Energy optimization method of household micro-grid based on Q-learning
A technology of energy optimization and micro-grid, which is applied in the direction of electrical components, circuit devices, AC network circuits, etc., can solve the problems of not being widely used and not suitable for single residential users, and achieve the effect of improving accuracy
Active Publication Date: 2017-03-08
SOUTHEAST UNIV
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Problems solved by technology
However, the following problems generally exist in the existing research: Most of the models use the load aggregator to realize the optimal dispatch of group air conditioners by controlling the start and stop of the air conditioners, but this method is not suitable for a single resident user who can only control the temperature of the air conditioner; Research on air conditioner setting temperature as the goal usually approximates the air conditioner setting temperature as the actual indoor temperature, ignoring the impact of environmental dynamic changes on room temperature; most studies use simplified thermal equivalent parameter models for air conditioners, but Lack of detailed instructions for obtaining room parameters and air-conditioning energy efficiency ratio coefficients in practical applications
However, there are few studies on air-conditioning modeling in household microgrids. How to accurately model indoor air-conditioning, give full play to its demand response performance as a temperature-controlled load, and at the same time improve user comfort and achieve temperature control. Precise control has become the focus of household microgrid energy management research
[0004] The above three problems make the current energy management strategies for air conditioning loads too idealistic, and if they are not resolved, they will not be widely used.
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[0063] The present invention will be further described below in conjunction with the accompanying drawings.
[0064] (1) Establish the model of each unit in the household microgrid
[0065] A typical household microgrid is composed of photovoltaic cells, energy storage systems, and various household loads. The voltage level is single-phase AC 220V. Its structure diagram is as follows: figure 1 shown.
[0066] 1) Photovoltaic power generation system
[0067] Equipped with small photovoltaic cells, users can make full use of solar energy resources, change the passive power consumption mode of users' one-way purchase of electricity from the grid, and feed excess power back to the grid. With the development of new energy, various types of small photovoltaic cells have begun to be used in residents, such as dye-sensitized cells composed of transparent conductive glass, dyes and electrolytes, which are used as window glass, which is both light-transmitting and can be used as batte...
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The invention discloses an energy optimization method of household micro-grid based on Q-learning. Load of air-conditioners is taken as the research key, other controllable loads and energy storage equipment in the household micro-grid are combined, and the method aims at balancing the power utilization cost and the user comfortableness. According to the thermal capacity and thermal resistance of a room and the different models of the air conditioner and on the basis of a thermodynamic model, obtained adaptively in the present stage by utilizing a genetic algorithm, of a present scene, the set temperature of the air-conditioner can be corrected adaptively in a day via Q-learning according to dynamic change of the present scene environment in the application process, and the accuracy of energy management is further improved. Willing of a user is taken into full consideration, the user can select a corresponding energy management mode according to requirements, and customized management of the household micro-grid is realized. The method can be used to improve the scheduling accuracy and practicality of the household micro-grid, and facilitates popular application of energy management of the household micro-grid.
Description
technical field [0001] The invention relates to a Q-learning-based energy optimization method for a household microgrid, which belongs to the field of microgrid energy management. Background technique [0002] Distributed power generation has the advantages of small investment, flexible power generation methods, low loss, and environmental protection. Compared with centralized power supply for peak power loads, it is more economical and effective. The household microgrid is an autonomous network that integrates distributed power sources, energy storage devices, loads and other units and has independent control capabilities. Energy management of household microgrids can give full play to the peak-shaving potential of loads, guide users to use electricity rationally, and improve the economy and grid operation efficiency of household microgrids on the premise of satisfying user comfort as much as possible. At the same time, with the rapid growth of the national economy and the...
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Login to View More IPC IPC(8): H02J3/00G06Q10/04G06Q50/06
CPCG06Q10/04G06Q50/06H02J3/00H02J2203/20
Inventor窦晓波孙帅陆斌吴在军胡敏强
OwnerSOUTHEAST UNIV