Demand Response Contextual Remuneration of Prosumers with Distributed Storage
Author:
Silva CátiaORCID, Faria PedroORCID, Ribeiro Bruno, Gomes LuísORCID, Vale ZitaORCID
Abstract
Prosumers are emerging in the power and energy market to provide load flexibility to smooth the use of distributed generation. The volatile behavior increases the production prediction complexity, and the demand side must take a step forward to participate in demand response events triggered by a community manager. If balance is achieved, the participants should be compensated for the discomfort caused. The authors in this paper propose a methodology to optimally manage a community, with a focus on the remuneration of community members for the provided flexibility. Four approaches were compared and evaluated, considering contextual tariffs. The obtained results show that it was possible to improve the fairness of the remuneration, which is an incentive and compensation for the loss of comfort. The single fair remuneration approach was more beneficial to the community manager, since the total remuneration was lower than the remaining approaches (163.81 m.u. in case study 3). From the prosumers’ side, considering a clustering method was more advantageous, since higher remuneration was distributed for the flexibility provided (196.27 m.u. in case study 3).
Funder
FEDER Funds through COMPETE program national funds
Subject
Electrical and Electronic Engineering,Biochemistry,Instrumentation,Atomic and Molecular Physics, and Optics,Analytical Chemistry
Reference26 articles.
1. Short Time Electricity Consumption Forecast in an Industry Facility;IEEE Trans. Ind. Appl.,2022 2. Fei, L., Shahzad, M., Abbas, F., Muqeet, H.A., Hussain, M.M., and Bin, L. (2022). Optimal Energy Management System of IoT-Enabled Large Building Considering Electric Vehicle Scheduling, Distributed Resources, and Demand Response Schemes. Sensors, 22. 3. Bhattacharya, S., Chengoden, R., Srivastava, G., Alazab, M., Javed, A.R., Victor, N., Maddikunta, P.K.R., and Gadekallu, T.R. (2022). Incentive Mechanisms for Smart Grid: State of the Art, Challenges, Open Issues, Future Directions. Big Data Cogn. Comput., 6. 4. Behavioral decision-making in power demand-side response management: A multi-population evolutionary game dynamics perspective;Int. J. Electr. Power Energy Syst.,2021 5. Muqeet, H.A., Javed, H., Akhter, M.N., Shahzad, M., Munir, H.M., Nadeem, M.U., Bukhari, S.S.H., and Huba, M. (2022). Sustainable Solutions for Advanced Energy Management System of Campus Microgrids: Model Opportunities and Future Challenges. Sensors, 22.
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