Research On User-Side Microgrid Optimal Operation Based On Control For Active Loads

With the rapid development of smart-grid technology and demand response for citizens in recent years, there are more and more space for the development on utilization efficiency and interactive services between the grid and users. Intelligent power is the key to solve the issues in the related field, also is the important part of smart-grid. At the same time, with the popularization of distributed energy in the residential area and the development in intelligent household appliance industry, the way for power consumption in residential side is much more flexible, which also open up a new path for intelligent power. View from the current study, most of the researches of intelligent power technology concentrated on the basic functions such as the development of terminal devices in the system and network communication technology and other hardware functions. However, the issue on how to make the operation of home appliances and energy storage more optimal is still determined by users themselves, which means that the real "intelligent" has not come true. Therefore, it is seriously necessary to explore how to apply the related data such as information on electricity demand, device parameters and requirements of individual users to help users to adjust their energy structure more actively and to plan their electricity consumption more rationally.This thesis proposes an optimized operation strategy based on the control of active loads, and the reasearch object is a user-side microgrid which includes PV, stored energy and intelligent home appliances. The strategy makes optimization specifically according to the characteristics of various types of electrical equipment, ultimately achieving the aim of energy economization and economy.Firstly, this paper introduces the related theoretical basis, including the technology of active load, the contents of demand response and the energy management of user-side microgrid. The technology of active load is the pointcut for intelligent power, and the physical basis of the energy management for user-side microgrid. The content of demand response is the guideline of intelligent power and belongs to the application of the energy management of user-side microgrid. The part of the energy management for user-side microgrid emphatically introduces the functions and features of each module in the system of energy management.Secondly, this paper establishes the user-side microgrid model in detail, including system topology, distributed power and several active loads models which participate in the optimal opreation. Then it proposes a kind of stepwise optimization strategies for different types of load in user-side microgrid. For the thermostatically controlled load with the characteristics of adjustable load, taking an optimizing strategy based on Nash bargaining theory, which means developing the operation plan by analyzing the relationship between the satisfaction and economy for the use of thermostatically controlled loads. For the transferable loads, taking an optimizing strategy which minimizes the electricity cost.Finally, this paper proposes a numerical example to confirm the effectiveness of the proposed strategy, and programs in MATLAB platform. For the optimizing operation of the adjustable loads, genetic algorithm and fmincon function are used to solve its optimizing operation model and comparative analysis for the results is carried out. For the optimizing operation of the transferable loads, we uses the mixed integer programming method to solve its model. Then this paper sets up other optimization in order to make comparison, highlighting the advantages of the strategy proposed here. The result shows that the strategies designed can make analysis quantitatively and dynamically for the economy and satisfaction of the thermostatically controlled loads, and then make operation scheme according to it. Also, the stepwise optimization strategies is helpful to the peak-avoiding for the whole system of user-side microgrid effectively and increasing of income to system operation.