The power flow calculation considering uncertainty is the most basic way for solving the security issue of the system under uncertain conditions. As the renewable energy characterized by randomness and uncertainty, such as wind and solar power, has been applied to the distribution network, it is especially essential to study on power flow of distribution network considering uncertainty. The traditional models of uncertainty have the problem of singleness in expressing uncertainties while the uncertainty objectively shares two or more than two kinds of characteristics. A new model for describing the uncertainties, which combines connection number and fuzzy number and describes the interval quality and fuzziness of uncertain information comprehensively, is presented. Through improving the calculation of sample value and possibility measure, the traditional fuzzy simulation is modified and then applied to the power flow calculation in consideration of wind and solar power output uncertainty and load uncertainty. Two definitions, which are satisfaction index and degree of uncertainty, are introduced to measure the results accuracy with sample number changing and to represent the variation range of uncertain parameters respectively. The proposed model and modified algorithm are verified by case studies based on IEEE 33-bus system. The results are compared with those obtained from Monte Carlo simulation and proved to be correct. In addition, several other numerical examples are presented and discussed in order to achieve the influences of sample number, degree of uncertainty and membership function change on results. Through analysis of the power flow results considering uncertainty, we may find out the weak links of network, which can provide references for making electrical accident premeditation and then adjusting operation scheme. (C) 2013 Elsevier Ltd. All rights reserved.

For the distribution network with distributed generation, we establish optimal power flow models for three objective functions including minimizing generation cost, pollution processing cost and active power loss. We use the back/forward sweep method to calculate power flow, and adopt the modified Tabu search algorithm to solve the optimal power flow. In the process of searching, we introduce the self-adaptive move-step size to improve the algorithm accuracy. Through calculating the IEEE 33-node example system, we verify the validity of the models and algorithm. The research shows it can achieve the goals of reducing cost, loss and pollution with the optimal control of distribution network with distributed generation.

Through the study on economic dispatching of renewable energy distribution generation system, the operating costs and environmental pollution could be minimized on the premise of meeting the demands, and eventually the renewable energy would be more efficiently used. The mathematical models of renewable energy distribution generation system were analyzed in detail which including solar power, wind power, fuel cell, diesel and battery were analyzed. Based on the models, the objective functions and energy dispatching strategies of the system were presented. The objective functions were calculated with the priority list method. The simulation results showed the correctness and validity of the models and algorithms. The method can provide a reference for the optimal dispatch and economic combination of generation unit in renewable energy distribution generation systems.

A new control strategy of grid-connected inverters in microgrid is presented in this paper. Combining the voltage, the frequency, the active power and the reactive power of microgrid, the structure of the grid-connected inverters is analyzed. And then it achieved the V/f-P/Q control strategy of the grid-connected inverters in microgrid. Also, the conventional P/Q control strategy of the grid-connected inverters is researched in the end. Through the example system, the dynamic characteristics of microgrid with the mode switching and load changing are detailedly analyzed. The simulation results show the correctness and validity of the control strategy of grid-connected inverters.