Research Of Optimal Electric Power Dispatch Including Wind Farm

Different from conventional generation, wind power brings about a new demandand challenge for the dispatching of power system due to its intermittent, volatility andanti-peaking. The use of the Energy Storage System (ESS) can help to alleviate theimpact of these issues on the power system, and improve the flexibility of the powersystem operation. Dynamic economic dispatch is a high dimension, nonlinear,multi-constrained optimization problem, which is difficult to get the optimal solution.But since it has great economic benefits, the research of the dynamic economic dispatchis significant under the economic requirements and application of the electricitymarkets.Base on the state of power system economic dispatch, the dynamic economicdispatch and energy-saving dispatch considering ESS、wind farm and thermal powerplants are researched. The main work are as follows:①Based on “information-sharing strategy “and “elite learning strategies“, theparticle swarm optimization (PSO) algorithm is improved. The example shows that thealgorithm can accelerate the convergence speed of the particles and enhance the abilityto search the global optimal solution. It provides an efficient algorithm to solve thepower system dynamic economic dispatch with ESS and wind farm.②The dynamic economic dispatch of power system must considers the couplingof different time sections, it will be more complex when wind power integration intopower system. Base on the dynamic economic dispatch in the power system with windpower and thermal power, this paper considers the influence of ESS, the single-objectmodel of dynamic economic dispatch in the power system with ESS、wind power andthermal power is established. The improved PSO algorithm is used to solve this problem.On this basis, the effect of ESS installed in different location on the economic dispatchis considered, when the line transmission capacity is insufficient.③Considering thermal power unit start-stop scheduling and the ESS connected tothe grid, an unit commitment model is established. The model considers the output ofthermal power, output of wind farm and charging and discharging power of ESS ascontrolling variables, with minimize the generating cost as the function，the constrainsinclude the output constraints and the ramp speed constraints of thermal power unit、theoutput constraints and the charging and discharging limits of ESS, and so on. And the problem is solved by branch-and-bound method and PSO algorithm. The thermalpowers and ESS share the spinning reserve capacity demand brought by wind powerforecasting error together.