| Considering the deteriorating global environment and the challenge of power supply brought about by the energy crisis,governments of different countries have begun to introduce energy policies in order to encourage the development and utilization of distributed renewable energy.The fast development of distributed generation(DG)helps to exposes the advantages and disadvantages all together.Although green power supply is more environment-friendly,its randomness,volatility and variability will bring great challenges to the stable operation of the distribution network connected to urban power grid.In addition,the traditional network capacity expansion construction in order to improve the reliability of power grid will be constrained by limited urban space.Therefore,various types of flexible distributed energy resources(DER),including demand response,electric vehicles(EV)and energy storage can help address these problems.To build much elastic and resilient urban distribution network,it is of vital significance to aggregate the same type of DERs at each node of distributed netwok and to establish a two-layer distributed optimal scheduling model.This paper builds a two-layer distributed optimal scheduling strategy to coordinate multitype DERs in distribution network.A deterministic optimization model and robust optimization model are proposed based on this two-layer framework.Firstly,the characteristics of various DERs such as DG,demand response,EVs,and energy storage are studied.Then,a two-layer distributed optimal scheduling framework is established to coordinate different kinds of DERs.Finally,considering the deterministic and stochastic characteristics of DERs’ response to the incentive signals,a deterministic optimization scheduling model and a robust optimization scheduling model to coordinate multi-type DERs are established based on aobove mentioned framework.The main work of this paper is as follows:(1)Research on the characteristics of DERs connected to the power grid.Firstly,the characteristics of different kinds of DERs such as DG,energy storage,electric vehicles and demand response are studied.Considering the decentralized characteristics of interruptible load and individual electric vehicle,the similar resources connected to the same node of distribution network are aggregated,so as to obtain the distributed resource aggregation models which are available to distribution network operators or dispatching agencies.In addition,since power user’s response is affected by the actual condition of industrial production or the randomness of the user’s individual behavior,the uncertainty of all kinds of DERs is analyzed.Through case study,the validity of the models in this chapter is verified.(2)Establishment of deterministic optimal scheduling model for DERs based on the twolayer distributed scheduling framework.Firstly,based on the different characteristics of global controller and local controller such as scheduling period and the ability to derive local information,a two-layer distributed scheduling framework is built.The framework takes a full advantage of local controllers to improve the prediction accuracy of DG and load,and to share the computation tasks of the global controller.Then,based on the two-layer distributed dispatching framework,a two-layer distributed optimal schdeduling model is established to support the safe and economic operation of distribution network with multi-type DERs.The effectiveness and superiority of the proposed two-layer distributed optimal scheduling model are verified through case study.(3)Establishment of robust optimal scheduling model for DERs based on two-layer distributed scheduling framework.Based on the two-layer distributed scheduling framework proposed above,an optimal scheduling model provided for local controller is adjusted due to the uncertainty of DERs’ response,and the AARO robust optimization method is applied on the scheduling model.The response uncertainty of multi-type DERs will be handled by the realtime adjustable variables of energy storage.Case study is given to verify the economy and robustness of distributed network under AARO robust optimization algorithm. |
PDF Full Text Request