Multi-Stage Robust Dispatch Considering Demand Response Under Decision-Dependent Uncertainty

A multistage distributionally robust optimization approach for generation dispatch with demand response under endogenous and exogenous uncertainties

“…The convergence of Algorithm 1 can be referred to [30]. Since the introduction of dummy variables does [23] not essentially change the iteration process of SDDiP, that is, the forward and backward step, the convergence of our improved SDDiP is the same as that of standard SDDiP [30]. By implementing Algorithm 1 in day-ahead stage, the optimal power output and reserve capacity of thermal units and underapproximation cutting planes can be obtained.…”

“…The conventional loads can be distinguished with the curtailable loads by setting the parameter d c,u n,t in equation (6e) to be 0. The DDUs of deferrable loads are essentially caused by the accumulation of demand shifting decisions at previous stages [23]. For a real-time DR program in re-dispatch, the demands at current time will be shifted to the future time.…”

“…The DDUs of deferrable loads are essentially caused by the accumulation of demand shifting decisions at previous stages [23]. For a real‐time DR program in re‐dispatch, the demands at current time will be shifted to the future time.…”

“…However, all of them almost adopted SP or RO methods in a two-stage framework. Reference [23] used a multistage dispatch method but it still belongs to the category of RO. In this case, the mentioned drawbacks of SP, RO and two-stage scheduling might be inherently introduced into dispatch decisions.…”

“…In [22], strategic day‐ahead renewable power curtailment is considered in robust generation dispatch, which affects the variation range of real‐time wind power output and thus forms a decision‐dependent uncertainty set. Reference [23] developed a multistage robust dispatch model to cope with the DDUs of deferrable loads.…”