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Economic Dispatch For Wind-Thermal Hybrid Power Systems Based On Particle Swarm Optimization

Posted on:2016-03-13Degree:MasterType:Thesis
Country:ChinaCandidate:F WuFull Text:PDF
GTID:2272330470470924Subject:Control engineering
Abstract/Summary:PDF Full Text Request
With the increase of energy demand and depletion of global fossil oil resources in 21 century, wind power generation has become a good alternative to thermal energy power generation. However, different from conventional generators, wind power has uncertainty and variability, thus the large-scale integration of wind power generators causes operational challenges to power grid. Economic dispatch (ED) is a high-dimensional, nonlinear, non-convex, multi-constrained optimization problem, and it becomes more complex with the integration of wind power. This paper will investigate the economic dispatch for wind-thermal hybrid power systems via particle swarm optimization (PSO) method.First, the effects of the wind power on the conventional power systems are analyzed in order to solve the ED problem. The uncertainty and variability of wind power are analyzed to build wind power prediction output model. Based on the general ED solution methods, an ED mathematical programming model with wind power integration is proposed, which contains the objective function with wind power output and constraints with positive/negative spinning reserve.Second, a hybrid intelligent algorithm combining discrete particle swarm optimization (DPSO) and quadratic programming (QP) algorithm is introduced. ED problem is divided into outer and inner optimization sub-problems. The outer layer is unit commitment, solved by discrete particle swarm optimization considering unit rules. The inner layer is economic distribution of the load solved by quadratic programming. The specific solution procedure is illustrated through a 10-machine system. Unit commitment and load distribution before and after integrating wind power are compared. The results show that the algorithm is feasible effective, giving trade-off between economy and reliability in wind power integrated systems.Finally, an improved dual particle swarm optimization (PSO) algorithm including both discrete and continuous parts is proposed. The starting and shutdown states of units are optimized according to different period of time using discrete PSO, The continuous PSO is used in units’ load dispatch during the process of deciding starting-stopping states and after the solution, where constraints of power balance, spinning reserve and lower and upper limits were considered. Example of a 10-machine system is considered. The experimental results show the proposed approach decreases the cost during dispatch and improves the convergence rate.
Keywords/Search Tags:unit commitment, wind power, discrete particle swarm optimization, dual particle swarm optimization, quadratic programming
PDF Full Text Request
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