Study On Analysis Methods In Power Systems With Distributed Generation

As the complementarity of centralized generation, distributed generation (DG) has been widely concerned in the world in recent years because it can be reducing power losses and on-peak operating costs, improving voltage profiles, deferring or eliminating for system upgrades, and mitigating environment pollution. Due to some particularities of DG, analysis methods in power systems with DG are not completely consistent with traditional methods. Therefore, study on analysis methods for power grids connected DG is one of the hotspots in the power engineering research field. This thesis concentrates on studying critical problems in this field, including the steady-state and dynamic stability analysis methods for the systems with DG, optimal planning methods for DG, optimal operation methods under the condition of uncertain DG output.In the aspect of the steady-state analysis for the system with DG, at first the models of various kinds of DGs are developed in power flow calculations, and two algorithms available to calculate the power flow of distribution system with multi-type DGs are presented. One includes a two-layer iterance process, and the other is based on constructing a sensitivity matrix. The convergence characteristics of the two algorithms is compared and analyzed. An example of 90-node system gives an illustration of the feasibility of the presented method. After that, the impacts of DG on voltage profiles of distributed network are analyzed using the presented algorithm based a sensitivity matrix. Then, two main scenarios are investigated to evaluate the impacts of DGs on the system static voltage stability. These impacts are quantified by a voltage stability index introduced in this thesis. Some important conclusions are obtained.In the aspect of the optimal planning for DG, a heuristic method for selecting the sites of DG is presented according to the above obtained conclusions. This method is easy to be applied in practice, which is in favor of the planning engineers to site DGs in distribution systems. In addition, this thesis also studies the integrated planning method for siting and sizing of DG. A multi-objective fuzzy optimal model is proposed that takes into account minimizing the investment cost of DG and the power loss of distribution networks and maximizing the static voltage stability margin. The multi-objective planning is transformed into single objective planning by employing the fuzzy optimization theory. Owing to an increase of short-circuit current level (SCL) due to DG, the maximum SCL limit is taken into account in the constraints. The fault calculation principle in the distribution network with DG is analyzed. As DG has the intermission characteristic, a spinning reserve constraint is included in the model, that is, the distribution substation can supply sufficient power to meet load demands should any DG unit quit. The feasibility of the method proposed is shown by an example of a 43-bus distribution system.Wind power generation is one of DG technologies. Large wind farms connected to power grid bring new challenges to optimal operation of power systems. In this thesis, the optimal power flow (OPF) problems in wind power integrated systems are researched and a multi-period dynamic OPF model is presented. In order to consider the wind speed random behavior, a dividing-stage strategy is developed. Based on the Q-V equation of the induction generator, an improved interior point method for the multi-period dynamic OPF is presented. The effectiveness and computation performance of the proposed method are verified in the IEEE 30-bus system.However, wind speed is difficult to be forecasted accurately. In order to overcome the difficulty, fuzzy theory is applied to represent the random variation of wind power output. The dynamic economic dispatch (DED) problem including wind farms is discussed and a fuzzy modeling for DED is then presented, which could make the dispatch result reflect the willingness of decision-makers and hereby adapt the random wind power output better. Moreover, the conventional particle swarm optimization (PSO) is improved by using the descending search and then adopted to solve the proposed dynamic economic dispatch. The example testing result indicates the feasibility of the proposed method.Reactive power optimization problem in distribution system with wind power generators is also analyzed. A compositive index based on scenario analysis is presented. Power loss and static voltage stability margin are taken into considered in this index. A new model including the index for reactive power optimization is proposed. The strategy for selecting typical scenarios of wind power output is discussed from the view point of probability. A genetic algorithm based on self-adaptive weight is proposed and applied to solve the reactive power optimization problem. The samples show that the proposed method is feasible.Finally, influences of DG on the dynamic stability are discussed in some scenarios. A comparison between the network performance with different sites and different contributions of DG is made. Some important conclusions are obtained, which provides a reference value for the operation of practical system.