO2 (sCO2) Brayton cycle deteriorates significantly due to the mismatch between the cold source temperature and the working fluid’s critical point. Here, we present the first study on the off-design performance of a novel supercritical CO2 mixture Brayton cycle with floating critical points. A distillation based regulation subsystem is integrated into the power cycle to dynamically adjust the circulating composition of the binary CO2 mixture, thereby making its critical point float with the ambient temperature and achieving good temperature matching. The off-design behavior of the system operating with the representative mixture is investigated based on an in-house code. The influence of trigger conditions of critical point regulation on energy consumption of the regulation process is investigated. When the maximum temperature difference of the design points for consecutive days is set to 3 °C, the equivalent power consumption can be limited to 2.34 × 106 MJ per year, which affects the annual efficiency by less than 1 %. The results confirms that using the floating critical point method can improve the annual efficiency by 7 %-10.9 % and improve the specific output power by 6.1 %-9.4 % compared to the sCO2 cycle, depending on the power plant locations.

Optimizing Geothermal Power Plant Locations in Indonesia: A Multi-Objective Optimization on The Basis of Ratio Analysis Approach

Optimizing Geothermal Power Plant Locations in Indonesia: A Multi-Objective Optimization on The Basis of Ratio Analysis Approach

Multi-criteria solar power plant siting problem solution using a GIS-Taguchi loss function based interval type-2 fuzzy approach: The case of Kars Province/Turkey

The determination of the areas where the solar power plant will be installed is of great importance for the performance of the solar power plant. Solar and hydroelectric energy are the most widely used renewable energy sources in Kars province. Site selection for these power plants is an important factor in terms of reducing the installation cost of the solar power plant and achieving maximum efficiency during operation. Determining the areas where the power plants will be installed is a very complex and difficult to analyse spatial decision making problem. In this study, firstly GIS is used as a mapping method to obtain the locations of both solar power plants in Susuz, Arpaçay, Akkaya, Kars city centre, Selim, Digor, Kağızman and Sarıkamıș districts of Kars province and then Taguchi loss function based interval type-2 fuzzy approach is applied to the problem. In order to obtain more accurate results, the results of the two methods (GIS and Taguchi loss function based interval type-2 fuzzy approach) were also compared. According to the solar power plant map obtained, it was determined that the total area of suitable areas is 78600 km2.

Measurement of Environmental Gamma Radiation Dose Rates and Estimation of Radiation Risk near the Construction Site of the Nuclear Power Plant, Indoor and Outdoor Locations of the Research Reactor, and Coal-Fired Thermal Power Plant Area

Measurement of Environmental Gamma Radiation Dose Rates and Estimation of Radiation Risk near the Construction Site of the Nuclear Power Plant, Indoor and Outdoor Locations of the Research Reactor, and Coal-Fired Thermal Power Plant Area

On identifying suitable hydrogen power plant location under [formula omitted]-spherical fuzzy hypersoft matrix structures

In recent decades, the prime objective of the energy sector has been to replace conventional energy sources with renewable energy sources such as hydrogen power, solar energy, etc. The objective of the present communication is to computationally locate the best site for the establishment of the hydrogen power plant given the various uncertainty parameters in terms of inexact and incomplete information. The uncertainty components of the information are well dealt with by the incorporation of T-spherical fuzzy hypersoft information. In accordance, we present the new concept of T-spherical fuzzy hypersoft matrix (TSFHSM) with different matrix-theoretic structured possibilities having useful computational setups. Some standard matrix operations with their algebraic properties have also been studied. Next, the structure of the proposed matrix has been utilized in presenting two new methodologies for the decision-making selection problems — one with the help of choice/weighted choice T-spherical fuzzy hypersoft matrices and the other with the value & score T-spherical fuzzy hypersoft matrices. Further, an illustrative example where the set of sites for the selection of hydrogen power plants has been computationally studied with the help of the presented novel algorithms given the available criteria. The efficacy of the proposed algorithms and their implementations have been discussed along with a comparative analysis, advantages and a characteristic comparison table.

Thermo-economic feasibility study to utilize ORC technology for waste heat recovery from Indian nuclear power plants

A feasibility study is essential before installing a power generation system to recover waste heat from nuclear power plants, but not yet been done. Hence, nine possible waste heat locations of Indian nuclear power plants are identified and two feasible cases (case-1 and case-2) are deduced to use the organic Rankine cycle (ORC) as a bottoming cycle. Energy, exergy, economic and environmental performances are evaluated for feasible cases with three working fluids. Capital investment in alternator has been correlated based on market data and applied in economic analysis. The economic study is based on Net present value, Discounted payback period, Levelized cost of energy, Internal rate of return, Profit and per unit build-up cost of ORC to suggest whether the installation is worth to venture or not. The result shows that below 41 °C condenser temperature, case-2 based bottoming ORC should be the priority to install and at the availability of sufficient funds, both cases can be installed, which will cumulatively produce 486.2 kW of electricity from waste energy with a total of 201.14 thousand USD annual profit from the total capital investment of 723.74 thousand USD. In 40 years of the project's lifetime, a total of 1.317 million USD will be used if both cases are employed and the invested cost will be returned in 8.3 years.

Assessment of Off-Grid Power Plants in Nigeria: Location, Capacity, Performance and Current Status

The power sector in Nigeria still struggles with significant electricity challenges resulting from the unavailability of power supply and the unreliability of the conventional national grid. The total installed capacity of off-grid plants in Nigeria is approximately a meagre 52 MW, with a combination of 67 operational mini-grids and solar home systems across the country impacting only about one million households and around five million residents out of Nigeria’s population of over 200 million people. It has been reported that both urban and rural areas suffer the impact of power shortages and frequent blackouts. The unreliability of power supply in Nigeria has been identified as a significant problem affecting educational institutions in terms of productive learning, student residency and institutional operations, and also the overall operation of healthcare facilities as it limits access to quality healthcare services. The study examines the presence and potential of off-grid power solutions in Nigeria which present a more reliable approach to supplying electricity to users, as a deliberate response to the multiple and complex challenges in the Nigerian power systems to identify the present location, installed capacity, operational performance, and current status of off-grid power plants in Nigeria. The Geographic Information System and statistical approaches were employed. It was discovered that off-grid solutions are beginning to spread across the country on different scales. However, most rural areas in Nigeria still do not have access to electricity supply. The study encourages decentralized power generation in the country and emphasizes the need for the federal government through the Rural Electrification Agency (REA) to consider investing in off-grid solutions, particularly in the rural areas for socio-economic benefits.

Developing a Multi-Criteria Decision-Making model for nuclear power plant location selection using Fuzzy Analytic Hierarchy Process and Fuzzy VIKOR methods focused on socio-economic factors

In response to its position as the fourth most populous country globally, Indonesia is exploring constructing nuclear power plants (NPPs) as a sustainable energy solution. A pivotal step in this initiative is selecting an appropriate NPP site. This study employs two Multi-Criteria Decision-Making (MCDM) methods, the Fuzzy Analytic Hierarchy Process (Fuzzy-AHP) and Fuzzy VIKOR, to identify the most suitable location for an NPP, focusing on socio-economic factors. The Fuzzy-AHP method is utilized to prioritize ten sub-criteria: transmission network, operating costs, economic impact, security, transportation network, legal considerations, the impact of tourism, land ownership, historical sites, and public acceptance. Following this, the Fuzzy VIKOR method leverages these prioritized criteria to evaluate two potential sites: East Kalimantan and West Kalimantan. The analysis reveals that security, transmission, and transportation networks emerge as the top priorities. The application of the Fuzzy VIKOR algorithm identifies West Kalimantan as the optimal site for NPP construction, evidenced by its lower VIKOR index of 0.3599, indicating a higher overall preference based on the evaluated criteria. The study demonstrates that the integration of Fuzzy-AHP and Fuzzy VIKOR methods prioritizes critical socio-economic factors and quantitatively assesses potential sites, offering a systematic and objective approach to support decision-making in NPP site selection.