A platform for research: civil engineering, architecture and urbanism
Energy-constrained model for scheduling of battery storage systems in joint energy and ancillary service markets based on the energy throughput concept
Among different local renewable resources, using battery energy storage (BES) has grown more than other technologies. The main reasons for this growth are flexibility and schedulability of BES. The fast ramp-rate of BES systems provides the opportunity of effective participation of these resources in the regulation ancillary service. However, continuous charging and discharging cycles of BES could decrease its lifetime and the expected profit, consequently. Therefore, the lifespan is a crucial parameter that shall be considered in the scheduling of BES. In this paper, an energy-constrained model is proposed for the scheduling of BES in joint energy and ancillary service markets. Moreover, the Energy Throughput (ET) concept is proposed for modeling the lifetime in the short-term scheduling strategy. In the proposed strategy, the uncertainties of energy prices in energy and regulation markets are modeled by Robust Optimization (RO) methodology. The scheduling problem is linearized and formulated based on the mixed-integer linear programming (MILP) method. The proposed model determines the optimal scheduling of BES based on the profit maximization, operational constraints, lifespan, and the defined risk level. Finally, the performance of model is evaluated vie case study results. ; This work has received funding from the EU Horizon 2020 research and innovation program under project TradeRES (grant agreement No 864276) and from FEDER Funds through COMPETE program and from National Funds through FCT under the projects UIDB/00760/2020 and CEECIND/02887/2017 CIND. ; info:eu-repo/semantics/publishedVersion
Energy-constrained model for scheduling of battery storage systems in joint energy and ancillary service markets based on the energy throughput concept
Among different local renewable resources, using battery energy storage (BES) has grown more than other technologies. The main reasons for this growth are flexibility and schedulability of BES. The fast ramp-rate of BES systems provides the opportunity of effective participation of these resources in the regulation ancillary service. However, continuous charging and discharging cycles of BES could decrease its lifetime and the expected profit, consequently. Therefore, the lifespan is a crucial parameter that shall be considered in the scheduling of BES. In this paper, an energy-constrained model is proposed for the scheduling of BES in joint energy and ancillary service markets. Moreover, the Energy Throughput (ET) concept is proposed for modeling the lifetime in the short-term scheduling strategy. In the proposed strategy, the uncertainties of energy prices in energy and regulation markets are modeled by Robust Optimization (RO) methodology. The scheduling problem is linearized and formulated based on the mixed-integer linear programming (MILP) method. The proposed model determines the optimal scheduling of BES based on the profit maximization, operational constraints, lifespan, and the defined risk level. Finally, the performance of model is evaluated vie case study results. ; This work has received funding from the EU Horizon 2020 research and innovation program under project TradeRES (grant agreement No 864276) and from FEDER Funds through COMPETE program and from National Funds through FCT under the projects UIDB/00760/2020 and CEECIND/02887/2017 CIND. ; info:eu-repo/semantics/publishedVersion
Energy-constrained model for scheduling of battery storage systems in joint energy and ancillary service markets based on the energy throughput concept
Khojasteh, Meysam (author) / Faria, Pedro (author) / Vale, Zita (author)
2021-01-01
doi:10.1016/j.ijepes.2021.107213
Article (Journal)
Electronic Resource
English
DDC:
690
Scheduling of Battery Energy Storage and Demand Response Resource in Balancing Ancillary Service
BASE | 2020
|Scheduling of Battery Energy Storage and Demand Response Resource in Balancing Ancillary Service
BASE | 2020
|Battery energy storage systems for ancillary services in Renewable energy communities
BASE | 2023
|Optimizing commercial building participation in energy and ancillary service markets
Online Contents | 2014
|