Location Of Power Plants Research Articles

Determination of the optimal location of power plants as a part of an autonomous power supply system based on renewable ener-gy sources

The paper proposes the problem solution of optimal location determining of several power stations in some region. These stations receive primary energy from renewable sources, such as solar panels and wind turbines. At the same time, the condition of the problem includes the availability of information on several perspective areas in this region for the placement of such power stations, as well as information of values and distribution of loads. The developed algorithm for solving of the optimal location selection problem of power stations consists of several stages. The content of the first stage of the algorithm is ranking of possible areas for the location of power stations using local criteria, which are proposed as the specific estimated cost of station arrangement, the remoteness of the proposed location of the power station from loads and settlements. The second stage of the algorithm consists in a set formation of possible areas for the location of stations. And at the final stage of the algorithm, they are ranked using system criteria that evaluate these sets of areas for the location of power stations as a power supply system. The estimated cost of a power supply system arrangement based on power stations, located on areas of the rated set, the specific estimated cost of power stations arrangement, applied to the set of power stations with power lines as an autonomous power supply system, as well as the average rating of areas are proposed as system criteria. In this case, the decision maker, after familiarizing with values of system criteria, sets critical boundaries for each of them. The result of the algorithm is a certain totality of prospective sets for the location of several power stations in a given region, estimates of which according to system criteria are the best correspond to preferences of the decision maker. A feature of the proposed approach is the participation of the decision maker at all stages of design.

DEVELOPMENT PROCESS AND SPATIAL TRANSFORMATION OF TOMIOKA TOWN, THE MUNICIPALITY WHERE THE NUCLEAR POWER PLANT IS LOCATED AND AFFECTED BY THE DISASTER

Tomioka Town, which is the location of the nuclear power plant and the disaster-stricken municipality, became the main player in urban planning in modern times and gathered the population in the center, but the finances deteriorated and the population decreased. The location changed, but a hydrogen explosion caused the entire town to evacuate for six years. The population has plummeted, and half are short-term nuclear workers. They live in single-person apartments in the land readjustment project area. This situation is the same as before the disaster, except that various players were active in the center.

Novel DE-based Optimization Technique for the Renewable Sources' Integration

Ever since the thermal generation units, once a foundation of a large number of the power systems, were marked as one of the main emitters of greenhouse gases and, therefore, undesirable in the modern systems, the renewable energy sources are taking over their share in the generation mix. Although this process is going fast, it might still not be efficient enough to reach the climate goals, set with short deadlines. In accordance with that, every measure that enhances the integration of renewable sources into the grid and makes the application process for the new investors simple and straightforward is welcome. To aid that cause, this paper proposes the method for determining the optimal location of the new wind power plant in the predefined geographical area, taking into account both the characteristics of the power system in that region and the relevant climatic indicators. This technique was developed by utilizing the differential evolution mechanism, while introducing a novel space search formula that ensures the avoidance of the local optima. For the mapping of the solutions and switching between the discrete and continuous values, the georeferencing principle was implemented. This method was illustrated on the part of the Serbian real-life system.

Damping Torque Analysis of the PMSG-Based WT with Supplementary Damping Control for Mitigating Interarea Oscillations

This study presents a comprehensive analysis of the impact that a supplementary damping controller of the permanent magnet synchronous generator (PMSG)-based wind turbine (WT) has on low-frequency oscillation (LFO) damping. A reduced mathematical model of an interarea system is first established. Then, an auxiliary damping controller is designed using the PMSG active power control loop, enabling the WT to actively support the interarea LFO mitigation. Based on this, the damping torque analysis (DTA) method is applied to explore the contribution of the PMSG-based WT with an auxiliary damping controller to LFO damping enhancement, whose analytical expressions of the damping torque coefficients reveal the impacts of the control parameters and the operation conditions on the system damping characteristics. It is evident that the installation location of the wind power plant (WPP) plays a leading role in determining whether the damping provided by the PMSG controller is positive or negative. Also, the contribution of damping from the PMSG can be improved by tuning the droop coefficient of the PMSG controller properly. The results indicate that the proposed damping control is always helpful in improving the system damping when the wind power penetration increases. Accordingly, analytical conclusions can serve as guidelines for the control design. Case studies of a two-area test system integrated with a PMSG-based wind farm have been conducted to verify the theoretical analysis.

A Multicriteria Decision Framework for Solar Power Plant Location Selection Problem with Pythagorean Fuzzy Data: A Case Study on Green Energy in Turkey

Turkey is one of the most suitable countries for solar power plants, owing to its ideal location in terms of receiving solar radiation; accordingly, plans are in place to expand its solar power plant system to fulfill the increasing energy demand. In this study, a combination of multicriteria decision-making and fuzzy logic was used to evaluate potential locations (cities in southern Turkey) to install new solar power plants subject to different criteria of an uncertain nature. The proposed methodology has several attractive features, which are described throughout this study. The criteria were selected based on the literature and the opinions of experts. In addition, a new criterion (capacity of existing solar power plants) was added to achieve more precise results. Ten criteria and eighteen cities were selected to form the decision matrix for the problem. First, the weight of each criterion was computed by stepwise weight assessment ratio analysis (SWARA). Then, the TOPSIS approach was extended to the Pythagorean fuzzy form in ranking the locations of the decision matrix as a new solution procedure. The results show that the best candidate city to install a new solar power plant is Antalya, followed by Karaman and Malatya as the second and third best candidates, respectively. Finally, to measure the impact of the changes in the weight of the criteria, a sensitivity analysis was conducted. Multiple scenarios were considered, and the results indicated that Antalya was the best alternative in most of the scenarios.

State-of-the-art: Multi criteria decision making variables on solar PV business potential

Most developing countries, such as Indonesia, have increased targets for renewable energy. These developing countries still have limited framework alternatives that can be used as a business assessment tool or guideline for renewable energy. The characteristics in developing countries are different from developed countries, there are some challenges in adopting the global renewable energy tools that do not suit the characteristics of developing countries. Several literatures describe several variations of methods for decision making in the field of renewable energy sources, particularly the multi-criteria decision analysis (MCDA) method. The Analytic Hierarchy Process (AHP) method has been at the forefront as the most widely used method for evaluation of the best location. Due to the climate, proximity to other facilities, and the existence of protected environmental areas, the location of photovoltaic power plants is a key issue for large-scale projects. There are some papers that analyze and research about the selection process and method to choose the best location. This research has compiled and analyzed the state-of-the-art in MCDA variable in energy business potential decision making research that has been conducted in the past years and looks for research gaps that can be used as a reference for conducting further research. From the analysis, there is still a gap in current research that fulfills all aspects (technical, politic, economy, social, legal, environmental) into one assessment. Technical aspect is the most used variable and the legal aspect is the least used variable. Analyzing all six aspects into one integrated risk assessment to select the potential location for floating solar PV will be the novelty of the research. In addition, the existing studies are dominated by land solar PV objects and very few have raised the topic of floating solar PV. This is something that needs to be studied because the risk character of floating PV is different from land PV.

Potential and Economic Evaluation of Biogas Resources and Location of its Power Plants with GIS in Iran

Excessive consumption of fossil fuels has led to threats to energy reserves and environmental issues as two common concerns of today’s societies. On the other hand, renewable energy sources have been growing as alternative sources to reduce severe environmental problems such as global warming, climate change, and acid rain. As a result, it is necessary to assess the potential of renewable resources and the location of power plants related to them. Among renewable energies, biomass energy and biogas have a high status and importance, accounting for a significant share of energy production. Therefore, choosing a suitable location for biogas power plants in energy production and transmission, cost reduction, and environmental aspects. Today, the use of GIS has made it possible to integrate the information needed for location effectively. Therefore, in this study, while identifying the influential factors and criteria in the location of biogas power plants and the AHP hierarchical analysis process as one of the multi-criteria MCDSS decision-making methods to the location of biogas power plants in Iran, as one of the criticalroles in the production of agricultural biomass, livestock and poultry, and waste has been addressed. The results of the economic analysis showed that the construction of biogas power plants is justified in cities where the cost of the power plant is less than 0.098 USD per cubic meter of gas produced and the average cost of biomass is less than 0.0915 USD per cubic meter of synthetic gas.

The effect of population density on the suitability of biomass energy development

Biomass, as a kind of renewable and clean energy with large reserves, provides a carbon-neutral solution for today's environmental degradation caused by fossil fuel combustion. Population density is a key factor that influences a region's suitability for biomass development. By examining the impacts of population density on the suitability of biomass energy development, this paper is committed to locating the interval of population density suitable for developing biomass energy, thereby providing data as a reference for biomass energy development planning in a region. The paper utilized a spatial analysis tool to identify the location of biomass thermal power plants, and studied 51 districts, counties, and county-level cities within service areas. The percentages of biomass energy supply have been obtained by calculating the total biomass energy demand and supply. And multiple regression analysis on the percentage and population density. The analysis result shows that population density and suitability of biomass energy development are negatively correlated. The relationship between the two can be divided into four intervals: extremely suitable, relatively suitable, relatively unsuitable, and extremely unsuitable.

Spatio-temporal dynamic clustering modeling for solar irradiance resource assessment

Nowadays, with the development of international policies and agreements to promote the integration of renewable energy sources, mainly solar and wind, modeling the solar resource by including the spatio-temporal variability is crucial to determine future PV power plant locations and estimate potential power generation performances. However, contributions involving long-term periods and different time windows to explore such potential solar resource variability are generally scarce. Under this framework, the present paper proposes a methodology focused on characterizing and clustering the spatio-temporal solar resource variability through the global horizontal irradiance analysis. Hierarchical clustering technique is firstly used to classify the spatial data. Different time windows — from short-term to long-term data — can be subsequently evaluated by using various sources of information. The Spanish territory is selected as case study, considering 22-year period data (1999–2020) and 1,936,917 observations from online satellite database. Spatial variability and geographical clustering differences are discussed and compared depending on the selected time windows, identifying relevant spatial variations for some specific months. Additionally, some years present more variability as well, in line with the sunspot peak of the solar cycles. The proposed approach gives an alternative comprehensive spatio-temporal clustering and characterization of GHI evolution, providing a suitable methodology to help the current European sustainable energy transition.

RESEARCH OF THE WIND POWER PLANTS GENERATION WITH ENERGY STORAGE SYSTEMS

In this work, the problem of integration of such elements of the electric power network as: industrial energy storage and directly wind generators is investigated. The sharp increase in the share of this type of electricity creates a number of issues that need to be resolved, first of all, the stochastic nature of the work. Solving this problem is relevant not only from the point of view of eliminating the phenomenon of uneven energy generation using a wind turbine, since wind is a variable source of energy, but also increasing the indicators of the interaction of the wind flow with the generator blades, i.e. increasing the permeability of the wind. This problem was noticed during the study of the operation of modern wind systems, especially the period of operation during direct start-up and in the presence of low wind speed, and therefore the efficiency is minimal. In this case, the use of energy storage systems is the best option for integration, as it allows not only to store energy, but also to increase the level of reliability of electricity supply. The work includes an overview of several variations of the location of wind power plants and energy storage systems: local, distributed, centralized. The use of one or another option depends on the size and load of the direct network. In addition, two models of energy storage were investigated in the work: storage in the rear part of the installation and storage in the front part of the installation. The study showed that using the option when the storage systems are located in the front part of the installation increases the weight of the nacelle, which is a negative factor, but installing it in the rear part or next to it increases the level of losses, which is an equally significant factor. In general, the installation of storage systems will complicate the immediate work, and also increase the cost, but in view of the future perspective, the solution to these issues is fully justified. Having solved the technological questions that gradually arise, the process of generating energy based on wind turbines and its synchronized storage will satisfy other important questions.

The novel augmented Fermatean MCDM perspectives for identifying the optimal renewable energy power plant location

The Fermatean fuzzy set has been authorized as a suitable tool for the uncertainty and vagueness of information by augmenting the spatial space of acceptance membership and non-acceptance membership degrees of both intuitionistic and Pythagorean fuzzy sets. Solar energy does not emit any hazardous gases into the atmosphere, making it one of the most effective strategies to reduce global warming in the environment. Under a variety of circumstances, finding a spot for a photovoltaic solar power plant might be difficult. As a result, we experiment with multi-criteria decision-making (MCDM) techniques. We presented a hybrid technique based on the PV-SPSS method based on the Removal Effects of Criteria (MEREC) and Multiple Objective Optimization on the Basis of Ratio Analysis with Full Multiplicative Form (MULTIMOORA) analysis. The MEREC approach is used to calculate the weightage of each attribute, and MULTIMOORA is used to find the ranking of the alternatives. Also, a new rectified generalized score function determines the score value of FFSs. Culmination: the validity of the result is assessed by implementing the existing MCDM approaches and by changing the criterion weight.

Determining Optimal Solar Power Plant Location in Melaka, Malaysia: A GIS-Based Solutions

The energy demand has risen dramatically in recent years as a result of population growth and the fast expansion of the global economy. Due to rising carbon dioxide (CO2) emissions and increasing energy needs, Malaysia has recently intensified its efforts to encourage the development of renewable energy supplies. Despite the abundance of solar resources, the PV growth in underdeveloped countries such as Malaysia is moving slower. Malaysia has the advantage in solar energy generation since it is geographically close to the equator and has a significant solar generation potential due to its hot and sunny weather all year. Therefore the question here is, where is the most suitable place to build more solar power plants? What methods will we be using to find the most suitable place to build the solar power plant? In picking a place for such development, several factors must be examined, such as how effective the PV power station site is and how to decrease the overall cost of the project by minimising proximity to existing infrastructures while improving solar panel power production. A geographic information system (GIS) is a tool that can help to solve this challenge. In this case, we integrate economic, environmental, and technical variables such as solar radiation intensity, local physical terrain, environment, climate, and placement criteria such as distance from roads and rivers. As additional input factors, other geographical information data were used (solar radiation, digital elevation models (DEM), land cover, and temperature). Further analysis using the Analytic Hierarchy Process (AHP) based Multi-Criteria Decision Making (MCDM) was then applied to this study to get the suitable location based on the importance of the criteria. In order to build a cost-effective and high-performing solar project, a complete solar site assessment is required. The results of the study should give a decision support system model and map on determining the optimal locations of solar power plants in Melaka.

Geospatial-assisted multi-criterion analysis of solar and wind power geographical-technical-economic potential assessment

Amid the increasing electricity demand, energy crisis and pollution, the transition to renewable energy (RE) is becoming a preoccupation and major global challenge due to the multidimensional and intricate problem of RE planning. In Egypt, about 90% of gross power generation comes from carbon-intensive power plants (natural gas and coal). Here, we propose a novel geospatial-decision-making model aimed at geographical-technical–economic potential mapping and assessment of solar photovoltaic (PV) and onshore wind turbine (WT) power plants at a high level of resolution (1 km2) in Egypt. We identify the locations suitable for PV and WT development considering sixteen restrictive and contradictory evaluation criteria. These locations have been further analyzed to estimate how much energy generation is available and at what energy cost.The analysis identifies Middle-Upper Egypt and Suez Canal as hosting the majority of highly suitable locations for PV and WT power plants, respectively. Our finding reveals that the proper planning on RE projects at the proposed optimum locations could support the country's energy mix with a sizable 32% share of the projected country’s electricity consumption from PV and 50% share from WT, by 2030. Furthermore, we show that the investment opportunities of PV and WT generation are potentially attractive with affordable competitive prices estimated at 57.84 $/MWh and 32.36 $/MWh, respectively, against conventional generation for today and the future.We anticipate that our results will provide valuable support in realizing Egypt’s vision for sustainable electricity generation and in keeping abreast of the global transformation in power systems being witnessed. Ultimately, the method’s relevance extends beyond the geographical boundaries of the present territory; it features a strategic, clear and reproducible approach that may be applied to a larger area or continent, provided the necessary input data and criteria are introduced.

Multi-objective optimization model for regional renewable biomass supported electricity generation in rural regions

Greenhouse gas (GHG) emissions from fossil fuel-generated electricity can be avoided by utilizing biomass (wood waste) available in rural communities. This study developed a two-layer supply chain network model comprising feedstock supply sites and candidate power plant locations. The multi-objective mathematical model considers various decisions such as power plant locations, allocation of suppliers to power plants, biomass harvesting, storage, and transportation options in the supply chain network. The goal of this formulation is to minimize the overall system cost and GHG emissions in each process of the entire network. A case study is presented in which a direct-fired power plant converts wood waste to electricity for the Grenada County, Mississippi. A Pareto solution was obtained for the case study using a Lexicographic augmented ∊-constraint algorithm. The solution with no limits on GHG emissions facilitates a higher power plant capacity, 25 MW with lower system costs and satisfies 32.1% of the total electricity demand of the case study area. The solution with the highest GHG emission restrictions (5.19 Kiloton (kt)) reduces the power plant capacity to 10 MW, which satisfies only 10.2% of the total electricity demand with higher overall system costs due to the increase in the purchase of electricity from external sources as penalty cost. Finally, a sensitivity analysis was performed by varying the total feedstock supply quantity, total electricity demand, and conversion rate of the power plant. The results show that 10.2–41.5% (base case- 40% increase in conversion rate) of the total electricity can be satisfied by the bioenergy facility taking into account the solution which facilitates bioenergy facility. In conclusion, by proper selection of power plant location and plant capacity based on the supply chain network, wood waste-based electricity generation can reduce both GHG emissions and total operational costs. This model can be applied to any region to determine the ideal location of a bioenergy facility.

Design and Simulation of Grid-Connected Solar PV System Using PVSYST, PVGIS and HOMER Software

In this paper, the design and simulation of a 5 MW solar power plant in Ghor province, Afghanistan have been investigated. A suitable place at a distance of about 8.17 km from the center of the province was selected as the power plant location. The main objective of this study is the investigation of solar renewable energy resources' capacity for generation of electrical energy from domestic resources to provide reliable and sustainable energy in the center of the Ghor province which is currently not connected to the national electrical grid. In this power plant, 6399 kWp, STP-320 W PV module, and 5300 kW Growatt convertor type were used. The PVSYST, PVGIS, and HOMER renewable energy simulation tools were used for analyzing the system. The results obtained from each simulation tool were compared together. Analysis of the results using HOMER and PVGIS shows that the annual energy generated using each simulation tool is about 11698 MWh and 10673 MWh respectively while the result from PVSYST is 11938 MWh per year. According to the obtained values, results from PVSYST depict 240 MWh more energy generation than HOMER and 1265 MWh than PVGIS simulation tools annually. These values indicate that PVSYST produces higher annual power for this system than HOMER and PVGIS. Comparing the annual generated power results of the simulations with reference to the PVSYST results, it can be concluded that PVGIS is 10.6% lower and HOMER is 2% lower. There is about a 2% difference between PVSYST and HOMER.

Optimizing The Performance of Photovoltaic Power Plants Through the Root Cause Analysis Method

Photovoltaic Power Plant (PV Power Plant) with various capacities, types, and locations have been built in Indonesia since 2011 until now, some of which have less than optimal performance and even do not last long. The limited management and problem-solving of PV Power Plant is the main obstacle. Several PV Power Plant performance analysis studies have been carried out but are still partial, not yet integrated from several aspects of the assessment. A thorough evaluation is needed by tracing the root causes of the problem in PV Power Plant, which is easy to understand and do in general on various types of PV Power Plant. In this study, an integrated PV Power Plant performance analysis was carried out through Root Cause Analysis and recommendations for follow-up solutions. The results of the research of PV Power Plant I (50 kWp, On-Grid), PV Power Plant II (100 kWp, Off-Grid), and PV Power Plant III (350 kWp, On-Grid), which are located on the islands of Sulawesi and Maluku show that the performance of PV Power Plant II and PV Power Plant III is not optimal (Performance Ratio < 60%) while PV Power Plant I is optimal. The results of the aggregation of the causes of the most significant losses come from Inverters, Batteries, and Solar Modules. The results of the Root Cause Analysis show that losses are caused by non-periodic maintenance factors, less reliable design and construction, low material quality, and inadequate PV Power Plant operator competence. Recommended priority for replacing damaged inverters and batteries includes optimizing design, material quality, construction, periodic maintenance, and regular training programs for operators. Based on the research results, the overall effort to optimize PV Power Plant performance through the Root Cause Analysis approach is easy to understand and easy to use in general for various types and capacities of PV Power Plant and different locations to optimize follow-up plans for improvements effectively for the sustainability of a PV Power Plant operation.

Optimal siting of a nuclear power station in Nigeria using fuzzy grey relational analysis

One of the primary causes of Nigeria's underdevelopment is a lack of electricity to power the country's industries. Rather than relying solely on fossil fuels to generate electricity in Nigeria, a variety of other sources, such as nuclear energy, must be considered. A Nuclear Power Plant's (NPP) location is a critical step in its development. This paper thus presents a methodology for resolving the issue of NPP site selection. For this project, the fuzzy Grey Relational Analysis (GRA) method was chosen. To assess the feasibility of the approach, one of Nigeria's six south-south states was chosen as the location of a hypothetical nuclear power plant. According to the findings, the NPP would be best located in Delta State, which had the highest gray relational grade of 0.7897.

Life cycle assessment of power generation using cocoa pod husk in Côte d’Ivoire

Objectives: This study assesses the environmental performance of cocoa pod husk as a fuel for a biomass power plant in Côte d’Ivoire. Methods: In this study, a life cycle assessment (LCA) is applied to identify four environmental impacts generated during the production of electrical energy. LCA assesses the environmental impact on the global warming potential of electricity production from a biomass power plant using a cocoa pod husk in Côte d’Ivoire. The greenhouse gas emissions of this electricity production are compared with those of other energy sources. Findings: The results show that the production of one kilowatt-hour results in the emission of 1.12 g SO2eq,0.28 g PO4eq., 9.91 g 1.4 DBeq. and 328.22 g CO2eq. These emissions involve acidification, eutrophication, human toxicity and global warming respectively. The sensitivity analysis showed that the transport distance has an effect on the greenhouse gas (GHG) emissions of the chain. The sensitivity analysis showed that the transport distance has an effect on the GHG emissions of the sector. Thus, GHG emissions increase with the distance travelled by the transport vehicle. The analysis identified power plant locations that would reduce GHG emissions for the production of 1 kWh of electricity. Novelty: The life cycle assessment was used to evaluate the environmental impact of various processes using crop residues for energy purposes. Keywords: Bioenergy; Crop residues; Cocoa pod husk; LCA; Thermal power plant

Rainwater Harvesting Systems That Reduce Water Consumption With Optimal Locations of Solar Concentration Power Plants

At present, the increase in population has caused an increase in the demand for electrical energy, which creates saturation in the national electrical system. In addition to this, the main source of energy for the generation of electricity is fossil fuels, which causes environmental pollution problems due to the increase in the concentration of greenhouse gases. To counteract the negative environmental impact, new energy sources that are friendlier to the environment have been sought, such as solar energy through power generation plants using solar concentrators. In this sense, this research proposes a mathematical optimization model to determine the feasibility of installing electric power generation plants through solar concentrators, to satisfy the energy demand in cities with the highest demand for electric power in the state of Michoacán. The proposed model considers the availability of water resources, the demand for energy, the costs involved for the installation of power generation plants, and the sizing of water collection systems to reduce the consumption of fresh water that is extracted from natural sources. It is a linear integer mixed programming model, where two scenarios are analyzed, considering variation in the operating time of the thermal storage system and the incorporation of the rainwater harvesting system to reduce freshwater consumption. The results show that 237,600 MW can be produced by installing three of the six power generation plants considered and considering a 19 h operation with thermal storage, generating a profit from the sales of the energy produced of 6,326,700 USD/year. Likewise, with the sizing of the rainwater harvesting system, it is possible to collect 1,678 m3 for the operation of the three determined power generation plants.

Solar power plant location selection using integrated fuzzy DEMATEL and fuzzy MOORA method

Nowadays, global warming is one of the biggest problems of humanity and the main reason is energy production. Therefore, renewable energies such as wind, rain, tides, waves and sunlight are an appropriate way for producing clean energy. In this study, suitable locations for solar power plant are analysed. To do this, data and information acquired from three decision-making groups are implemented to improve an analytical tool that integrates modified fuzzy DEMATEL and fuzzy MOORA. The weights of criteria and sub-criteria are calculated by the fuzzy DEMATEL method. Decision-making groups select five eligible regions for a solar power plant in Turkey, and the fuzzy MOORA method is used to rank regions. Also, a sensitivity analysis was performed using the fuzzy AHP method and as a result, it was observed whether there was a change in the order of the alternatives.