Coordinated Optimal Scheduling Of Active Distribution Network With Multi-Microgrids

The integration of distributed generations,energy storage systems,controllable loads and microgrids has significantly changed the operation approach and control strategies of distribution network.This innovation promotes the transition of distribution network from passive systems with unidirectional flow to active distribution network with bidirectional flow,thus making the reliability,economy and environmental benefit greatly enhanced.However,the proliferation of variable distributed energy resources also brings complexity problems to distribution network operation from both technical and economic aspects.Furthermore,the uncertainty and volatility of renewable energy generations bring challenges to the security and reliability of power systems.Distributed generations,along with storage and control devices,can supply the electrical and heat loads locally,introducing the concept of microgrid(MG).MG can operate autonomously or intentionally island from the grid during events thereby improving system reliability.Distribution network and MGs are different independent entities,utilized by distribution network operator(DNO)and microgrid operator(MGO)respectively.The operating condition of MG would influence the scheduling strategy of DNO,and vice versa.Therefore,this paper proposes an optimization model for coordinated optimal scheduling of distribution network and MGs,aiming at minimizing operational cost of each entity.The main contributions of this paper are summarized as follows:(1)Proposing a scenario-based two stage stochastic optimal scheduling model for active distribution network.For the proposed model,the contracting cost of energy and reserve scheduling is considered in the first stage and the expected adjustment cost of actual reserve deployment under different scenarios is considered in the second stage.Scenario-based method is used to approach the uncertainty of renewable generations,where Latin hypercube sampling is used to generate scenarios and simultaneous backward reduction is applied for scenario reduction.The power flow of distribution network is linearized via a simplified method,making the proposed model transformed into a linear programming problem.Then the proposed model is solved using the Cplex solver of general algebraic modeling system software.Case studies show that the proposed stochastic model can effectively reduce reserve configuration and improve economic benefits.(2)Proposing a hierarchical bilevel model for coordination of distribution network and MGs.Model for the distribution network is at the upper level and models for MGs are at the lower level.The distribution network and microgrids optimize their own objective independently,aiming at minimizing respective operational cost.The contracting cost of energy and reserve scheduling and theexpected adjustment cost of actual reserve deployment under different scenarios are considered.Moreover,MG serves a reserve supplier for distribution network and can obtain benefits for that.The proposed bilevel model is solved based on Karush-Kuhn-Tucker condition.Models of MGs is transformed into constraints of DNO model,thus the bilevel problem can be dealt in the form of single-level problem.A modified IEEE 33-bus distribution network with three MGs is used for case studies.Results show that the proposed bilevel model can coordinate economics of the distribution network and MGs,and the MG reserve service can enhance the economics of the whole system(including distribution network and microgrids).(3)Solving the proposed bilevel model with analytical target cascading(ATC),a distributed algorithm.Considering the autonomy and information privacy for MGs,ATC,a distributed algorithm,is used to solve the proposed model.The interruptable load program is considered in the energy and reserve scheduling.Models for the distribution network and MGs are decomposed via shared variables between them and a penalty relaxation of consistency constraints of levels is used to ensure subproblems feasibility.Then iterative coordination of subproblems is performed with limited information exchange between distribution network and MGs.Tests show that the operational cost of the whole system under ATC is close to results traditional central algorithm and the amount of information transformed between distribution network and MGs is reduced.ATC can realize a holistic optimization while maintaining autonomy and information privacy of MGs.