Evaluation of the impact of the distance determination function on the results of optimization of the geographical placement of renewable energy sources-based generation using a metaheuristic algorithm
Since the United Power System was created electrical supply of remote and hard-to-reach areas remains one of the topical issues for the power industry of Russia. Nowadays, usage of various renewable energy sources to supply electricity at remote areas has become feasible alternative to usage of dies...
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Saint-Petersburg Mining University
2025-02-01
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| Series: | Записки Горного института |
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| Online Access: | https://pmi.spmi.ru/pmi/article/view/16333?setLocale=en_US |
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| author | Andrei M. Bramm Stanislav A. Eroshenko |
| author_facet | Andrei M. Bramm Stanislav A. Eroshenko |
| author_sort | Andrei M. Bramm |
| collection | DOAJ |
| description | Since the United Power System was created electrical supply of remote and hard-to-reach areas remains one of the topical issues for the power industry of Russia. Nowadays, usage of various renewable energy sources to supply electricity at remote areas has become feasible alternative to usage of diesel-based generation. It becomes more suitable with world decarbonization trends, the doctrine of energy security of Russia directives, and equipment cost decreasing for renewable energy sources-based power plants construction. Geological exploration is usually conducted at remote territories, where the centralized electrical supply can not be realized. Placement of large capacity renewable energy sources-based generation at the areas of geological expeditions looks perspective due to development of industrial clusters and residential consumers of electrical energy at those territories later on. Various metaheuristic methods are used to solve the task of optimal renewable energy sources-based generation geographical placement. The efficiency of metaheuristics depends on proper tuning of that methods hyperparameters, and high quality of big amount of meteorological and climatic data. The research of the effects of the calculation methods defining distance between agents of the algorithm on the optimization of renewable generation placement results is presented in this article. Two methods were studied: Euclidean distance and haversine distance. There were two cases considered to evaluate the effects of distance calculation method change. The first one was for a photovoltaic power plant with installed capacity of 45 MW placement at the Vagaiskii district of the Tyumen region. The second one was for a wind power plant with installed capacity of 25 MW at the Tungokochenskii district of the Trans-Baikal territory. The obtained results show low effects of distance calculation method change at average but the importance of its proper choose in case of wind power optimal placement, especially for local optima’s identification. |
| format | Article |
| id | doaj-art-b5e5f72385d4450ebce3c4d74a5e0b40 |
| institution | OA Journals |
| issn | 2411-3336 2541-9404 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | Saint-Petersburg Mining University |
| record_format | Article |
| series | Записки Горного института |
| spelling | doaj-art-b5e5f72385d4450ebce3c4d74a5e0b402025-08-20T02:02:09ZengSaint-Petersburg Mining UniversityЗаписки Горного института2411-33362541-94042025-02-0127114115316333Evaluation of the impact of the distance determination function on the results of optimization of the geographical placement of renewable energy sources-based generation using a metaheuristic algorithmAndrei M. Bramm0https://orcid.org/0000-0002-1868-4389Stanislav A. Eroshenko1https://orcid.org/0000-0001-9617-2154Ural Federal University named after the first President of Russia B.N.YeltsinUral Federal University named after the first President of Russia B.N.YeltsinSince the United Power System was created electrical supply of remote and hard-to-reach areas remains one of the topical issues for the power industry of Russia. Nowadays, usage of various renewable energy sources to supply electricity at remote areas has become feasible alternative to usage of diesel-based generation. It becomes more suitable with world decarbonization trends, the doctrine of energy security of Russia directives, and equipment cost decreasing for renewable energy sources-based power plants construction. Geological exploration is usually conducted at remote territories, where the centralized electrical supply can not be realized. Placement of large capacity renewable energy sources-based generation at the areas of geological expeditions looks perspective due to development of industrial clusters and residential consumers of electrical energy at those territories later on. Various metaheuristic methods are used to solve the task of optimal renewable energy sources-based generation geographical placement. The efficiency of metaheuristics depends on proper tuning of that methods hyperparameters, and high quality of big amount of meteorological and climatic data. The research of the effects of the calculation methods defining distance between agents of the algorithm on the optimization of renewable generation placement results is presented in this article. Two methods were studied: Euclidean distance and haversine distance. There were two cases considered to evaluate the effects of distance calculation method change. The first one was for a photovoltaic power plant with installed capacity of 45 MW placement at the Vagaiskii district of the Tyumen region. The second one was for a wind power plant with installed capacity of 25 MW at the Tungokochenskii district of the Trans-Baikal territory. The obtained results show low effects of distance calculation method change at average but the importance of its proper choose in case of wind power optimal placement, especially for local optima’s identification.https://pmi.spmi.ru/pmi/article/view/16333?setLocale=en_USpv power plantswind power plantscapacity factorswarm intelligenceartificial intelligenceforecasting |
| spellingShingle | Andrei M. Bramm Stanislav A. Eroshenko Evaluation of the impact of the distance determination function on the results of optimization of the geographical placement of renewable energy sources-based generation using a metaheuristic algorithm Записки Горного института pv power plants wind power plants capacity factor swarm intelligence artificial intelligence forecasting |
| title | Evaluation of the impact of the distance determination function on the results of optimization of the geographical placement of renewable energy sources-based generation using a metaheuristic algorithm |
| title_full | Evaluation of the impact of the distance determination function on the results of optimization of the geographical placement of renewable energy sources-based generation using a metaheuristic algorithm |
| title_fullStr | Evaluation of the impact of the distance determination function on the results of optimization of the geographical placement of renewable energy sources-based generation using a metaheuristic algorithm |
| title_full_unstemmed | Evaluation of the impact of the distance determination function on the results of optimization of the geographical placement of renewable energy sources-based generation using a metaheuristic algorithm |
| title_short | Evaluation of the impact of the distance determination function on the results of optimization of the geographical placement of renewable energy sources-based generation using a metaheuristic algorithm |
| title_sort | evaluation of the impact of the distance determination function on the results of optimization of the geographical placement of renewable energy sources based generation using a metaheuristic algorithm |
| topic | pv power plants wind power plants capacity factor swarm intelligence artificial intelligence forecasting |
| url | https://pmi.spmi.ru/pmi/article/view/16333?setLocale=en_US |
| work_keys_str_mv | AT andreimbramm evaluationoftheimpactofthedistancedeterminationfunctionontheresultsofoptimizationofthegeographicalplacementofrenewableenergysourcesbasedgenerationusingametaheuristicalgorithm AT stanislavaeroshenko evaluationoftheimpactofthedistancedeterminationfunctionontheresultsofoptimizationofthegeographicalplacementofrenewableenergysourcesbasedgenerationusingametaheuristicalgorithm |