Multicriteria renewable energy planning using an integrated fuzzy VIKOR & AHP methodology: The case of Istanbul

The purpose of this study is twofold: first, it is aimed at determining the best renewable energy alternative for Istanbul by using an integrated VIKOR-AHP methodology. Second, a selection among alternative energy production sites in this city is made using the same approach. In the proposed VIKOR-AHP methodology, the weights of the selection criteria are determined by pairwise comparison matrices of AHP. In energy decision making problems, the judgments of decision makers are usually vague. As it is relatively difficult for decision makers to provide exact values for the criteria, the evaluation data for the alternative energy policies should be expressed in linguistic terms. In order to model this kind of uncertainty in human preferences, fuzzy logic is applied very successfully. Thus, both classical VIKOR and classical AHP procedures are performed under fuzzy environment. The originality of the paper comes from the application of the proposed integrated VIKOR-AHP methodology to the selection of the best energy policy and production site. It is found that wind energy is the most appropriate renewable energy option and Çatalca district is the best area among the alternatives for establishing wind turbines in Istanbul.     

Wind farm site selection from the perspective of sustainability: A novel satisfaction degree‐based fuzzy axiomatic design approach

As a clean and renewable energy resource, wind energy is the most mature, environmentally friendly, and most commercially developed new energy resource in the world. Therefore, it is of great importance to determine the best location of wind farms to ensure the sustainable development of wind energy. However, since wind farm site selection often involves multiple criteria, which include qualitative and quantitative criteria, there may be conflicts between these criteria, so wind farm site selection is a complex multi‐criteria decision‐making (MCDM) problem. Therefore, the objective of this study is to propose a novel integrated MCDM approach using a fuzzy analytic hierarchy process and satisfaction degree‐based fuzzy axiomatic design (AD) to determine the optimal onshore wind farm site under a hybrid decision information environment. First, based on the literature review and experts' opinion, the evaluation index system for wind farm site selection is built from a sustainable perspective, which includes geographic, technical, economic, social, and environmental criteria. Second, fuzzy analytic hierarchy process is applied to determine criteria weights. Third, the satisfaction degree‐based fuzzy AD is employed to evaluate and rank alternatives under a hybrid decision information environment. Finally, a case study is used to illustrate the reliability and advantages of the method proposed in this paper. In addition, the information content of each alternative is calculated by aggregating the evaluation matrix of experts, and the results are IC₁ = 0.058, IC₂ = 0.096, IC₃ = 0.16, IC₄ = ∞, IC₅ = ∞, and IC₆ = 0.226. Then the satisfaction degree of each alternative is S₁ = 0.629, S₂ = 0.545, S₃ = 0.501, S₄ = 416, S₅ = 389, and S₆ = 0.463. Thus, the best wind farm site is A₁. Moreover, the results show that the method proposed herein is flexible and can effectively deal with the wind farm site selection problem. Although this paper chooses China as a case study, the proposed method herein is also applicable to other countries or regions.     

Multidimensional evaluation of global investments on the renewable energy with the integrated fuzzy decision‐making model under the hesitancy

This study aims to assess global investment alternatives with respect to renewable energy. Within this framework, five different renewable energy types (biomass, hydropower, geothermal, wind, and solar) are determined as investment alternatives. Moreover, eight different criteria are selected by considering the four different dimensions of balanced scorecard. Additionally, the fuzzy‐based decision making trial and the evaluation laboratory under the hesitancy (HF‐DEMATEL) model are taken into the account to weight these dimensions and criteria and the technique for order the preferences by the similarity to the ideal solution with the fuzzy hesitant methodology (HF‐TOPSIS) is considered to select the alternatives of renewable energy investments. The novelties of this study are to propose an integrated model and provide the balanced scorecard–based evaluations of global renewable energy investment alternatives. The findings show that learning and growth and customer are the most important dimensions for the investment on renewable energy. It is also identified that market potential, product customization, and technological development are the most significant criteria for this situation. On the other side, solar and wind energy are the most important renewable investment alternatives. These results explain that technological improvement should be maintained, and customer expectations should be met by the companies. Furthermore, solar power plant and wind power plant should be developed in the countries. For this purpose, governments should give necessary incentives to the investors, such as allocating appropriate lands. These actions can attract the attentions of the potential investors for these renewable energy alternatives. Owing to this issue, it can be possible to increase the capacity of electricity productions in the countries with a potential minimum cost.     

A decision model for energy resource selection in China

This paper evaluates coal, petroleum, natural gas, nuclear energy and renewable energy resources as energy alternatives for China through use of a hierarchical decision model. The results indicate that although coal is still the major preferred energy alternative, it is followed closely by renewable energy. The sensitivity analysis indicates that the most critical criterion for energy selection is the current energy infrastructure. A hierarchical decision model is used, and expert judgments are quantified, to evaluate the alternatives. Criteria used for the evaluations are availability, current energy infrastructure, price, safety, environmental impacts and social impacts.     

Hydrogen energy storage method selection using fuzzy axiomatic design and analytic hierarchy process

This paper presents an integrated Fuzzy Analytical Hierarchy Process (fAHP) and Weighted Fuzzy Axiomatic Design (wfAD) methodology for a strategic level problem of hydrogen energy storage (HES) method selection for Turkey. Considering alternatives of tank, metal hydride and chemical storage, we design our decision problem with respect to five assessment criteria as weight, capacity, storage loss and leak, reliability, and total system cost. In the solution methodology, we first implement fAHP to determine criteria weights by incorporating linguistic judgement and vague information. Next, we define functional requirements and design parameters for the selection problem and use wfAD to compare alternatives. After implementing the proposed integrated approach, we perform additional sensitivity analysis experiments to test the robustness of the solution with respect to changes in functional requirements.     

Optimization of the photovoltaic-hydrogen supply system of a stand-alone remote-telecom application

Hydrogen is considered as the optimal carrier for the surplus energy storage from renewable resources. Although hydrogen and its application in fuel cell is considered as a high-cost energy system, some cost-efficient solutions have been found for their use in stand-alone applications, which usually depend on the variability of renewable sources that have to be oversized in order to reduce their dependence on external energy sources. This paper shows the results from the simulation of several alternatives of introducing hydrogen technologies to increase the independence of a remote-telecom application fed by photovoltaic panels. Hydrogen is obtained by electrolysis and it is used in a fuel cell when the renewable energy source is not enough to maintain the stand-alone application. TRNSYS simulation environment has been used for evaluating the proposed alternatives. The results show that the best configuration option is that considering the use of hydrogen as a way to storage the surplus of radiation and the management system can vary the number of photovoltaic panels assigned to feed the hydrogen generation, the batteries or the telecom application.     

Innovative methodologies in renewable energy: A review

This paper is concerned with innovative approaches to renewable energy sources computation methodologies, which provide more refined results than the classical alternatives. Such refinements provide additional improvements especially for replacement of fossil energy usages that emit greenhouse gas (GHG) into the atmosphere leading to climate change impact. Current knowledge gap among each renewable energy source calculation is rather missing fundamentals of plausible, rational, and logical explanations for the interpretation of results. In the literature, there are rather complicated and mechanically applicable methodologies, which require input and output measurement data match with missing physical explanations. The view taken in this review paper is to concentrate on quite plausible, logical, rational, and effectively applicable innovative energy calculation methodologies with simplistic fundamentals. For this purpose, a set of renewable energy methodological approaches is revisited with their innovative structures concerning solar, wind, hydro, current, and geothermal energy resources. With the increase in the renewable energy utilizations to combat the undesirable impacts of global warming and climate change, there is a need for better models that will include physical environmental conditions and data properties in the probabilistic, statistical, stochastic, logical, and rational senses leading to refined and more reliable estimations with application examples in the text. Finally, new research directions are also recommended for more refined innovative energy system calculations.     

Hybrid IT2 fuzzy modelling with alpha cuts for hydrogen energy investments

The framework of this study is to weight 8 selected determinants and rank energy alternatives for hydrogen investments. For this purpose, different criteria that are based on two dimensions are identified with supported literature and interval type-2 (IT2) fuzzy decision-making trial and evaluation laboratory (DEMATEL) with alpha cuts is considered to measure the significant criteria. Additionally, renewable and non-renewable energy alternatives are ranked regarding the appropriateness for hydrogen energy investments with the help of IT2 fuzzy technique for order preference by similarity to ideal solution (TOPSIS) and IT2 fuzzy Vlse Kriterijumska Optimizacija Kompromisno Resenje (VIKOR) with alpha cuts. It is concluded that the weights of the criteria are quite similar for different alpha cuts. Also, ranking results of different energy alternatives are almost the same for both IT2 fuzzy TOPSIS and IT2 fuzzy VIKOR. Thus, it can be concluded that the analysis results are reliable and coherent. The principal results indicate that cost-efficiency and reserve adequacy play a key role in hydrogen investments since they have the highest weight (0.129). Moreover, it is also found that technological capacity also plays a critical role in this regard with the weight of 0.127. However, legal regulation has the lowest importance weight (0.121) in comparison with other factors. Additionally, the weights of personnel competency (criterion 3) and storage (criterion 4) are also low (0.122). The major conclusion show that renewable energy alternatives are more suitable to generate hydrogen energy in comparison with non-renewable ones. Within this context, it is identified that solar and geothermal energies are more appropriate alternatives for hydrogen production whereas coal and nuclear are on the last rank. Hence, the main strategy should be lowering the costs by following up-to-date technological developments. Another important issue is that it becomes more logical to produce hydrogen in renewable energy sources that will not be consumed forever so that sustainable production of the hydrogen can be provided.     

Developing a framework for renewable technology portfolio selection: A case study at a R&D center

The rapid development of technologies, their increasing complexity and variety, long lead times of R&D and market dynamics have made the task of technology selection difficult. Considering high level of competitiveness, organizations need to strategically allocate their limited resources to the best subset of possible projects.Today, the increased consumption of energy in modern industrial societies, in addition to the risk of quick exhaustion of fossil resources, has brought about irreversible and threatening environmental changes faced by the world. Dealing with these challenges, decision makers focus on the development of renewable energy technology viewed both as a process of diversification of energy sources and as a creation of an alternative energy option that will help curb down global climate change.To successfully tackle investment projects in renewable energy, it is essential to use models facilitating decision making process and guarantying the greatest possible value for organizations. Technology portfolio managers have traditionally used consensus-based tools, such as Analytical Hierarchy Process (AHP), Delphi but these tools are limited in their ability to fully quantify the impact of technology portfolio selection on the overall aspects of the system.This paper presents the results of developing a mathematical model for renewable technology portfolio selection at an oil industry R&D center maximizing support of the organization's strategy and values. The model balances the cost and benefit of the entire portfolio. It is also flexible and changes can be applied very easily.     

Analysis of the assessment factors for renewable energy dissemination program evaluation using fuzzy AHP

By 2030, Korean government aims to increase the share of new and renewable energy sources to 11% in the overall primary energy mix, that is, approximately 33 million TOE. However, carefully designed program is needed given the current low level of the share (2.37%, approximately 5.6 million TOE, as of 2007). Therefore, alongside R&D on new and renewable energy technology, establishing an effective dissemination program is also essential. This would require a decision-making base, for which this study established the criteria and factors and assessed the importance of each factor using the fuzzy analytical hierarchy process (AHP) method. Five criteria – technological, market-related, economic, environmental, and policy-related – and a total of seventeen factors were established. From the weights estimation results, we derived four major conclusions regarding the importance of economic feasibility, the advancement of the target technology in the global market, the disagreement between the policy maker and the specialist group, and the application of the results.     

Sustainable energy planning decision using the intuitionistic fuzzy analytic hierarchy process: choosing energy technology in Malaysia

Energy consumption for developing countries is sharply increasing due to the higher economic growth due to industrialisation along with population growth and urbanisation. The increasing demand of energy leads to global energy crisis. Selecting the best energy technology and conservation requires both quantitative and qualitative evaluation criteria. The fuzzy set-based approach is one of the well-known theories to handle fuzziness, uncertainty in decision-making and vagueness of information. This paper proposes a new method of intuitionistic fuzzy analytic hierarchy process (IF-AHP) to deal with the uncertainty in decision-making. The new IF-AHP is applied to establish a preference in the sustainable energy planning decision-making problem. Three decision-makers attached with Malaysian government agencies were interviewed to provide linguistic judgement prior to analysing with the new IF-AHP. Nuclear energy has been decided as the best alternative in energy planning which provides the highest weight among all the seven alternatives.     

Energy for the future: An integrated decision aid for the case of Turkey

Environmental concerns and the increase in oil prices in the fall of 2000 made energy one of the priority issues in the industrial world. Research shows that the problem of selecting an energy resource requires a detailed multi-dimensional analysis. Most forms of renewable energy are dependent on geographic and environmental factors that vary immensely from place to place. As a result, each country has to work out its own policies in accordance with its geographical and political conditions. This paper is concerned with the multi-attribute decision making evaluation of energy resources that will enable the selection of a suitable electricity generation alternative for Turkey. It also provides an integrated decision aid (IDEA) framework for the selection of the most suitable multi-attribute method and presents ranking of alternatives and robustness analysis as recommendation to the authorities.     

半结构多目标模糊优选理论在确定工程治涝标准中的应用

在区域除涝规划设计阶段,关键是要选择出合理的除涝工程标准。在选择的过程中,要考虑定量因素和定性因素。为协调各因素之间的复杂关系,提出将层次分析法和多目标模糊优选理论相结合,建立除涝工程标准方案多目标决策模型。运用层次分析法建立指标层次模型,根据不同决策人的偏好确定相应的指标权向量,在此基础上使用多目标模糊优选模型求解各方案最优相对隶属度,以确定最佳方案。经实例分析表明,该模型在确定区域除涝工程标准中具有重要的应用价值与现实意义,能为最后的总决策提供较为客观公正的依据。     

Planning of community-scale renewable energy management systems in a mixed stochastic and fuzzy environment

In this study, an interval-parameter superiority–inferiority-based two-stage programming model has been developed for supporting community-scale renewable energy management (ISITSP-CREM). This method is based on an integration of the existing interval linear programming (ILP), two-stage programming (TSP) and superiority–inferiority-based fuzzy-stochastic programming (SI-FSP). It allows uncertainties presented as both probability/possibilistic distributions and interval values to be incorporated within a general optimization framework, facilitating the reflection of multiple uncertainties and complexities during the process of renewable energy management systems planning. ISITSP-CREM can also be used for effectively addressing dynamic interrelationships between renewable energy availabilities, economic penalties and electricity-generation deficiencies within a community scale. Thus, complexities in renewable energy management systems can be systematically reflected, highly enhancing applicability of the modeling process. The developed method has then been applied to a case of long-term renewable energy management planning for three communities. Useful solutions for the planning of renewable energy management systems have been generated. Interval solutions associated with different energy availabilities and economic penalties have been obtained. They can be used for generating decision alternatives and thus help decision makers identify desired policies under various economic and system-reliability constraints. The generated solutions can also provide desired energy resource/service allocation plans with a minimized system cost (or economic penalties), a maximized system reliability level and a maximized energy security. Tradeoffs between system costs and energy security can also be tackled. Higher costs will increase potential energy generation amount, while a desire for lower system costs will run into a risk of energy deficiency. They are helpful for supporting: (a) adjustment or justification of allocation patterns of renewable energy resources and services, (b) formulation of local policies regarding energy utilization, economic development and energy structure under various energy availabilities and policy interventions, and (c) analysis of interactions among economic cost, system reliability and energy-supply shortage.     

Renewable energy supply chains,performance, application barriers,and strategies for further development

Due to the depletion of traditional energy resources, such as crude oil, coal, and natural gas, many initiatives all over the world have addressed the efficient use or replacement of these resources. Several renewable energy sources have been introduced as alternatives to traditional sources to protect environmental resources and to improve the quality of life. This study assesses renewable energy sources from a supply chain perspective and presents an investigation of renewable energies focusing on four main components: renewable energy supply chain, renewable energy performance, and barriers and strategies to its development. The study provides managerial insights to governments, researchers, and stakeholders for the initiation of renewable energy use, and suggestions for overcoming the barriers to its development.     

Genetic fuzzy rule extraction for optimised sizing and control of hybrid renewable energy hydrogen systems

A major challenge related to the design of a hybrid renewable energy hydrogen system is which energy sources to include and at what capacity, for regionally different potentials of renewable energy and hydrogen demand. In addition, once the plant is in operation, control variables need to be optimised. The problem resorts to an area of multiple criteria decision making referred to as multi-objective optimisation. The results obtained from these type of algorithms include not only one optimal solution, but a set of optimal solutions (Pareto front) thereby offering a system designer several options. This set of solutions can be hard to interpret and a method is needed to automatically extract useful design and control strategies from this information. A methodology that is quite successful in deriving human interpretable rules from this type of information is genetic fuzzy systems. In this work a k-means clustering algorithm is used to generate membership functions and a fuzzy rule-base is trained by means of a genetic algorithm. The genetic fuzzy system obtained is reduced by determining the minimum number of rules followed by a membership function reduction process. The reduced genetic fuzzy system is deemed more interpretable. Geographic weather data from three different sites are used to generate data to be used in the genetic fuzzy method. Results show that the technique provides valuable information that can be used for the design of such hybrid renewable energy hydrogen production systems.     

Investigation of solar energy utilization for production of hydrogen and sustainable chemical fertilizer: A case study

Renewable energies play a vital role in the economic and social development and progress of many countries. As one of the most significant sources of renewable energy, solar energy has been used due to its availability in many regions. Generating electricity for hydrogen production is one of the applications of solar energy. In petrochemical complexes, hydrogen is often used for producing fertilizers, especially urea fertilizers. The present study aims at investigating five major Iranian petrochemical complexes in terms of their suitability for the construction of a solar plant to produce electrolysis‐based green chemical fertilizers. To this end, a multicriteria decision‐making model is proposed, which includes the fuzzy analytic hierarchy process (AHP) and extended TODIM method of multicriteria decision making (including crisp, interval, and fuzzy numbers). The present research investigates 10 criteria for prioritizing petrochemical complexes, classified into four general categories, namely, climatic, geographic, environmental, and probability of natural disaster occurrence categories. Having calculated the weight of the criteria using the fuzzy AHP method, the alternatives are prioritized using the extended TODIM method. The methods of simple additive weighting (SAW), Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), and VIKOR were then used for validation of the results. Results showed that the Shiraz Petrochemical Complex has the highest priority and Khorasan Petrochemical Complex has the lowest priority for producing green fertilizer via solar energy–assisted water electrolysis. By using the solar system, Shiraz Petrochemical Complex can emit over 1900 tons less pollutants in the environment per day and provides up to 8% of its annual total production through clean energy.     

New maximum power point tracker for PV arrays using fuzzy controller in close cooperation with fuzzy cognitive networks

The studies on the photovoltaic (PV) generation are extensively increasing, since it is considered as an essentially inexhaustible and broadly available energy resource. However, the output power induced in the photovoltaic modules depends on solar radiation and temperature of the solar cells. Therefore, to maximize the efficiency of the renewable energy system, it is necessary to track the maximum power point of the PV array. In this paper, a maximum power point tracker using fuzzy set theory is presented to improve energy conversion efficiency. A new method is proposed, by using a fuzzy cognitive network, which is in close cooperation with the presented fuzzy controller. The new method gives a very good maximum power operation of any PV array under different conditions such as changing insolation and temperature. The simulation studies show the effectiveness of the proposed algorithm.