Theoretical Research On Decision-making Of Unit Commitment To Address Uncertainties

Nowdays,distributed energy resources(DER)are integrated to the transmission network and distribution network in a centralized or decentralized manner.DER include uncontrollable renewable energies(eg.wind and solar energy),and controllable active loads(eg.storage and electric vehicles).Therefore,the generations and loads in power system become diverse,and the bidirectional flow enhances the interaction of the transmission network and distribution network.Under this background,the integration of high percentage DER makes the unit commitment(UC)problem more complex.UC must be combined with active loads(eg.energy storage system(ESS)and demand side response(DR))considering the risk loss caused by uncertainties,storage investment and user utility.In consideration of the spatial distribution characteristics of distributed energy,uncertain risks,energy storage investment and user utility are taken into comprehensive consideration,so as to realize the synergistic optimal decision of transmission,distribution,and micro grid.Therefore,it is difficult to directly use the traditional UC theory and method,and it is undoubtedly of great theoretical significance and engineering value.Under this background,this thesis focuses on dealing with uncertainties or accommodating DER,takes the UC problem as the key,and the optimization of comprehensive benefit as the target.The distributed thought is adopted to coordinate the interaction of the active and passive in DER,as well as the the interaction between transmission and distribution network.The UC optimization decision is researched and explored in-depth.The main work and innovative achievements of this thesis are as follows:(1)In order to determind the optimal confidence interval of wind power uncertainty accepted by power system.A CVaR-based two-stage robust unit commitment(RUC)with adjustable uncertainty set for wind power uncertainty is proposed,and it is solved effectively by the proposed column and constraint generation(C&CG)algorithm,which improves the solving efficiency of the model.The characteristics of this model and method are as follows:Conditional value-at risk(CVaR)is used to measure the operational risks including wind spillage risk and load shedding risk when the real wind power output is beyond the part that the system can accept.The decision maker can make the tradeoff between the acceptance risk loss and the operation economy by adjusting the penalty coefficient,thus determining the admissible boundaries of wind power.CVaR is added into the RUC model as an additional constraint and objective to strictly ensure the operation feasibility within the uncertainty set,and limit the risk loss outside the uncertainty set.ESS can not only improve the flexibility of thermal power system operation,but also reduce the risk of system operation.Case studies illustrate that the effectiveness of the model and method.(2)In view of the problem that the wind power random process is difficult to be expressed as precise probability density and probability distribution.A distributionally robust Uunit commitment(DRUC)based on imprecise Dirichlet model(IDM)is proposed.The model does not need to assume that the wind power follows the predetermined probability distribution,and the ambiguity set constructed based on IDM contains all possible cumulative distribution function(CDF)of wind power,so the CDF confidence belt can be more accurately estimated.Then,based on the CDF confidence belt,the uncertainty interval of wind power is deduced at a certain confidence level.In this way,it can be connected with the traditional adaptive robust optimization model.By this means,the intractable DRUC problem is reformulated into a traditional RUC problem,which improves the applicability of the model.Different from the model with affine policy,which may lead to sub-optimal solution,the proposed model complies with the fully adaptive policy between UC and robust optimization,thus,it can inherit the features of the traditional RO while overcoming its conservativeness.Finally,the min-max-min robust optimization model can be solved efficiently by C&CG algorithm.Case studies demonstrate the effectiveness and efficiency of the proposed method.Imprecise probability is used to describe the uncertainty problem,which provides a new way to deal with the uncertainties in UC optimization strategy.(3)In view of the problem that individual differences of user demand response(DR)and weak degree of system node in UC,an integrated UC dispatch strategy based on compensation mechanism considering DR behavior is proposed.According to the law of diminishing marginal utility on individual user in economics,the mechanism of individual utility integrated overall utility is studied,and the analytic expression of demand utility function of different users is deduced.The demand utility function is incorporated into the traditional UC model to realize the joint optimization of DR and UC.In order to encourage users to actively participate in DR,the mechanism design principle based on game theory is adopted to design a DR compensation mechanism that takes into account incentive compatibility constraint and individual rational constraint.This mechanism correlates user behavior parameters with user intention parameters and node location parameters of power system.The special compensation schemes for different users at differnt locations avoids the conservatism of overall behavior decision-making of market.Meanwhile,the game-based parameter formation mode overcomes the problems of communication,calculation and privacy in parameter setting under the centralized manner.The mixed integer programming is used to solve the model.Case studies demonstrate the effectiveness and efficiency of the proposed method.This research fully excavates the initiative of the load side,and provides a new idea for how to stimulate the participation of active load in the integration decision of DR and UC.(4)On the basis of the above research,in order to consider the correlation and influence between transmission and distribution networks,a transmission grid(TG)-active distribution grid(ADG)-micro grid(MG)three-layer interactive UC model of regional power system and a novel analytical target cascading(ATC)algorithm are proposed.In order to explore the synergistic ability of the TG-ADG-MG coping with uncertainties,the primary and secondary frequency regulation are taken as the means for the TG to cope with uncertainties,and together with the active loads in ADG-MG,they are added into the multi-layer interactive UC model.Both the start up/shut down variables of the thermal units and the active variables in TG-ADG-MG are optimized simultaneously.This model realizes the optimal goal of the whole network,and resources complementary and optimal allocation of power system.The model is solved by target cascading parallel solution method,its core is:the overall optimization obj ective of the regional system is continuously divided according to TG-ADG-MG,the response of each layer is fed back from bottom to top,and each layer is solved independently and optimized alternately.In this way,the source-network-load-storage synergistic scheduling can be realized horizontally,and the synergistic optimization of TG-ADG-MG can be realized vertically.This study explores the initiative of the whole network,realizes the unified optimization of the whole network.It is the extension of the UC theory to 'source-network-load' synergy on multi-layer network,which has certain engineering application value.The research in this thesis provides the theoretical basis for the optimization decision of the multi-layer interactive UC model in regional power system.It expands the application of uncertain theory and method in the UC problem,fully excavates the initiative of source side,demand side and the entire network.It has certain reference value for improving the unified comprehensive scheduling level of the power system.