Consumer Reliability Evaluation Of Distributed Network With Distributed Generation Considering Load Nodes’ Equivalent Loss For The Quantity Of Electricity

With the development of power distributed network, more and more researches have turned their views into the consumer side when discussing the operation of power system. The basic requirement for the reliability of power system is to supply power steadily and continuously for consumers. It’s necessary to focus more on the consumer side as well as the demand response when doing reliability research.According to the theory of reliability, many researches focus on power running and fault analysis, consulting reliability index of time, frequency, and probability, but seldom on the consumer side. Especially when DGs are put into network, the situation is becoming more complicated and consumers will play a more directly role in the power system. A full consideration for reliability is good for the construction of the power system. So this paper will be focused on the points below:1. Deeply researching on the basic theory of network reliability, including basic index for the evaluation of network reliability, compare between advantages and disadvantages of methods for evaluation.2. The first 2 chapters also analyze features of DG, and also different ways to access into network.3. On chapter 3, firstly simplify the network into a equivalent model. Analyzing consumers value of loss from different sides: safety level, economic loss, level for backup DG Then setting up the model for Equivalent Loss for the Quantity of Electricity.4. Focus on the method to solve reliability evaluation, combining the concept model of equivalent loss for load nodes’electricity and the unavailability time index of reliability evaluation, a new Monte Carlo Method is used to calculate the equivalent loss for the quantity of electricity. The efficiency for the method is proved by the example, can be used for quantized analyzing the reliability of every user considering the status of loads.5. On chapter 5, a new method for optimizing power cut off is used to discuss when a power cut off situation comes. Based on Genetic Algorithm, finding a optimized consumer group to cut off.