Research On Risk-based Dispatch Considering The Fuzzy Random Factors Of The Source-side And Load-side

With the environmental contamination and energy crisis,the integration of wind power into the grid has been constantly increasing nowadays.With the integration of large-scale wind power into the grid,the uncertainty of wind power requires the power system to reserve additional capacities and reduces the flexibility of the dispatch.Influenced by subjective factors such as communication delay,neglect of incentive policy and consumption intention,the response behaviors of demand response exhibit uncertain characteristics.With the continuous development of wind power and demand response integrated into the grid,the combined uncertainties of source-side and load-side bring great difficulty to the schedule of power grid.The traditional optimal schedule of power system is inadequate to satisfy the new requirements of power system operation under the hybrid uncertain environment of source-side and load-side.In this background,the risk-based schedule considering fuzzy random factors is investigated in this paper.Fuzzy random chance constrained goal programming is proposed as the theory basis and total probability risk measure is developed as risk criterion of the risk-based schedule.Various types and various characteristics of uncertain factors both in the day-ahead and intra-day scale is quantitative evaluated.The investigation of power system optimal dispatch is carried out to deal with the combined uncertainties both in the source-side and the load-side.The main work and innovative achievements of this paper are as follows:(1)In order to model the double uncertain problem,fuzzy random chance constrained goal programming is proposed based on various theories.Firstly,chance constrained programming under single type of uncertain environment is extended to fuzzy random environment.Then a combination of goal programming and fuzzy stochastic chance constraint programming is utilized to establish fuzzy random chance constrained goal programming.And the correspondding deterministic equivalent is proposed.Fuzzy random chance constrained goal programming avoids the infeasible solution when dealing with a variety of complex chance constraints and provides the theoretical basis for the risk measuse and dispatch model under the fuzzy random environment.The introduction of relaxation deviation value and weight factor makes the optimal solution more close to the preference of decision makers.With regard to computation performance,the deterministic equivalent maintains the model accuracy and accelerates model solutions.(2)In order to conduct the quantitative analysis of potential risk under the fuzzy random environment,total probability risk measure is developed based on fuzzy random chance constrained goal programming.The adjustable random conditional value-at-risk based chance constrained goal programming is proposed and is extended to the fuzzy environment.Then total probability risk measure is proposed by a combination of law of total probability and conditional value-at-risk.In order to identify the different levels of the potential risk,the value-at-risk is introduced as the critical point to divide total probability risk measure into buffer risk zone and extreme risk zone.Total probability risk measure represents both normal condition risk and extreme risk and provides a flexible and careful consideration of risk assessment under fuzzy random environment for the schedule model.The cost coefficients of different risk zones are separately set to represent the risk preference of decision maker.(3)In order to address reserve constraints and branch flow constraints,the day-ahead risk dispatch model is proposed based on fuzzy random chance constrained goal programming and total probability risk measure.First of all,the distribution characteristics of wind power stochastic error and demand response fuzzy error are investigated and fuzzy random variable is introduced to represent the forecast error both in source-side and in load-side.In the day-ahead risk-based schedule,fuzzy random chance constrained goal programming is employed to model fuzzy random forecast error and total probability risk measure is present to evaluate the potential risk caused by forecast error.The validity of the model is verified with IEEE standard case and actual region grid.The results shows that the proposed model is competent enough to effectively quantify the influence of fuzzy random errors on operation schedule.Total probability risk measure makes the schedule to reserve enough adjustment capacities to deal with the potential risks.Besides,total probability risk measure is immune to the confidence level and it is suitable to evaluate the potential risk in the fuzzy random environment.(4)In order to satisfy the requirement of rolling dispatch under fuzzy random environment,the time-varying characteristics of forecast error and fluctuation trend of wind power output in successive periods are taken into consideration.The time-varying slack confidence is introduced to establish the intra-day rolling scheduling model.Firstly,time-varying characteristics and distributing characteristics of the combined uncertainties are analyzed.Fuzzy random variable is introduce to characterize the forecast error of wind power and demand response.To adequately consider time-varying characteristics of forecast error and dynamic update mechanism of rolling dispatch,time-varying slack confidence is embedded in fuzzy random chance constrained goal programming to establish intra-day rolling dispatch model.The numerical results demonstrate that the proposed model can effectively reduce the redundant reserve on the basis of ensuring the safety operation of the system,and reduce the operation cost of rolling schedule by optimizing schedule and reducing the reverse regulation output.(5)In order to address different types and different distributions of uncertain information,the schedule model is established based on a combination of information granular theory and chance constrained goal programming.Firstly,the fuzzy information granular theory is introduced to transform different types and different distributions of uncertain errors to a unified fuzzy granular.Based on the information granular theory,a unified granular model is built up to characterize the combined error of wind power and demand response.In the scheduling model based on fuzzy information granule,fuzzy information granule chance constraint goal programming is employed to establish the reserve constraints and branch flow constraints.The total probability risk measure is adopted to quantitatively evaluate the potential risk caused by fuzzy information granule.Finally,the case studies demonstrate that the proposed model has the ability to effectively handle different types and different distributions of forecast error and improve the computation performance with maintaining the model accuracy.