An integrated multi-objective decision model for renewable energy planning

It is difficult to meet the increased energy demand with fossil-based fuels, due to their limited reserves. Awareness of environmental issues, depleting fossil fuel resources, the precarious nature of dependency on fossil fuel/oil imports laid the foundation for the recent interest in the exploitation of renewable energy sources. Renewable energy is deemed to be clean, sustainable, cost-effective, reliable and environmental friendly, and hence can be relied on for the long-term. The most important feature of renewable energy sources is their environmental suitability. Therefore they are needed for sustainable energy planning. Renewable energy sources play an important role in countries' energy policies in terms of ensuring energy security, energy independence, and achieving environmental concerns according to international agreements such as the Kyoto Protocol. According to the International Energy Agency (IEA), one quarter of the world's energy consumption will be supplied from renewable energy sources in 2020. Increased energy needs are planned to be provided from renewable energy sources in accordance with long-term energy investments and energy policies. The energy consumption of Turkey shows a continuous increase in parallel with the growth of population, industrialization, and urbanization. More specifically, according to electricity demand projections Turkey's electricity consumption will increase by nearly two times in less than 15 years. Therefore, it is strategically important that energy demand projections should be implemented accurately and optimally. In order to respond to such a large increase in demand, it is necessary to understand demand, to make accurate demand projections and to establish investment plans accordingly. Turkey is known as a country blessed with great potential for renewable energy with its suitable climate and geological position. These advantages not only facilitate but also incentivize Turkish authorities for investment in sustainable and renewable energy sources. Hence, effective utilization of various potential renewable energy sources is among the strategies published by the Turkish Republic of Ministry of Energy and Natural Resources (MENR). Energy planning is a complex managerial practice involving various interrelated processes, such as energy generation, delivery, and distribution, while striving to meet the goals of different stakeholders. It is difficult to deal with such complex and multidimensional energy problems. In energy planning, all benefits and losses should be balanced while policy makers and decision makers/managers in the energy sector create an efficient energy supply chain mechanism. Multi-objective decision making approaches can provide effective results by simultaneously satisfying multiple and often conflicting objectives. In this study, a renewable energy investment planning model is proposed using an integrated multi-objective decision making approach. The proposed optimization model attempts to improve multiple conflicting objectives such as total electricity production cost, the distance between electricity production and consumption regions, renewable energy potential, socio-environmental impact factor and the avoided of carbon emissions with a consideration of long-term sustainable energy goals. In this study, it is expected that the existing renewable energy resource potential is utilized at a maximum level and the idle sources are evaluated and brought into the national economy. The developed model evaluates the energy resources within the technical, economic, social and environmental perspectives, which created a resource optimization model with the application of the case on Turkey that has 21 electricity distribution regions. The majority of energy planning studies in the literature investigate fossil energy sources, or fossil and renewable energy sources together in a comparative fashion. The number of studies focusing solely on renewable energy sources and their collective advantages is still limited, despite the recent increase in the interest and related research in this area. The limited number of studies in renewable energy planning focused on individual regions and/or countries other than Turkey. As energy planning models are developed to reflect the characteristics of a particular region/country, they can vary considerably depending on the diversity of local sources, policies and the views of local communities on renewable energy plants (social acceptance factor). The study aims to enrich the field with a comprehensive analysis of Turkey's renewable energy strategy. In fact, it is very difficult to access all of the unique characteristics that exist at granular levels in developing countries, such as Turkey. The collective use of multiple data/information sources was an added enabler of this study. In the first part, Turkey's energy sector was evaluated and then the alternative energy strategies were created. According to results, increasing the share of renewable energy sources in energy supply was emerging as an important strategy. Then, Turkey's electricity needs emerging in 2023 (short term), in 2030 (medium term) and in 2050 (long-term), was forecasted using traditional approaches, artificial intelligence methods, and hybrid approaches. When methods were compared in terms of prediction accuracy, it was observed that the hybrid Holt-Winters-Genetic algorithm method developed using with MATLAB software, and the support vector regression, which was a successful machine learning method, performed better. The demand information obtained from this method was used as the electrical demand of regions in the developed mathematical model. In this study, evaluations were carried out via interviews with the authorities from the leading institutions and organizations in the energy sector. Then, the socio-environmental impact factor was calculated using the Hesitant Fuzzy TOPSIS method. The fuzzy sets approach has been chosen because it provides successful results in making the evaluation with the linguistic term within an indefinite and restricted set of data. The accurate determination of the weights of the objectives (i.e., importance levels) in the multi-objective decision making model directly affects the solution and all of the subsequent derivations. Due to such sensitiveness and serious impacts of the weights of the determined objectives on the model, the weights were determined/calculated using the Analytical Hierarchy Process method. The developed multi-objective mixed integer linear programming model was solved by the CPLEX solver of GAMS software using the compromise programming method. The model consistency was tested with sensitivity analysis and scenario analyses, and the model was observed to yield successful results. According to the extant literature, there is no such comprehensive renewable energy investment planning model at a country level that has been developed according to a multi-stage hybridized methodology (which integrates demand forecasting, fuzzy sets theory and multi-criteria/objective decision-making approaches) to achieve sustainability goals. The proposed multi-objective decision model offers decision makers a deterministic and integrated tool based on scientific methods to assist in making strategic decisions on matters associated with the planning of energy resources in Turkey.