Plant Site Selection Research Articles

The waste-to-energy incineration plant site selection based on hesitant fuzzy linguistic Best-Worst method ANP and double parameters TOPSIS approach: A case study in China

The waste-to-energy (WTE) project can handle the expanding volume of municipal solid waste (MSW) and promote the development of the circular economy, effectively. To achieve sustainable MSW management, it is pivotal to select a promising WTE incineration plant site. Thus, this paper aims to propose a novel methodology for selecting the optimal WTE incineration plant site. A sustainable evaluation index system is constructed from the environment, economy, society, risk, and energy aspects. Evaluation criteria are articulated by mathematical models and hesitant fuzzy linguistic term set, respectively. Given interactional relations among criteria and computation efficiency, HFL-BWM-ANP (hesitant fuzzy linguistic Best-Worst method-Analytic Network Process) is proposed to obtain criteria weights. The double parameters TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) approach is employed to rank alternative sites. The feasibility of the proposed methodology is illustrated by a numerical case. Triple sensitivity analysis and comparative analysis are performed to demonstrate the robustness, effectiveness, and superiority of the proposed methodology. Some managerial insights are provided from multiple dimensions for investors and the government to implement the WTE incineration plant project.

Calculation of the real daily and monthly mean working temperature of a photovoltaic plant

AbstractAccurately predicting the production of a photovoltaic (PV) plant is essential to its economic evaluation. Ambient temperature is a major environmental factor affecting how much power a PV plant generates. However, weather bureaus in most developing countries can only provide the daily or monthly mean ambient temperatures, rather than the real mean working temperature in the vicinity of the PV plant. Moreover, the difference between the real daily or monthly mean working temperature and the corresponding daily or monthly mean temperature is large in the Gobi, desert, and Qinghai‐Tibet Plateau, causing some errors in some present PV power predictive models. Using Datafit 9.0 software in this paper, regression equations were created for Beiluhe (Qinghai‐Tibet Plateau) and Desert Knowledge Australia Solar Centre (DKASC) (desert) data relating the difference of the real daily or monthly mean working temperature and the corresponding mean temperature (Y factor) as well as the daily or monthly temperature difference (X factor). One general equation: Td10d = 1.290 + 0.475 × Tdmm − 1.331 × Tdmm0.5 (Equation 6) could represent all of the regression equations obtained from the Beiluhe and DKASC data. These basic findings are valuable for improving accuracy of present PV power predictive model by including the daily or monthly mean air temperature. Another, the research result will be helpful for PV plant site selection and evaluation.

A robust decision making approach for hydrogen power plant site selection utilizing (R, S)-Norm Pythagorean Fuzzy information measures based on VIKOR and TOPSIS method

In recent years, there is a rapid development in the direction of hydrogen energy industry having primary involvement in automobile transportation fuel. Hydrogen is the most abundant element and serves as a perfect energy carrier. In general, choosing an appropriate hydrogen power plant site is a complex selection multi-criteria decision making (MCDM) problem which involves proper assessment of a location based on various essential criteria, decision maker's expert opinion and other qualitative/quantitative factors. In the present communication, we first incorporate (R,S)-Norm Pythagorean fuzzy entropy and respective discriminant measure in the VIseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) MCDM techniques and proposed the modified MCDM algorithms in two different stages. Further, the hydrogen power plant site selection problem has been dealt with proper matching of the laid down essential criteria under a wider sense of Pythagorean fuzzy information measures. Such measures have not been utilized in the study of site selection problems of the hydrogen energy resources. In view of the existing literature on the MCDM problems, comparative remarks including the sensitivity analysis and the advantages have been presented for providing the novelty of the proposed methodologies. The presented work proves to be an effective tool for handling the various similar types of selection problems with a desired consistency.

A Multi-Criteria Decision Support Framework for Inland Nuclear Power Plant Site Selection under Z-Information: A Case Study in Hunan Province of China

To promote the development of nuclear power project in inland China, a specialized multi-criteria decision support framework is constructed for the site selection of inland nuclear power plants in this work. The best worst method (BWM), decision-making trial and evaluation laboratory (DEMATEL), and technique for order performance by similarity to ideal solution (TOPSIS) are integrated with Z-numbers, namely Z-BWM, Z-DEMATEL, and Z-TOPSIS. Z-BWM and Z-DEMATEL are combined to produce the weights of criteria, and an extended Z-TOPSIS is utilized to determine the ranking of all alternatives. Finally, a case study is performed in Hunan province to demonstrate the practicability of the proposed decision support framework. The robustness and feasibility of the proposed method are shown by an in-depth analysis of the decision results.

A two‐stage decision framework for inland nuclear power plant site selection based on GIS and type‐2 fuzzy PROMETHEE II: Case study in China

AbstractSite selection is a critical strategic decision for inland nuclear power plants which have broad prospects of development. However, several shortcomings exist in current researches, such as the incomplete decision frameworks, the indiscriminately treated properties, and the information loss. To handle the above flaws, this study establishes a two‐stage site selection framework. In the first stage, the geographic information system and preselection criteria are applied to identify suitable alternative sites. And in the second stage, the interval type‐2 fuzzy PROMETHEE II and suitability criteria are utilized to rank alternatives and select the optimal site, where different preference functions are selected accordingly. Thereinto, the interval type‐2 fuzzy numbers are adopted to describe the uncertainty and vagueness in calculation, without being transformed to exact value. Finally, based on the proposed two‐stage decision framework, a case of Hunan, Hubei, and Jiangxi provinces is studied, to demonstrate its validity and practicability. The results show that S8 is selected as the optimal site for its strong government support, convenient fuel transport, and land availability. This study not only enriches the material databases for inland nuclear power plant site selection, but also offers theoretical reference for site selection studies of various objects.

Mineral processing plant site selection using integrated fuzzy cognitive map and fuzzy analytical hierarchy process approach: A case study of gilsonite mines in Iran

Selecting the most suitable location for a mineral processing plant is of vital importance for achieving the highest throughput and lowering overall costs. The aim of the research is to select the best location for a gilsonite processing plant (Kermanshah Province, Iran). First, laboratory scale concentration experiments were conducted to determine the most suitable concentration technique for the material from all gilsonite mines nearby. It was concluded that, one production line is enough to concentrate of the material from all mines by flotation method. Afterwards, the effective criteria for locating the processing plant were identified as processing, facilities and infrastructure, mining, environmental, geographical, social and cultural, legal, geological and finally technical and technological factors. Considering the multiplicity of effective factors and interactions between them, fuzzy cognitive map (FCM) method is used for ranking of the factors. A survey for the evaluation of each factor was conducted through interviewing a number of experts in various mining engineering fields. Then, the FCM method was used to determine the weights of each factor. The results show that distribution of mines is the most important factor. In order to determine the appropriate site for installation of the plant, 4 sites were selected in the vicinity of larger mines by investigating the geological maps, using Geological Information System (GIS), aerial photos and objective visits. In order to obtain the global weights of alternatives, the local weights obtained from FCM and FAHP methods were combined. According to the results, site No.4, located at longitude 34˚ 18′28″ and latitude 45˚ 41′ 49″ was proposed as the best location.

Proposal of a novel mixed integer linear programming model for site selection of a wind power plant based on power maximization with use of mixed type wind turbines

Several methods that have been developed to obtain energy, which is indispensable for life and whose necessity has increased geometrically in the course of time, are no longer sustainable. Therefore, human being has headed towards sustainable alternative energy sources. Wind has been one of the most interested renewable energy sources for human as of the beginning of the 20th century. This study focuses on one of the most important work items at the establishment phase of this important energy source, power plant site selection. Within the scope of linear programming perspective, two models were presented based on mixed integer linear programming. The first model provides employment of single-type wind turbine on the selected site, whereas the second model, which was developed within the current study, aims additional increase in total power output by allowing employment of multiple-type wind turbine on the selected site. The same region showed up as the most appropriate site to establish wind power plant as a result of both models of the study.

Land Suitability Determination of NPP’s Potential Site in East Kalimantan Coastal Using GIS

Nuclear Power Plant (NPP) site selection is the key phase of the nuclear power plant process and significantly influence the construction cost and safety. In order to prepare for nuclear power programs in East Kalimantan province, Geographical Information System (GIS) analysis along the coast of East Kalimantan province, especially the Berau district, East Kutai, Kutai Kartanegara, Samarinda, Balikpapan, Penajam Paser Utara and the Paser. The research purpose is to find suitable site for nuclear power plants location using spatial analysis and modeling. The potential Nuclear Power Plant (NPP) site is based on several criteria, such as: geology, slope, soil type, land use, hydrology, and existing road network. Based on the weighting and ranking results using GIS application: there are three locations serve as the potential NPP sites are obtained Kutai Kartanegara and Kutai Timur regency. Next, land suitability analysis is done by using GIS application which shows potential sites suitable general and specific criteria of the site evaluation process development.

Evaluating optimal sites for combined-cycle power plants using GIS: comparison of two aggregation methods in Iran

ABSTRACTThis study aims to use an integration of GIS and multi-criteria evaluation for combined-cycle power plant site selection and compares two aggregation methods for Iran. The information layers of the criteria are prepared in the GIS environment and then the layers standardised using fuzzy functions in IDRISI. All layers are combined using two conventional methods of fuzzy logic and weighted linear combination; from this information, the suitability maps were created. Results show that only 2.0% of the region under study is scored high-suitable using the fuzzy logic, while 21% of the area is considered as highly suitable when the weighted linear combination is used. Despite this significant difference, both approaches recommend the ideal place in the north and northwest of the study area. In conclusion, integrating GIS and multi-criteria evaluation is a comprehensive approach that improves and strengthens the suitability of site selection studies.

Integrated multi-criteria decision making methodology for pumped hydro-energy storage plant site selection from a sustainable development perspective with an application

Pumped hydro-energy storage (PHES) development involves heavy investment with stringent environmental and social requirements. Therefore, selecting the best site is a key influencer of the plant's ability to sustainably provide the expected benefits throughout its whole lifecycle. An important contribution could be provided by developing specific tools for improving decision accuracy while addressing the issue of sustainability through the decision-making process. In this view, this study aims to propose a decision-making model for selecting the best alternative from a number of predetermined PHES candidate sites, in a perspective of sustainable development. The approach is based on the identification of decision factors and criteria, and the use of multi-criteria decision-making (MCDM) techniques such as the analytic hierarchy process (AHP), rating scales and fuzzy logic-based scoring systems, and the ELimination and Choice Expressing REality (ELECTRE) III. These methods are comprehensively selected and combined to deal with the heterogeneity of the information and the vagueness of human preference and, to operationalise the concept of strong sustainability. Its practicality and efficiency was successfully tested on a set of eleven PHES candidate sites in Western Cameroon. As result the five best alternatives to be considered in the framework of the country's sustainable power generation policy were suggested in descending order of priority: (1)-Enep, (2)-Mbatu-dam, (3)-Benakuma, (4)-Bamendjin, (5)-Mentchum.

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.

The use and comparison of a deterministic, a stochastic, and a hybrid multiple-criteria decision-making method for site selection of wind power plants: An application in Turkey

Clean domestic energy is an attractive option, especially for developing countries. Wind has been one of the most appealing renewable energy sources for those as of the beginning of the 20th century. This study focuses on an important work item of the establishment phase of this important energy source: power plant site selection. Three approaches were examined based on multiple-criteria decision-making methods. Stochastic multi-criteria acceptability analysis (a simulation-based approach with different kinds of uncertain information), analytic hierarchy process (a conventional deterministic approach), and AHP-SMAA (a hybrid approach) were applied separately in Turkey. In terms of novelty, analyses were conducted both with (analytic hierarchy process) and without (stochastic multi-criteria acceptability analysis) the preference information of the decision makers. The unique hybrid method integrates stochastic multi-criteria acceptability analysis with analytic hierarchy process to allow the simulation-based experiments with deterministic variables. As a result of the approaches, the same region (Burhaniye-Pelitköy) showed up as the optimal site to establish wind power plants at every turn. The techniques are globally applicable as long as the computational data and all parameters are gathered completely.

Hydrogen Power Plant Site Selection Under Fuzzy Multicriteria Decision-Making (FMCDM) Environment Conditions

Fuel and energy are basic resources necessary to meet a country’s socioeconomic development needs; further, countries rich in these resources have the best premise for meeting the inputs of an economic system; however, this also poses many political challenges and threats to national security. Vietnam is located in the Southeast Asian monsoon-humid tropical region and has diverse fuel-energy resources such as coal, petroleum, and hydropower, along with renewable energy sources such as solar energy, biomass energy, and geothermal energy. However, the reality of economic development in recent years shows complex fluctuations in fuel and energy usage, i.e., besides the export of coal and crude oil, Vietnam still has imported processed oil products. To overcome this issue, many hydrogen power plants will be built in the future. This is why we propose fuzzy multicriteria decision-making (FMCDM) for hydrogen power plant site selection in this research. All criteria affecting location selection are determined by experts and literature reviews, and the weight of all criteria are defined by a fuzzy analytic hierarchy process (FAHP). The technique for order of preference by similarity to an ideal solution (TOPSIS) is a multicriteria decision analysis method, which is used for ranking potential locations in the final stage. As a result, the decision-making unit, DMU010 (DMU010), has become the optimal solution for building hydrogen power plants in Vietnam. A multicriteria decision-making (MCDM) model for hydrogen power plant site selection in Vietnam under fuzzy environment conditions is a contribution of this study. This research also provides useful tools for other types of renewable energies in Vietnam and other countries.

Decision framework for ocean thermal energy plant site selection from a sustainability perspective: The case of China

Site selection is a key factor to the success of ocean thermal energy conversion (OTEC) project. It is a multi-criteria decision making (MCDM) problem with a series of conflicting criteria involved. However, limited studies were found concerning this area and problems existing in classical MCDM methods tended to fail OTEC site selection decisions. Therefore, this paper proposes an extended MCDM method and establishes a new decision-making framework to select the optimal location. First, a comprehensive evaluation criteria system for OTEC site selection from the view of sustainability with 16 criteria involved is established. Second, feasible alternative sites for OTEC project are identified by PEST analysis. Third, an extended PROMETHEE (Preference Ranking Organization Method for Enrichment Evaluation) under intuitionistic fuzzy environment is proposed to avoid compensation assumptions. During the decision process, seven groups of experts shared the work and cooperated with each other according to their backgrounds. Finally, a real case is studied and sensitive analysis is conducted, demonstrating the robustness and effectiveness of the proposed method. This study can effectively improve OTEC site selection decision making quality and also extends the domains of intuitionistic fuzzy PROMETHEE applications.

The Influence of Manufacturing Plant Site Selection on Environmental Impact of Machining Processes

Sustainability has become an important aspect in the strategic planning of manufacturing organizations due to rising energy cost, climate change, environmental emissions, and carbon tax policies. Most of the large manufacturing organizations have a worldwide network of factories, which is mainly driven by financial and political aspects. In past few decades, many attempts have been made to improve the sustainability of the manufacturing processes with consideration of carbon efficiency, energy efficiency, and cost effectiveness. The influence of the manufacturing plant site on the environmental sustainability of the manufacturing process is not considered in most site selection decisions despite its importance in improving the sustainability of production networks. This paper investigates the site based factors to influence the environmental sustainability of a machining process and the effect of these factors is analyzed using life cycle assessment. A case study is conducted with eight different cases based on the location of raw material, manufacturing site, and customers in India and Germany. Four key influencing factors are identified and the environmental impact of the milling process is assessed. One of the key findings is the significant influence of climate and the supply chain on the environmental sustainability of the machining process. This study can be used to include the environmental performance of the machining process into the strategic planning of new manufacturing plants.

A GIS-based Decision-Making Support System for Wind Power Plant Site Selection, Case Study for Saskatchewan

A GIS-based Decision-Making Support System for Wind Power Plant Site Selection, Case Study for Saskatchewan

Optimal site selection of straw biomass power plant under 2-dimension uncertain linguistic environment

The optimal site selection is extremely important for straw biomass power plant. Uncertainty composed of fuzziness and randomness is an important issue in the site selection under increasingly complex environments. The 2-dimension linguistic information is a powerful tool to express the fuzziness of information, and meanwhile, the cloud model depicts the randomness of information with three numerical characteristics perfectly. Combining them together, this paper proposes the specialized decision framework of straw biomass power plant site selection. Firstly, a comprehensive set of index system is established to meet the need of scientific and reasonable evaluation. Secondly, the paper combines three-parameter interval number and order relation to determine the index weight, the importance of each factor is calculated. Thirdly, this paper uses the 2-dimension uncertain linguistic variable group decision-making model which solves the bias caused by individuals, fully expresses expert opinions and reflects the psychological states well, reduces the information missing. Finally, the paper proposes the specialized decision framework of straw biomass power plant site selection which clearly standardizes the decision-making process, provides the project managers with executable and real solutions. The results show that the model is very effective to study the straw biomass power plant site selection and is well worth popularizing in the future studies.

Site Selection of Waste-to-Energy (WtE) Plant considering Public Satisfaction by an Extended VIKOR Method

Site selection of waste-to-energy (WtE) plant is critically important in the whole life cycle. Some research has been launched in the WtE plant site selection, but there is still a serious problem called Not In My Back Yard (NIMBY) effect that needs to be solved. To solve the problem, an improved multigroup VIKOR method is proposed to choose the optimal site and compromised sites. In the proposed method, the public satisfaction is fully considered where the public is invited as an evaluation group far more than creating general indicators to represent the public acceptance. First of all, an elaborate criteria system is built to evaluate site options comprehensively and the weights of criteria are identified by Analytic Hierarchy Process (AHP) method. Then, the interval 2-tuple linguistic information is adopted to assess the ratings for the established criteria. The interval 2-tuple linguistic ordered weighted averaging (ITL-OWA) operator is utilized to aggregate the opinions of evaluation committee while the opinions of the public are aggregated using weighted average operator. Finally, a case from south China which shows the computational procedure and the effectiveness of the proposed method is proved. Last but not least, a sensitivity analysis is conducted by comparing the results with different weights of evaluation group assessments.

A Multi-Criteria Decision Making (MCDM) for Renewable Energy Plants Location Selection in Vietnam under a Fuzzy Environment

In the context of increasing energy demands in Vietnam, and as a result of the limited supply of domestic energy (oil/gas/coal reserves are exhausted), the potential for renewable energy sources in Vietnam is significant. Thus, building wind power plants in Vietnam is necessary. Access to this type of renewable energy not only contributes to society’s energy supply but also helps to save energy and reduce environmental pollution. Although some works have reviewed applications of the Multi-Criteria Decision Making (MCDM) model in wind power plant site selection, little research has focused on this problem in a fuzzy environment. This is the reason why a hybrid Fuzzy Analytic Hierarchy Process (FAHP) and The Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) are developed for wind power plant site selection in Vietnam. In the first stages of this research, an FAHP model is proposed for determining the weight of each potential location for building a wind power plant, based on qualitative and quantitative factors. A TOPSIS is applied for ranking all potential alternatives in the final stage. The authors collected data from seven locations, which have good conditions for investment in a wind power plant. The results indicate that Binh Thuan (Binh Thuan Province is located on coast of South Central Vietnam) is the best place for building a wind power plant in Vietnam. The contributions of this work proposed an MCDM approach under fuzzy environments for wind power plant location selection in Vietnam. This paper also resides in the evolution of a new approach that is flexible and practical for a decision-maker. This work also provides a useful guideline for wind power plant location selection in others countries.