A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Optimal strategy of electricity and natural gas aggregators in the energy and balance markets
This paper presents a stochastic two-stage model for energy aggregators (EAs) in the energy and balancing markets to supply electricity and natural gas to end-users equipped with combined heat and power (CHP) units. The suggested model takes into account the battery energy storage (BES) as a self-generating unit of EA. The upper and lower subproblems determine the optimal energy supply strategy of EA and consumption of consumers, respectively. In the lower subproblem, the McCormick relaxation is used to linearize the cost function of the CHP unit. To solve the proposed model, the two-stage problem is transformed into a linear single-stage problem using the KKT conditions of the lower subproblem, the Big M method, and the strong duality theory. The performance and efficiency of the proposed model are evaluated using a case study and three scenarios. According to the simulation results, adding CHP units to the energy-scheduling problem of BES-owned aggregators increases the profit of EA by 5.96% and decreases the cost of consumers by 1.57%. ; This work has received funding from the EU Horizon 2020 research and innovation program under project TradeRES (grant agreement No 864276). Pedro Faria is supported by FCT, grant CEECIND/01423/2021. The authors acknowledge the work facilities and equipment provided by GECAD research center (UIDB/00760/ 2020) to the project team. ; info:eu-repo/semantics/publishedVersion
Optimal strategy of electricity and natural gas aggregators in the energy and balance markets
This paper presents a stochastic two-stage model for energy aggregators (EAs) in the energy and balancing markets to supply electricity and natural gas to end-users equipped with combined heat and power (CHP) units. The suggested model takes into account the battery energy storage (BES) as a self-generating unit of EA. The upper and lower subproblems determine the optimal energy supply strategy of EA and consumption of consumers, respectively. In the lower subproblem, the McCormick relaxation is used to linearize the cost function of the CHP unit. To solve the proposed model, the two-stage problem is transformed into a linear single-stage problem using the KKT conditions of the lower subproblem, the Big M method, and the strong duality theory. The performance and efficiency of the proposed model are evaluated using a case study and three scenarios. According to the simulation results, adding CHP units to the energy-scheduling problem of BES-owned aggregators increases the profit of EA by 5.96% and decreases the cost of consumers by 1.57%. ; This work has received funding from the EU Horizon 2020 research and innovation program under project TradeRES (grant agreement No 864276). Pedro Faria is supported by FCT, grant CEECIND/01423/2021. The authors acknowledge the work facilities and equipment provided by GECAD research center (UIDB/00760/ 2020) to the project team. ; info:eu-repo/semantics/publishedVersion
Optimal strategy of electricity and natural gas aggregators in the energy and balance markets
Khojasteh, Meysam (author) / Faria, Pedro (author) / Lezama, Fernando (author) / Vale, Zita (author)
2022-01-01
doi:10.1016/j.energy.2022.124753
Article (Journal)
Electronic Resource
English
DDC:
690
Aggregators' Optimal Bidding Strategy in Sequential Day-Ahead and Intraday Electricity Spot Markets
| BASE | 2017
Modeling a Local Electricity Market for Transactive Energy Trading of Multi-Aggregators
| BASE | 2022
Consumer Psychology Based Optimal Portfolio Design for Demand Response Aggregators
| DOAJ | 2021
Coordination of specialised energy aggregators for balancing service provision
| BASE | 2022