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Due to the growing importance of demand response program (DRP) in demand side management in power systems as well as increasing employment of combined heat and power (CHP) units, the issue of energy management of large consumers equipped with CHP units in the presence of a DRP based on the day-ahead electricity price has been studied in this paper. To solve the considered non-convex and non-linear energy management problem, particle swarm optimization (PSO) algorithm has been used. Also, given the importance of the effect of uncertainties on the planning and operation of units in the energy management, the unscented transformation (UT) method is used for modeling uncertainties related to electricity prices and the amount of electric and thermal loads. In the applied DRP, the consumers can shift a percentage of their load from higher-price hours to lower-price hours to reduce operating costs. No load-shedding is considered in the problem formulation. The consumer energy system consists of two CHP units, one electrical unit, one thermal unit, and a heat buffer tank (HBT) for the storage of surplus thermal energy. The consumer can also buy electricity from the main electricity grid to supply the demanded load based on the price of electricity. The simulation results show that the application of the suggested DRP reduces the operational cost.
|Title of host publication||Proceedings - 2022 IEEE 4th Global Power, Energy and Communication Conference, GPECOM 2022|
|Number of pages||7|
|Publication status||Published - 2022|
Bibliographical noteThis research was funded by the European Union’s Horizon 2020 research
and innovation programme under the Marie Sklodowska-Curie grant
agreement No 812991. J. M. Guerrero was supported by VILLUM FONDEN
under the VILLUM Investigator Grant (no. 25920).
- PSO algorithm
- UT method
- combined heat and power unit
- demand response
- energy management