Yayın: An interactive multi-criteria decision-making framework between a renewable power plant planner and the independent system operator
| dc.contributor.author | Soltaniyan, Salman | |
| dc.contributor.author | Salehizadeh, Mohammad Reza | |
| dc.contributor.author | Tascikaraoglu, Akin | |
| dc.contributor.author | Erdinc, Ozan | |
| dc.contributor.author | Catalao, Joao P. S. | |
| dc.date.accessioned | 2026-06-27T14:34:47Z | |
| dc.date.issued | 2021 | |
| dc.description.abstract | Providing efficient support mechanisms for renewable energy promotion has drawn much attention from researchers in the recent years. The connection of a new renewable power plant to the transmission system has impacts on different electricity market indices since the other strategic generation units change their behaviour in the new multi-agent environment. In this paper, as the main contribution to the previous literature, a combination of multi-criteria decision-making approach and multi-agent modelling technique is developed to obtain the maximum possible profits for an intended renewable generation plan and also direct the investment to be located in a way to improve electricity market indices besides supporting renewable energy promotion. Fuzzy Q-learning electricity market modelling approach in combination with the technique for order preference by similarity (TOPSIS) is used as a new decision support system for promotion of renewable energy for the first time in the literature. The proposed interactive multi-criteria decision-making framework between the independent system operator (ISO) and the renewable power plant planner provides a win win situation that improve market indices while help the renewable power plant planning. The effectiveness of the proposed method is examined on the IEEE 30-bus test system and the results are discussed. (c) 2021 Elsevier Ltd. All rights reserved. | en |
| dc.description.sponsorship | FEDER funds through COMPETE 2020 | |
| dc.description.sponsorship | Portuguese funds through FCT [POCI-01-0145-FEDER-029803 (02/SAICT/2017)] | |
| dc.description.uri | https://doi.org/10.1016/j.segan.2021.100447 | |
| dc.identifier.doi | 10.1016/j.segan.2021.100447 | |
| dc.identifier.issn | 2352-4677 | |
| dc.identifier.uri | https://hdl.handle.net/20.500.14981/62310 | |
| dc.identifier.volume | 26 | |
| dc.identifier.wos | 000645076400005 | |
| dc.language.iso | eng | |
| dc.publisher | ELSEVIER | |
| dc.relation.ispartof | SUSTAINABLE ENERGY GRIDS & NETWORKS | |
| dc.subject | Electricity market | |
| dc.subject | Power system | |
| dc.subject | Renewable energy | |
| dc.subject | Reinforcement learning | |
| dc.subject | Fuzzy Q-learning | |
| dc.subject | CONGESTION MANAGEMENT | |
| dc.subject | ENERGY | |
| dc.subject | GENERATION | |
| dc.subject | TRANSMISSION | |
| dc.subject | INTEGRATION | |
| dc.subject | OPTIMIZATION | |
| dc.subject | EFFICIENCY | |
| dc.subject | RESOURCES | |
| dc.subject | STRATEGY | |
| dc.subject | DESIGN | |
| dc.subject | Energy & Fuels | |
| dc.subject | Engineering | |
| dc.title | An interactive multi-criteria decision-making framework between a renewable power plant planner and the independent system operator | |
| dc.type | Article | |
| dspace.entity.type | Publication | |
| local.import.source | WOS |