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Optimism Allocation Of Distribution Generation Considering Distribution Network Operation Risk

Posted on:2016-10-08Degree:MasterType:Thesis
Country:ChinaCandidate:L X WangFull Text:PDF
GTID:2322330473965727Subject:Electrical engineering
Abstract/Summary:PDF Full Text Request
The reasonable, safe and reliable use of renewable energy is the key step in the national strategy of sustainable development. Renewable energy sources such as wind, solar and other natural climate conditions, has a strong random and intermittent characteristic. Such characteristic brings about much influence of different level on operation and planning of distribution network. The degree of influence is closely related to the location and capacity of distributed generation.This paper makes a evaluation of distribution network operation risk, which combines with the characteristics of distributed generation. The distribution network operation risk assessment is based on the risk theory. The analysis is developed from two points, which are the impact on of the operation risk and cost when distribution generation accessing to the distribution network. The easy also uses the improved particle swarm optimization algorithm to improve the distributed generation multi-objective optimal allocation model, to obtain the optimal allocation scheme. The specific contents are as follows:Firstly, according to the effect of distribution generation on distribution network operation risk, a evaluation model is established. The model uses utility function to measure the consequences of failure, synthetically considers the impacts of distributed power line outage probability and aging of components failure rate and weather factors on the probability of failure. The establishment of risk index is from three aspects, which are the node voltage and line overload and loss of system load. A combination weighting method is used in the distribution network operation risk assessment process, which is the combination of AHP and the node important degree. The IEEE-33 bus system simulation results show that the evaluation method has good adaptability to the fluctuation of load, which can be used in the evalution of distribution network operation risk under different load demand.Secondly, the risk theory is introduced to the optimal allocation of distributed generation. And a multi-objective optimization model for distribution network based on the risk assessment is established. The model considers the influence of system risk and economy when distribution generation accessing to distribution network. The model can adjust the indexes by changing the index weights, in order to achieve the optimal allocation of distributed generation in different operation modes. Through the example of IEEE-33 bus system, the results show that the optimal objective function is proposed to meet the requirements of different operation condition optimization, and can improve system operating conditions. What's more it can impove the safety and economy of system operation, and the fluctuation of the system load is more feasible.Lastly, a probability model of distributed power supply is established, because when the wind turbine and photovoltaic power access to distribution network, the output is random, intermittent. Through the analysis of the influence of distributed generation output volatility on the operation cost of the distribution network, the cost of distributed generation operation risk was introduced to the optimal allocation of distributed generation. Distribution generation optimization model was established to run the risk of cost considerations. The model also takes into account to run the risk of islanded mode as the optimization goal, in order to reduce accident loss when a major accident cases happen. Simulation results of PG&E 69 bus system show that the optimization is not only more economical, effective and reasonable, but also fully embodies the comprehensive value of distributed generation.
Keywords/Search Tags:Distribution generation, Optimization, Distribution network planning, Operation risk, Cost of risk, Particle swarm optimization
PDF Full Text Request
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