Energy Optimization Of Distribution Network With Distributed Generation

Nowadays, the Distributed Generation (DG) is promoted on a wide scale inmany countries driven by the problems of energy shortage and environmentalpollution. Since the DG can satisfy the specific requirements of power system andpower customers, and improve the reliability and economy, the permeability of DGis increased continuously. The traditional distribution network structure is changedwith the access of DG, and the output power of DG has characteristics ofrandomness, which complicate the energy management and optimal operation ofdistribution network.The energy optimization of distribution network with distributed generationwas studied in this paper, including economic dispatching and optimal power flow.For the question of economic dispatching, based on the mathematical models ofdistributed generation including solar power, wind power, fuel cell, diesel andbattery, the objective functions and energy dispatching strategies of the renewableenergy distribution generation system were presented. The objective functions werecalculated with the priority list method and the simulation results showed thecorrectness and validity of the models and algorithms. For the question of optimalpower flow, it established optimal power flow models for three objective functionsincluding minimizing generation cost, pollution processing cost and active powerloss. The back/forward sweep method was used to calculate power flow, and theself-adaptive move-step size was introduced to Tabu search algorithm to solve theoptimal power flow. Through calculating the IEEE33-node example system, itverifies the validity of the models and algorithm.In addition, for the uncertainties abundantly existed in power market, on thebasis of a review of the research methods of uncertainty, a new model fordescribing the uncertainties, which combined interval number and fuzzy number,was proposed in this paper. In the case study, the model was used to express thesolar and wind output power and load forecasting value, and the traditional fuzzysimulation was modified and then applied to the power flow calculation consideringuncertainty.