Protection system planning in distribution networks with microgrids using a bi-level multi-objective and multi-criteria optimization technique
•Optimized allocation, selectivity, coordination and specification of traditional protection and control devices (reclosers, sectionalizing switches, and fuses), in addition to island interconnection devices in the point of common coupling of microgrids, and relays ANSI 51 V and 81 as local protecti...
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| Veröffentlicht in: | Electric power systems research Jg. 228; S. 109966 |
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| Format: | Journal Article |
| Sprache: | Englisch |
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Elsevier B.V
01.03.2024
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| ISSN: | 0378-7796 |
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| Abstract | •Optimized allocation, selectivity, coordination and specification of traditional protection and control devices (reclosers, sectionalizing switches, and fuses), in addition to island interconnection devices in the point of common coupling of microgrids, and relays ANSI 51 V and 81 as local protections in the point of coupling of distributed generation (DG) units. The proposal considers the load transference to neighbor feeders and fuse-save and fuse-blow schemes.•Inclusion of dispatchable and renewable DG and BESS since such technologies present different behaviors regarding reliability and coordination features. Electric vehicle charging stations are considered in this work, as well.•Consideration of uncertainties associated with generation and loads categorized by the k-means method. Furthermore, the state-of-charge of batteries is estimated using a fuzzy inference system, where neural network tunning techniques are applied to adjust the fuzzy sets and fuzzy rules. Associated uncertainties are used as input data, and the batteries’ SoC from an optimal power flow model is considered output data for improving the fuzzy inference system performance;.•Use of a bi-level multi-criteria and multi-objective mixed integer nonlinear programming model, where the protection system coordination problem is embedded within the allocation problem as the lower-level optimization task. Efficient solutions are generated by NSGA-II metaheuristic, and the best compromise solution is identified by using the compromise programming based on companies’ criteria in a weight system, where the cost of energy not supplied and investment cost are the conflicting objectives.
Microgrids are able to improve several features of power systems, such as energy efficiencies, operating costs and environmental impacts. Nevertheless, microgrids’ protection must work congruently with power distribution protection to safely take all advantages. This research contributes to enable their protection by proposing a bi-level method to simultaneously solve the allocation and coordination problems, where the proposed scheme also includes local protections of distributed energy resources. The uncertainties associated with generation and loads are categorized by the k-means method, as well. The non-dominated sorting genetic algorithm II is employed in the upper-level task to solve the protection and control devices allocation problem with two opposing objectives. In the lower-level task, a genetic algorithm ensures their coordination. Protection devices include reclosers and fuses from the network, and directional relays for the point of common coupling of microgrids, while control devices consist of remote-controlled switches. In contrast to related works, local devices installed at the point of coupling of distributed generation units are considered as well, such as voltage-restrained overcurrent relays and frequency relays. The optimal solution for the decision-maker is achieved by utilizing the compromise programming technique. Results show the importance of solving the allocation and coordination problems simultaneously, achieving up to $25,000 cost savings compared to cases that solve these problems separately. The integrated strategy allows the network operator to select the optimum solution for the protective system and avoid corrective actions afterward. The results also show the viability of the islanding operation depending on the decision maker's criteria. |
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| AbstractList | •Optimized allocation, selectivity, coordination and specification of traditional protection and control devices (reclosers, sectionalizing switches, and fuses), in addition to island interconnection devices in the point of common coupling of microgrids, and relays ANSI 51 V and 81 as local protections in the point of coupling of distributed generation (DG) units. The proposal considers the load transference to neighbor feeders and fuse-save and fuse-blow schemes.•Inclusion of dispatchable and renewable DG and BESS since such technologies present different behaviors regarding reliability and coordination features. Electric vehicle charging stations are considered in this work, as well.•Consideration of uncertainties associated with generation and loads categorized by the k-means method. Furthermore, the state-of-charge of batteries is estimated using a fuzzy inference system, where neural network tunning techniques are applied to adjust the fuzzy sets and fuzzy rules. Associated uncertainties are used as input data, and the batteries’ SoC from an optimal power flow model is considered output data for improving the fuzzy inference system performance;.•Use of a bi-level multi-criteria and multi-objective mixed integer nonlinear programming model, where the protection system coordination problem is embedded within the allocation problem as the lower-level optimization task. Efficient solutions are generated by NSGA-II metaheuristic, and the best compromise solution is identified by using the compromise programming based on companies’ criteria in a weight system, where the cost of energy not supplied and investment cost are the conflicting objectives.
Microgrids are able to improve several features of power systems, such as energy efficiencies, operating costs and environmental impacts. Nevertheless, microgrids’ protection must work congruently with power distribution protection to safely take all advantages. This research contributes to enable their protection by proposing a bi-level method to simultaneously solve the allocation and coordination problems, where the proposed scheme also includes local protections of distributed energy resources. The uncertainties associated with generation and loads are categorized by the k-means method, as well. The non-dominated sorting genetic algorithm II is employed in the upper-level task to solve the protection and control devices allocation problem with two opposing objectives. In the lower-level task, a genetic algorithm ensures their coordination. Protection devices include reclosers and fuses from the network, and directional relays for the point of common coupling of microgrids, while control devices consist of remote-controlled switches. In contrast to related works, local devices installed at the point of coupling of distributed generation units are considered as well, such as voltage-restrained overcurrent relays and frequency relays. The optimal solution for the decision-maker is achieved by utilizing the compromise programming technique. Results show the importance of solving the allocation and coordination problems simultaneously, achieving up to $25,000 cost savings compared to cases that solve these problems separately. The integrated strategy allows the network operator to select the optimum solution for the protective system and avoid corrective actions afterward. The results also show the viability of the islanding operation depending on the decision maker's criteria. |
| ArticleNumber | 109966 |
| Author | Leite, Jonatas B. Reiz, Cleberton Javadi, Mohammad Sadegh Gouveia, Clara S. |
| Author_xml | – sequence: 1 givenname: Cleberton orcidid: 0000-0002-6718-396X surname: Reiz fullname: Reiz, Cleberton email: cleberton.reiz@unesp.br organization: Department of Electrical Engineering, São Paulo State University (UNESP), Ilha Solteira, São Paulo, Brazil – sequence: 2 givenname: Jonatas B. orcidid: 0000-0002-1204-7178 surname: Leite fullname: Leite, Jonatas B. organization: Department of Electrical Engineering, São Paulo State University (UNESP), Ilha Solteira, São Paulo, Brazil – sequence: 3 givenname: Clara S. surname: Gouveia fullname: Gouveia, Clara S. organization: Institute for Systems and Computer Engineering, Technology and Science (INESC TEC), Porto, Portugal – sequence: 4 givenname: Mohammad Sadegh surname: Javadi fullname: Javadi, Mohammad Sadegh organization: Institute for Systems and Computer Engineering, Technology and Science (INESC TEC), Porto, Portugal |
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| Cites_doi | 10.1109/TPWRD.2020.3013233 10.1016/j.jpowsour.2019.226824 10.1049/iet-gtd.2019.1945 10.1109/ACCESS.2022.3166918 10.1007/s00521-019-04361-z 10.1109/TLA.2015.7350048 10.1109/ACCESS.2020.3048940 10.1016/j.epsr.2017.03.028 10.1109/ACCESS.2022.3146799 10.1016/j.asoc.2020.106741 10.1109/TII.2017.2682101 10.1109/TIA.2022.3147149 10.1016/j.epsr.2020.106453 10.1016/j.rser.2021.111401 10.1109/TPWRS.2018.2842648 10.1109/TPWRS.2014.2322811 10.1109/TSTE.2018.2850805 10.1109/ACCESS.2019.2938193 10.1007/s40313-021-00729-6 10.1109/TPWRS.2018.2805322 10.1109/TSG.2017.2771146 10.3390/wevj13090163 10.1109/TSG.2016.2609681 10.1016/j.ijepes.2021.106925 10.1109/ACCESS.2021.3096128 |
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| Keywords | Power distribution planning Multi-objective programming Bi-level optimization Reliability Power system protection Microgrids |
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