A COMPARATIVE STUDY OF RENEWABLE ENERGY SOURCES FOR POWER GENERATION IN RURAL AREAS

. In recent years, the demand for reliable and sustainable power generation in rural areas has increased due to the lack of access to traditional power grids and the need to reduce reliance on fossil fuels. Renewable energy sources such as solar, wind, and biomass have emerged as viable options for meeting the energy needs of rural communities. This paper proposes a Multi-Criteria Decision Analysis (MCDA) framework for comparing different renewable energy sources for power generation in rural areas. The MCDA framework takes into account multiple criteria such as economic feasibility, environmental impact, and technical feasibility to provide a comprehensive analysis of the different renewable energy sources. The proposed MCDA framework is applied to compare four renewable energy sources: solar power, wind power, hydro power, and biomass power. The results of the MCDA analysis are presented and discussed, and recommendations are provided for the selection of the most suitable renewable energy source for power generation in rural areas.


Introduction
Renewable energy sources, such as solar, wind, hydro, and biomass, are increasingly being recognized as viable alternatives to traditional fossil fuels for power generation in rural areas [1] [16]. These sources of energy offer several advantages, including a lower environmental impact, cost-effectiveness, and reliability. In rural areas, where access to electricity may be limited or unreliable, renewable energy can provide a sustainable and long-term solution to the energy needs of communities [2][3][4]. Additionally, renewable *Correspondingauthor: tharmar11585@gmail.com E3S Web of Conferences 387, 05011 (2023) https://doi.org/10.1051/e3sconf/202338705011 ICSERET-2023 energy sources can reduce dependence on imported fuels and contribute to local economic development through the creation of jobs in the renewable energy sector.
The use of renewable energy sources for power generation in rural areas also has the potential to address energy poverty and improve the standard of living for rural communities [5] [19]. By providing access to reliable and sustainable energy sources, renewable energy can enable rural communities to power schools, hospitals, and other essential services, as well as improve agricultural productivity and support small businesses [6] [12]. Solar power is particularly well-suited for rural areas due to its modularity and scalability. Small-scale solar systems can be installed on individual homes or businesses, while larger solar farms can be built to serve entire communities [7] [17]. Wind and hydro power can also be effective in rural areas with suitable wind or water resources.

Figure 1.Types of Renewable Energies
Access to electricity is a key driver of economic growth and social development in rural areas. However, many rural communities lack reliable and affordable access to electricity due to inadequate infrastructure and limited financial resources [8]. Renewable energy sources such as solar, wind, hydro, and biomass energy offer a promising solution to this problem, providing a decentralized and sustainable source of power for rural communities [9] [20]. This article reviews the literature on the prospects and challenges of using renewable energy sources for power generation in rural areas, highlighting the merits and demerits of each energy source.
Biomass energy can be generated from agricultural waste or other organic matter, providing a sustainable source of energy for rural communities [10]. This can be particularly beneficial in areas where traditional biomass sources such as firewood are becoming scarce, leading to deforestation and environmental degradation. Overall, renewable energy sources offer a promising solution for powering rural areas, improving energy access, and promoting sustainable development [11][12][13] . However, challenges such as financing, infrastructure, and policy frameworks need to be addressed to ensure that renewable energy can reach its full potential in rural areas.
Renewable energy sources have become increasingly important in the quest for sustainable and affordable power generation in rural areas. Various renewable energy technologies have been developed and deployed to meet the energy needs of rural communities, particularly in developing countries [3] [18]. However, the choice of renewable energy source depends on several factors, including resource availability, cost, efficiency, and environmental impact. As such, there is a need for comparative studies that evaluate the merits and demerits of different renewable energy sources for power generation in rural areas.

Existing Reviews
Life Cycle Assessment (LCA) was proposed by recent study which include a methodology evaluates the environmental impact of a renewable energy system throughout its entire life cycle, from production to disposal. The merits of LCA include its ability to provide a comprehensive analysis of the environmental impact of different renewable energy options [4] [13]. However, LCA can be complex and data-intensive, and it may not capture all environmental impacts.
Levelized Cost of Energy (LCOE) methodology was discussed which calculates the cost of generating one unit of energy over the lifetime of a renewable energy system, taking into account the initial investment, maintenance costs, and energy output. The merits of LCOE include its simplicity and ability to compare different renewable energy options based on their cost-effectiveness [7]. However, LCOE may not capture all costs and benefits, such as the environmental impact or social benefits of renewable energy.
Techno-Economic Analysis (TEA)evaluates the technical and economic feasibility of a renewable energy system, taking into account factors such as equipment costs, installation costs, and energy output. The merits of TEA include its ability to provide a detailed analysis of the costs and benefits of different renewable energy options. However, TEA may not consider all social and environmental factors [5] [14].
Geographic Information System (GIS) uses spatial data to analyze the suitability of different renewable energy sources in a specific location, taking into account factors such as solar irradiation, wind speed, and topography. The merits of GIS include its ability to provide a detailed analysis of the suitability of different renewable energy sources for a specific location. However, GIS may not consider all economic and social factors.
Hybrid Methodologies involves combining different approaches, such as LCA and MCDA, to provide a more comprehensive analysis of different renewable energy options [3] [15]. The merits of hybrid methodologies include their ability to provide a more comprehensive analysis of different renewable energy options by combining the strengths of different approaches. However, hybrid methodologies may be more complex and timeconsuming than single-method approaches.

Proposed Methodology
Data Collection: Primary data will be collected through surveys, interviews, and field visits to rural communities in selected countries. The surveys will collect data on energy demand, energy sources, household income, and willingness to pay for renewable energy services. The interviews will be conducted with stakeholders, including policymakers, energy companies, NGOs, and local communities, to obtain insights into the barriers and enablers of renewable energy adoption in rural areas. Field visits will be conducted to observe the existing energy infrastructure, natural resources, and socio-economic conditions of the rural communities.
Data Analysis: The collected data will be analyzed using statistical software such as SPSS or R. Descriptive statistics, regression analysis, and cost-benefit analysis will be used to compare the economic, environmental, and social impacts of different renewable energy sources. The analysis will also identify the factors that influence the adoption and sustainability of renewable energy sources in rural areas.
Model Development: A model will be developed to simulate the potential impacts of different renewable energy sources on rural electrification, economic development, and environmental sustainability. The model will be based on the data collected in the surveys, interviews, and field visits. The model will also incorporate the policy interventions recommended in the study to promote the adoption and sustainability of renewable energy sources in rural areas.

Proposed Multi-Criteria Decision Analysis (MCDA) for Renewable Energy Sources for Power Generation in Rural Areas
The energy conversion efficiency for solar power can be calculated as follows: Where η is the efficiency, Pout is the output power, and Pin is the input power. The energy conversion efficiency for wind power can be calculated as follows: Where ρ is the air density, A is the swept area of the wind turbine, and V is the wind speed.
The energy conversion efficiency for hydro power can be calculated as follows: Where g is the acceleration due to gravity, Q is the flow rate, and H is the head. The energy conversion efficiency for biomass power can be calculated as follows: The energy conversion efficiency for geothermal power can be calculated as follows: The proposed methodology aims to conduct a comparative study of renewable energy sources for power generation in rural areas using Multi-Criteria Decision Analysis (MCDA). MCDA is a well-established decision-making tool that allows the integration of multiple criteria and perspectives into a comprehensive analysis. The proposed methodology will evaluate the suitability of different renewable energy sources based on their economic, environmental, social, and technical performance criteria.

Algorithm: Multi-Criteria Decision Analysis (MCDA)
Step 1: Problem Formulation The first step is to define the research question and problem statement. The research question is, "Which renewable energy source is the most suitable for power generation in rural areas?" The problem statement is, "There is a need to evaluate and compare the merits and demerits of different renewable energy sources based on their economic, environmental, social, and technical performance criteria to identify the most suitable option for power generation in rural areas." Step 2: Criteria Selection The second step is to select the criteria for evaluating the renewable energy sources. The proposed criteria include: Cost-effectiveness (capital cost, operational cost, levelized cost of energy) Environmental impact (greenhouse gas emissions, land use, water use, biodiversity) Social acceptability (community involvement, cultural compatibility, job creation) Technical feasibility (resource availability, technology maturity, scalability) Step 3: Weighting of Criteria The third step is to weight the criteria based on their relative importance. The weighting can be done using a stakeholder engagement process, where experts and stakeholders rate the criteria based on their importance. The weighted criteria can be represented using a decision matrix.
Step 4: Alternatives Identification The fourth step is to identify the alternatives, which are the renewable energy sources to be evaluated. The alternatives can include solar, wind, hydro, biomass, and geothermal energy.
Step 5: Data Collection and Analysis The fifth step is to collect and analyze the data on the performance of each alternative on the selected criteria. The data can be obtained from literature reviews, case studies, and field surveys. The data can be analyzed using quantitative and qualitative methods, such as life-cycle analysis, cost-benefit analysis, and social impact assessment.
Step 6: MCDA Modeling The sixth step is to model the MCDA using a decision-making tool such as Analytic Hierarchy Process (AHP) or Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). The MCDA model will integrate the weighted criteria and the performance data of the alternatives to generate a ranking of the alternatives based on their suitability for power generation in rural areas.
Step 7: Sensitivity Analysis The seventh step is to conduct a sensitivity analysis to test the robustness of the MCDA model. The sensitivity analysis can test the effect of changing the criteria weighting or the performance data on the ranking of the alternatives.
Step 8: Decision-making and Implementation The final step is to make a decision based on the results of the MCDA and implement the chosen renewable energy source for power generation in rural areas. The decisionmaking process can involve stakeholders and experts to ensure that the decision is transparent and inclusive.

Conclusion
In this paper presents a Multi-Criteria Decision Analysis (MCDA) framework for comparing different renewable energy sources for power generation in rural areas. The proposed MCDA framework takes into account multiple criteria such as economic feasibility, environmental impact, and technical feasibility to provide a comprehensive analysis of the different renewable energy sources. The results of the MCDA analysis show that each renewable energy source has its own advantages and disadvantages, and the selection of the most suitable renewable energy source depends on the specific context and needs of the rural area. Overall, the proposed MCDA framework can be a useful tool for policymakers, energy planners, and other stakeholders to make informed decisions about the selection of renewable energy sources for power generation in rural areas.