Increasing distributed generators(DGs)and flexible loads(FLs)enable distribution systems to provide both active and reactive power reserves(P-Q reserves)in supporting the frequency and voltage regulations of transmiss...Increasing distributed generators(DGs)and flexible loads(FLs)enable distribution systems to provide both active and reactive power reserves(P-Q reserves)in supporting the frequency and voltage regulations of transmission systems.However,such requirements at the interface between the transmission system operator(TSO)and distribution system operator(DSO)affect the distribution system operation security,considering the uncertainties of DGs and FLs.To exploit the reserve potential of distribution systems,this paper investigates the voltagedependent P-Q reserve capacity(V-PQRC)of such types of distribution systems.V-PQRC reflects the feasible space of PQ reserves that the DSO can provide to the TSO taking the voltage deviation limit at TSO-DSO interface into consideration,while ensuring the distribution system operation security under uncertainties of DGs and FLs.An evaluation method for VPQRC at the TSO-DSO interface is proposed.To improve the robust performance of the evaluation method,the DG uncertainty is captured by a generalized ambiguity set and the FL uncertainty is addressed by designing a constrained sliding mode controller(CSMC).Three objectives are considered in the evaluation,i.e.,P reserve capacity,Q reserve capacity,and the voltage deviation limit at the TSO-DSO interface.Then,a multiobjective optimization model integrating the generalized robust chance-constrained optimization and CSMC(GRCC-CSMC)is established for V-PQRC evaluation to obtain the Pareto optimal reserve schemes.Finally,a non-approximated selecting(NAS)method is proposed to build up a simplified V-PQRC linear model,which can be convenient to apply in the transmissiondistribution system coordination.Simulation results reveal that the V-PQRC evaluation method can achieve a good performance of accuracy and robustness against uncertainties.展开更多
基金supported by the National Key R&D Program of China(2020YFB0905900)Science and Technology Project of SGCC(State Grid Corporation of China):The key Technologies for Electric Internet of Things(SGTJDK00DWJS2100042).
文摘Increasing distributed generators(DGs)and flexible loads(FLs)enable distribution systems to provide both active and reactive power reserves(P-Q reserves)in supporting the frequency and voltage regulations of transmission systems.However,such requirements at the interface between the transmission system operator(TSO)and distribution system operator(DSO)affect the distribution system operation security,considering the uncertainties of DGs and FLs.To exploit the reserve potential of distribution systems,this paper investigates the voltagedependent P-Q reserve capacity(V-PQRC)of such types of distribution systems.V-PQRC reflects the feasible space of PQ reserves that the DSO can provide to the TSO taking the voltage deviation limit at TSO-DSO interface into consideration,while ensuring the distribution system operation security under uncertainties of DGs and FLs.An evaluation method for VPQRC at the TSO-DSO interface is proposed.To improve the robust performance of the evaluation method,the DG uncertainty is captured by a generalized ambiguity set and the FL uncertainty is addressed by designing a constrained sliding mode controller(CSMC).Three objectives are considered in the evaluation,i.e.,P reserve capacity,Q reserve capacity,and the voltage deviation limit at the TSO-DSO interface.Then,a multiobjective optimization model integrating the generalized robust chance-constrained optimization and CSMC(GRCC-CSMC)is established for V-PQRC evaluation to obtain the Pareto optimal reserve schemes.Finally,a non-approximated selecting(NAS)method is proposed to build up a simplified V-PQRC linear model,which can be convenient to apply in the transmissiondistribution system coordination.Simulation results reveal that the V-PQRC evaluation method can achieve a good performance of accuracy and robustness against uncertainties.
