| In recent years,renewable energy has been developed rapidly,among them,wind power is particularly prominent,which can effectively improve the environmental pollution problems and ease the energy crisis.Due to the limitations of wind power prediction technology and the diversity of climate and terrain distribution,wind power has the characteristics of intermittence,uncertainty and partial predictability,which challenges the planning and operation of power system.Wind power probability distribution function is uncertain indeed,as the exact information is not given,it’s impossible to reflect the actual wind power output,moreover,it’s hardly to fundamentally guarantee the effectiveness of power system planning and operation methods.When only partial information of the wind power probability distribution function is available,robust optimization method can be used to solve these problems.In this paper,two kinds of robust optimization methods are discussed.One of them will set the wind speed and the wind turbine output as random variables,and use the interval uncertainty set to describe the wind speed,and the random variable distribution information is used to describe wind power output uncertainty,the random optimization problem is rewritten as a deterministic one.The other robust optimization method using the CVaR(Conditional value at risk)to obtain the CVaR constraint model which include uncertainties when the first moment and second moment are given.To solve the proposed model conveniently,the proposed model is simplified by optimized duality theory,Schur complement and S-lemma and convert the CVaR constraint into bilinear matrix inequality(BMI)constraints.Finally,the deterministic model is solved using BMI-based immune particle swarm optimization(PSO)algorithm.In this paper,we study the application of robust optimization method in flexible load scheduling,reactive power planning and available transmission capacity assessment.Set wind power as the representative of new energy,the power output uncertainty can be balanced using flexible power scheduling.However,the flexible load is autonomy,randomness and disorder in most case,which will further increase the power system uncertainty.The flexible load scheduling strategy of transmission system based on robust optimization method is proposed in this paper.Distributionally robust optimization method is used to solve the reactive power planning in transmission system,it can be effectively applied to any wind power probability distribution case in the uncertainty set,minimize the power loss and reactive power equipment investment cost with the security constraints satisfied.Distributionally robust optimization method can be also used to solve the available transmission capacity assessment problem in transmission system,it can be effectively applied to any wind power probability distribution case in the uncertainty set,maximize the ATC with the security constraints satisfied.The simulation results and the numerical examples show that the proposed method is feasible and effective in the planning and operation of transmission system. |
