Abstract
Due to the need to include renewable energy resources in electrical grids as well as the development and high implementation of PV generation and DC grids worldwide, it is necessary to propose effective optimization methodologies that guarantee that PV generators are located and sized on the DC electrical network. This will reduce the operation costs and cover the investment and maintenance cost related to the new technologies (PV distributed generators), thus satisfying all technical and operative constraints of the distribution grid. It is important to propose solution methodologies that require short processing times, with the aim of exploring a large number of scenarios while planning energy projects that are to be presented in public and private contracts, as well as offering solutions to technical problems of electrical distribution companies within short periods of time. Based on these needs, this paper proposes the implementation of a Discrete–Continuous Parallel version of the Particle Swarm Optimization algorithm (DCPPSO) to solve the problem regarding the integration of photovoltaic (PV) distributed generators (DGs) in Direct Current (DC) grids, with the purpose of reducing the annual costs related to energy purchasing as well as the investment and maintenance cost associated with PV sources in a scenario of variable power demand and generation. In order to evaluate the effectiveness, repeatability, and robustness of the proposed methodology, four comparison methods were employed, i.e., a commercial software and three discrete–continuous methodologies, as well as two test systems of 33 and 69 buses. In analyzing the results obtained in terms of solution quality, it was possible to identify that the DCPPSO proposed obtained the best performance in relation to the comparison methods used, with excellent results in relation to the processing times and standard deviation. The main contribution of the proposed methodology is the implementation of a discrete–continuous codification with a parallel processing tool for the evaluation of the fitness function. The results obtained and the reports in the literature for alternating current networks demonstrate that the DCPPSO is the optimization methodology with the best performance in solving the problem of the optimal integration of PV sources in economic terms and for any kind of electrical system and size.
Funder
University of Talca- Chile, Universidad Distrital Francisco José de Caldas, Colombia, and Universidad Nacional de Colombia
Subject
General Mathematics,Engineering (miscellaneous),Computer Science (miscellaneous)
Reference38 articles.
1. Monteiro, V., Oliveira, C., Coelho, S., and Afonso, J.L. (2022). Active Building Energy Systems, Springer.
2. Detailed study, multi-objective optimization, and design of an AC-DC smart microgrid with hybrid renewable energy resources;Ghiasi;Energy,2019
3. Resiliency/cost-based optimal design of distribution network to maintain power system stability against physical attacks: A practical study case;Ghiasi;IEEE Access,2021
4. Vasant, P., Weber, G.W., Thomas, J.J., Marmolejo-Saucedo, J.A., and Rodriguez-Aguilar, R. (2022). Artificial Intelligence for Renewable Energy and Climate Change, John Wiley & Sons.
5. Ahmad, R., Mohamed, A.A.A., Rezk, H., and Al-Dhaifallah, M. (2022). DC Energy Hubs for Integration of Community DERs, EVs, and Subway Systems. Sustainability, 14.
Cited by
1 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. Optimal Allocation of DG Units in Radial Distribution Systems;2023 8th International Conference on Mathematics and Computers in Sciences and Industry (MCSI);2023-10-14