Demand Response Incentive Mechanism Design Of Civil Load With Distributed Sources&Energy Storage

Smart grid and energy interconnection provide powerful technical support for energy consumption revolution among the end-users. Currently, occupying higher proportion and with the development of small-scale distributed sources and energy storage devices, civil load has advanced into new load resources characterized with controllable autonomy and self-adjusting flexibility, which contain lots of demand response resources to be better developed and utilized. Under the dual pressure of growing energy demand and the deteriorated global environment, civil load demand response resources have become important potential solution the world’s energy and environmental crisis. This paper takes the new civil load equipped with distributed photovoltaic and energy storage as an example. The interest of both the incentive policy makers and civil load responders considered, the optimal decision of designing the demand response incentive mechanism is analyzed through model simulation in this paper.Firstly, the pluralistic, multi-state response characteristics of civil load containing distributed power and energy storage is studied based on domestic and abroad researches on civil load response strategy and practice experience of response incentive policy. And an optimization model of response decision to maximize the users’profit is built, based on which how the incentives affect the capacity programming of distributed photovoltaic and energy storage is debated. Secondly, the bi-level programming model is proposed to describe the response revenue coordination between the incentive policy-maker and civil load during demand response. Upper model where the policy-makers maximize social welfare objectives is to design the incentive mechanism, which is passed to the lower model where civil loads response in a way to maximize their own profit. Then the feedback from the lower model is sent to the upper one in turn. Thus the incentive design will finally be done through ’incentive-response’iterative interaction process between upper and lower models. The whole model is solved by the combined algorithm of genetic algorithm and branch-cut algorithm. Finally, simulation shows how the optimized response incentive mechanism works on the benefit of the system operator and users. Quantitative Analysis is carried out to research on the theory how’source-load’factors influence the incentive design, and collaborative relationship among multiple incentives when operating on civil loads is explored simply. The feasibility and effectiveness of model is verified by examples.