| Faced with the continuous deterioration of ecological environment,increasing depletion of fossil fuels and the appeals for green alternative energy sources,solar energy is currently one of the most renewable energies and it has the potential for large-scale development and utilization because of its clean,efficient,and endless feature.Solar power has raised the attention of the governments all around the world,among which photovoltaic generation has got the most attention.However,due to the characters of photovoltaic generation system,photovoltaic generation has the characteristics of variability and uncertainty.And with the large-scale photovoltaic generation integration,it would cause many adverse effects on the safe and stable operation of power system.Nowadays,the rapid development of the energy storage technology has provided a reasonable and effective solution for these problems.Based on that,how to make full use of the technical characteristics of various types of energy storage technologies,optimize the size of the multiple energy storage system,and improve both the capacity of photovoltaic power utilization and the economical and stable operation of power system is a serious problem that needs to be solved.Firstly,this paper conducts a modeling analysis of the photovoltaic output power.Based on the probabilistic characteristics of photovoltaic generation system,the scenario analysis method is used to describe the photovoltaic output power's variability,and a variable weighted K-means clustering algorithm based on Huffman tree is presented.By using this clustering algorithm to the photovoltaic generation's scenarios generated by the Latin Hypercube Sampling,it improves the clustering quality effectively.Secondly,this paper introduces the current mainstream energy storage technologies,and several energy storage technologies which are wildly used in power system with photovoltaics,are analyzed in details.After the technical and economical comparison of several energy storage technologies,a feasible composing scheme of the multiple energy storage system is proposed.And this paper chooses battery-super capacitor storage as the composing scheme of the multiple energy storage system.Then,according to the power allocation problem of the multiple energy storage system,a SOC feedback control strategy for the multiple energy storage system is proposed in the paper.The initial output power of the two energy storages is obtained by using the moving average filter method,and the battery energy storage's SOC is introduced to make feedback adjustment.After that,the super capacitor storage's SOC is introduced to make second adjustment of the output power to optimize the operation of the multiple energy storage system and improve the reliability and economy of the multiple energy storage system.On this basis,by setting the least annual cost of power system as the objective function,this paper proposes a model for calculating the optimal capacity of the multiple energy storage system.And the proposed model in this paper is verified by a test system.At last,according to the optimal capacity problem of the multiple energy storage system when it takes into account the virtual energy storage,this paper takes the air conditioning load as an example,and proposes a model of the virtual energy storage based on its characteristics.After that,considering the thermal balance constraints of the air conditioning load and the effects of human thermal comfort,an optimal sizing model of the multiple energy storage system is established in the paper,and the results of the test system verify the economic and technical effectiveness of the proposed model.Furthermore,the virtual energy storage's positive significances for power balance of power system are analyzed deeply.Last but not least,the paper can provide a theoretical and technical support for research on optimal capacity of the multiple energy storage system. |
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