Research On Multi-objective Dynamic Reactive Power Optimization For Smart Grid

The Reactive Power Optimization of distribution network is an important method to improve the power quality and system stability of power system. It can not only reduce the power loss of system, but also can adjust the grid voltage, so as to guarantee the security and stability of power system. With the speeding up of the smart grid process, the Distributed Generation(DG) will place in power system, causing certain influence to system current, voltage, which changes the traditional reactive power optimization of distribution network. Therefore, under the background of DG’s interconnection, the reactive power optimization of distribution network has important engineering significance.Because of the interconnection and randomness of DG, traditional reactive power optimization model is no longer applicable. Therefore this paper proposes a new optimization algorithm--Chaos Artificial Bee Colony Differential Evolution (CABC-DE) algorithm, respectively applies it to a multi-objective reactive power optimization model including DGs and a dynamic reactive power optimization model including DGs. Specific work is as follows:1. Due to the defects of premature convergence, poor local search ability of DE, this paper improves DE on the idea of artificial colony algorithm (ABC) and Chaos (Chaos), proposes the Chaos Artificial Bee Colony Differential Evolution (CABC-DE) algorithm. Then builds the model that make active power loss minimum as objective function, applies CABC-DE and DE respectively to IEEE-14 and IEEE-30 system simulation to verify the practicability of CABC-DE. The results show that the new algorithm is more suitable for reactive power optimization problem.2. Study the multi-objective reactive power optimization of distribution network system after DG’s interconnection. In order to achieve the multi-objective reactive power optimization, the paper proposes the multi-objective CABC-DE based on Pareto optimality theory. Then build the model that makes active power loss minimum, voltage deviation minimum, reactive compensation minimum as objective functions, then does simulations on IEEE-30 system. The results show that the algorithm can obtain uniform distribution of Pareto front, realizes the optimization of three objective functions, and satisfies the requirements of security and economy for power grid operation.3. Study the dynamic reactive power optimization of distribution network system after DG’s interconnection. In order to fully considering the randomness of DG’s power output and power system security, economy, the paper firstly builds the dynamic reactive power optimization of distribution network with DG, limits the number of reactive power control equipment operations in order to save operation cost and equipment life. And then consider the change of system load, cut the average daily load curve into different segments, fully considering the randomness of DG in each segment to obtain the optimal dynamic reactive power optimization.