{"title":"Applying the Analytic Hierarchy Process to Decision Making on the Development of Urban Energy System","authors":"T. Bugaeva, I. Filippova, Nikita Tribunskii","doi":"10.1145/3444465.3444513","DOIUrl":null,"url":null,"abstract":"Conditions for the development of urban energy supply systems have changed significantly in recent years. The functional and spatial structure of loads is changing; new technologies are emerging; electric and thermal energy markets are developing; new rules for their functioning are emerging; the industry is being digitalized. The range and influence of the concerned parties on the development of energy systems have expanded. One of the ways to improve the quality of decisions on the development of the city's energy supply is to create a decision support system (DSS), which can be used jointly by all entities involved in the development of the city's energy complex. The DSS is based on the energy system planning methodology. Multi-criteria analysis (MCDA) methods are often used in the decision-making process. However, the choice of a particular method and the possibility of its application to the problems of energy development require additional research. The article substantiates the need to apply MCDA methods when planning the development of energy systems in cities. The implementation of the analytic hierarchy process (AHP) is shown on the example of choosing the reconstruction option for a transformer substation. The criteria for achieving the goal are: minimum costs; minimum energy losses; minimum undersupply of electricity and minimum length of electrical networks. To automate calculations, the authors created a template MS Excel 2016, which implements the presented method. AHP allows to move the decision-making process to the area of strict mathematically based calculations and conclusions.","PeriodicalId":249209,"journal":{"name":"Proceedings of the 2nd International Scientific Conference on Innovations in Digital Economy","volume":"2 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2nd International Scientific Conference on Innovations in Digital Economy","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3444465.3444513","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
Conditions for the development of urban energy supply systems have changed significantly in recent years. The functional and spatial structure of loads is changing; new technologies are emerging; electric and thermal energy markets are developing; new rules for their functioning are emerging; the industry is being digitalized. The range and influence of the concerned parties on the development of energy systems have expanded. One of the ways to improve the quality of decisions on the development of the city's energy supply is to create a decision support system (DSS), which can be used jointly by all entities involved in the development of the city's energy complex. The DSS is based on the energy system planning methodology. Multi-criteria analysis (MCDA) methods are often used in the decision-making process. However, the choice of a particular method and the possibility of its application to the problems of energy development require additional research. The article substantiates the need to apply MCDA methods when planning the development of energy systems in cities. The implementation of the analytic hierarchy process (AHP) is shown on the example of choosing the reconstruction option for a transformer substation. The criteria for achieving the goal are: minimum costs; minimum energy losses; minimum undersupply of electricity and minimum length of electrical networks. To automate calculations, the authors created a template MS Excel 2016, which implements the presented method. AHP allows to move the decision-making process to the area of strict mathematically based calculations and conclusions.