Zhiao Li, Laijun Chen, Wei Wei, et al. Risk Constrained Self-Scheduling of AA-CAES Facilities in Electricity and Heat Markets: A Distributionally Robust Optimization Approach[J]. CSEE Journal of Power and Energy Systems, 2024, 10(3): 1159-1167.
DOI:
Zhiao Li, Laijun Chen, Wei Wei, et al. Risk Constrained Self-Scheduling of AA-CAES Facilities in Electricity and Heat Markets: A Distributionally Robust Optimization Approach[J]. CSEE Journal of Power and Energy Systems, 2024, 10(3): 1159-1167.DOI: 10.17775/CSEEJPES.2020.06130.
Risk Constrained Self-Scheduling of AA-CAES Facilities in Electricity and Heat Markets: A Distributionally Robust Optimization Approach
Advanced adiabatic compressed air energy storage (AA-CAES) has the advantages of large capacity
long service time
combined heat and power generation (CHP)
and does not consume fossil fuels
making it a promising storage technology in a low-carbon society. An appropriate self-scheduling model can guarantee AA-CAES's profit and attract investments. However
very few studies refer to the cogeneration ability of AA-CAES
which enables the possibility to trade in the electricity and heat markets at the same time. In this paper
we propose a multi-market self-scheduling model to make full use of heat produced in compressors. The volatile market price is modeled by a set of inexact distributions based on historical data through ø-divergence. Then
the self-scheduling model is cast as a robust risk constrained program by introducing Stackelberg game theory
and equivalently reformulated as a mixed-integer linear program (MILP). The numerical simulation results validate the proposed method and demonstrate that participating in multi-energy markets increases overall profits. The impact of uncertainty parameters is also discussed in the sensibility analysis.