Abstract

In this study, capacity allocation of demand-response (DR) and the real-time savings earned from implementing DR programmes (DRPs) are investigated based on a mixed integer non-linear multi-objective programming (MINMOP) framework according to two conflicting concepts, titled; maximum achievable potential (MAP) and realistic achievable potential (RAP). MAP indicates that placing a value on DR resources must be strictly weighed against the value of avoiding the acquisition of short-term resources to meet critical peak period, whereas RAP takes into accounts the amount of savings that might be achieved through DRPs. The proposed MINMOP includes both technical and economic aspects of integrating DRPs into the power systems by considering optimal generation scheduling cost, voltage drop, voltage stability margin, network loss, and incentive payment as objective functions. In addition, augmented ɛ-constraint method is applied to solve the proposed MINMOP by means of off-the-shelf conventional optimisation software. The IEEE 24-bus reliability test system (RTS 24-bus) is used to demonstrate the applicability of the proposed method. Eventually, DR allocation is analysed through four cases based on different number of candidate buses which demonstrate the interest and effectiveness of the proposed technique.

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