Distributionally robust chance-constrained energy management of steel industrial microgrid with energy storage in distribution market

The uncertainty of distributed PV output in the high-energy-consuming steel industrial microgrid (SIMG) can have an impact on the energy management strategy of the SIMG and even increase the operational risk in the distribution market. Considering the uncertainty of distributed PV in SIMG, this paper proposes an energy management method for SIMG under distribution market based on the distributionally robust chance-constraint (DRCC), to optimal the processes of steel industrial production. Firstly, according to the form of energy flow and information flow of SIMG, the transactional mode of participating in distribution market-clearing is proposed. A time series model of the steel production process is included in the energy management for SIMG, and the bi-level energy optimization management model under the environment of distribution market is further constructed. Then, DRCC method is applied to deal with the uncertainty of distributed PV output and the distributionally robust optimization model of energy management for SIMG based on moment information is constructed. Conditional value-at-risk (CVaR) theory and duality theory are introduced to transform the distributionally robust optimization model into a second-order cone (SOC) programming form. Finally, the primal-dual counterpart condition and the linearization method are introduced to transform the bi-level model into a mixed integer SOC programming (MISOCP) problem. The results show that the proposed method can take into account the risk and economy of energy management.