Solar Power Plant Site Selection Research Articles

GIS-Based Multi Criteria Analysis for Solar Power Plant Site Selection Support in Mecca

One of the major sources of renewable energy, particularly electricity generation and water desalination, is solar energy. The National Initiative to produce Water and Electricity started when the electricity consumption in Saudi Arabia begun to increase by about 5% per year. The current investigation aims to use a multicriteria GIS technique to identify the best spatial location for solar energy collection in the Mecca Administrative District. The best locations for solar power plant construction were determined with the use of a set of factors and criteria, including planning and environmental criteria, and terrain calibrator. These criteria were defined through a thorough literature review. This information was then used to create a digital geographic database, which was incorporated into an integrated GIS to produce a spatial fit model. According to the suitability data, most of Mecca region is ideal for solar energy projects, with an applicability percentage ranging between 30% and 80%. These findings are encouraging and promising for Mecca's renewable energy industry and they should be considered. It was discovered by examining these spatial locations and the level of suitability to the specifications that the lands with a sufficient share of more than 80% form an area of around 4000km2 and makeup 3% of all suitable lands. The governorates of the Mecca Administrative Area are home to most of these exceptionally suited locations. The Taif governorate takes first place with 35% of the total area and the two governorates of Turbah are placed second and third with 24% and 14%. In the Mecca Administrative Area, the appropriate lands for solar energy projects are distributed spatially according to a digital map. The study proposes incorporating the findings into the Saudi national plan for renewable energy sources.

Site Selection of Solar Power Plants Using Hybrid MCDM Models: A Case Study in Indonesia

Among developing countries in Asia, Indonesia has realized the importance of transitioning from fossil fuels to renewable energy sources such as solar power. Careful consideration must be given to the strategic placement of solar power installations to fully leverage the benefits of solar energy. This study proposes a methodology to optimize the site selection of solar power plants in Indonesia by integrating Data Envelopment Analysis (DEA), Fuzzy Analytic Hierarchy Process (F-AHP), and Fuzzy Measurement of Alternatives and Ranking according to Compromise Solution (F-MARCOS) models. The proposed methodology considers quantitative and qualitative criteria to evaluate potential locations for solar power plants. In the first stage, DEA is used to identify the most efficient locations based on quantitative measures such as solar radiation, land availability, and grid connectivity. In the second stage, qualitative factors such as technological, economic, environmental, and socio-political aspects are evaluated using F-AHP to prioritize the most important criteria for site selection. Finally, F-MARCOS ranks potential locations based on the selected criteria. The methodology was tested using data from Indonesia as a case study. The results show that the proposed hybrid model optimizes Indonesia’s solar power plant site selection. The optimal locations can contribute to a cost-effective long-term renewable energy supply nationwide. The findings from this study are relevant to policymakers, industry stakeholders, and researchers interested in renewable energy development and site selection. However, to promote sustainable solar energy development, governments and local authorities must also enact supportive policies and mechanisms that encourage the adoption and growth of renewable energy technologies in Indonesia.

A new interactive method based on multi-criteria preference degree functions for solar power plant site selection

Solar power energy is renewable and clean energy, widely used to produce electricity. Its unique properties have led to increasing demands in many countries. In this regard, the importance of Multi-Criteria Decision-Making (MCDM) in solar power plants, especially site selection problems, is increasingly on the rise. Thus, this study presents a new approach suited to the nature of this problem when the amount of the required investment is a critical aspect. As managers naturally cannot rely on methods that behave as a black box, this study renders a new approach that redefines the linear relations of Interactive Simple Additive Weighting (ISAW) by multi-criteria preference degree functions of Preference Ranking Organization Method for Enrichment Evaluation (PROMETHEE). In the proposed approach, an initial order of alternatives is gradually improved by swapping the order of a pair of alternatives until the decision-maker becomes satisfied. To validate the proposed method, we consider a case study of site selection for solar farms.

An integrated multiple layer perceptron-genetic algorithm decision support system for photovoltaic power plant site selection

There is a need for non-renewable energy sources in generation of power for almost every domestic and commercial purposes. This source of energy helps in the development of a country. Because of the increasing usage of the fossil fuels and depletion of these resources, our focus has been shifted towards the renewable sources of energy like solar, water and wind. Therefore, in the present scenario, the usage of renewable sources has been increasing rapidly. Selection of a solar power plant (SPP) requires environmental factor, local terrain, and local weather issues. Thus, a large amount of investment is required for installation. Multi-criteria decision making (MCDM) is a method that identifies one in choosing the best sites among the other proposed options. This paper gives a detailed study of optimal ranking of SPP site using analytical hierarchy process (AHP), multiple layer perceptron (MLP) neural network trained with back propagation (BP) algorithm and genetic algorithm (GA). Three SPP sites of India were considered and various important criteria like local weather, geographical location, and environmental factors are included in our study as SPP site selection is a multi-criteria problem. A precise comparison of these three methods is listed in this paper.

Application of choosing by advantages to determine the optimal site for solar power plants

Solar energy is a critical component of the energy development strategy. The site selection for solar power plants has a significant impact on the cost of energy production. A favorable situation would result in significant cost savings and increased electricity generation efficiency. California is located in the southwest region of the United States of America and is blessed with an abundance of sunlight. In recent years, the state's economy and population have expanded quickly, resulting in an increased need for power. This study examines the south of California as a possibly well-suited site for the constructing large solar power plants to meet the local electricity needs. To begin, this article imposed some limits on the selection of three potential sites for constructing solar power plants (S1, S2, and S3). Then, a systematic approach for solar power plant site selection was presented, focusing on five major factors (economic, technological, social, geographical, and environmental). This is the first time that the choosing by advantages (CBA) method has been used to determine the optimal sites for solar power plant construction, with the possible sites ranked as S2 > S1 > S3. The results were then compared with traditional methods such as the multi-criteria decision-making method. The findings of this study suggest that the CBA method not only streamlines the solar power plant site selection process but also closely aligns with the objectives and desires of the investors.

GIS BASED SOLAR POWER PLANTS SITE SELECTION USING ANALYTIC HIERARCHY PROCESS (AHP) IN ISTANBUL, TURKEY

Abstract. Today, countries are shifting their energy policies towards to renewable energy sources. The main reasons for this can be summarized as the reduction of fossil fuel resources, resulting in cost increase and their harmful effect on the ecological balance. Since renewable energy sources are both economical and eco-friendly, for countries which have high solar energy potential such as Turkey, it is reasonable to direct their energy policies to solar energy which is a renewable energy source.In this study, the development of renewable energy legislation in Turkey, from past to present has been examined and implementation steps for the licenced and unlicensed generation of electricity from solar energy have been introduced. Ten impact factors have been identified as the first step for the implementation of the solar power plant site selection in Istanbul, which was determined as the pilot region. Impact factors weighted using Analytical Hierarchy Process (AHP) method. Concurrently, the weights of these determined impact factors were compared with the weights obtained by evaluating the results of the “Evaluation of Solar Energy Power Plant Site Selection Factors” survey conducted during the study. After obtaining the weights, the relevant data were collected and the necessary analyses were performed with the help of the GIS software and the most suitable places were provided for the solar power plant for Istanbul.

A risk-based multi-criteria spatial decision analysis for solar power plant site selection in different climates: A case study in Iran

Identifying potential locations for installation of solar power plants is a critical step in utilizing sustainable energy resources. In this study, a GIS-based Multi-Criteria Decision Analysis (GIS-MCDA) technique is used to generate maps that represent potential areas for solar power plants in four provinces with different climate conditions in Iran. The concept of risk is included in the GIS-MCDA process using the Ordered Weighted Averaging (OWA) model. The OWA model can provide various risk-taking (optimistic) and risk-aversion (pessimistic) scenarios to determine the suitable power plant areas. The results of this study indicate that provinces located in an arid climate such as Yazd contain a more suitable area for the solar power plants compared to wet climate provinces (e.g., Mazandaran). The sensitivity analysis of results show that the criterion “fault” has the minimum effect while the criteria “slope” and “road network” have the maximum effects on the area of the highly desirable class.

A Decision Support System for Selection of Solar Power Plant Locations by Applying Fuzzy AHP and TOPSIS: An Empirical Study

The objective of this research is to propose a decision support system for avoiding flood on solar power plant site selection. Methodologically, the geographic information system (GIS) is used to determine the optimum site for a solar power plant. It is intended to integrate the qualitative and quantitative variables based upon the adoption of the Fuzzy Analytic Hierarchy Process (Fuzzy AHP) and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) model. These methods are employed to unite the environmental aspects and social needs for electrical power systematically. Regarding a case study of the choice of a solar power plant site in Thailand, it demonstrates that the quantitative and qualitative criteria should be realized prior to analysis in the Fuzzy AHP-TOPSIS model. The fuzzy AHP is employed to determine the weights of qualitative and quantitative criteria that can affect the selection process. The adoption of the fuzzy AHP is aimed to model the linguistic unclear, ambiguous, and incomplete knowledge. Additionally, TOPSIS, which is a ranking multi-criteria decision making method, is employed to rank the alternative sites based upon overall efficiency. The contribution of this paper lies in the evolution of a new approach that is flexible and practical to the decision maker, in providing the guidelines for the solar power plant site choices under stakeholder needs: at the same time, the desirable functions are achieved, in avoiding flood, reducing cost, time and causing less environmental impact. The new approach is assessed in the empirical study during major flooding in Thailand during the fourth quarter of 2011 to 2012. The result analysis and sensitivity analysis are also presented.