An interactive energy management method for users of AC/DC hybrid microgrid system

Abstract

An interactive energy management method for users of an AC / DC hybrid microgrid system, comprising the following steps: S1. Obtaining data of the AC / DC hybrid microgrid system; S2. Calculating the power between the electricity generated by photovoltaic cells and the load demand of power users Difference: dP=P PV -P LD , if dP≥0, execute step S3, otherwise execute step S4; S3. Use photovoltaic cells to provide power for power users, and transfer excess power to the large power grid to obtain economic benefits, and end; S4. Consumption EC for grid power purchase grid ; S5. Obtain the consumption EC discharged from the battery by the power user at this time grid ; S6. Judging the consumption EC of electricity purchased from the large power grid grid and consuming EC from battery discharge grid size, if the EC grid Greater than EC grid , then use photovoltaic cells to supply power to power users, if EC grid less than EC grid , the large power grid is used to supply power to power users, and it ends. The invention selects a more favorable power supply mode for power users by comparing the consumption of large power grids and batteries, so as to ensure that the power users can obtain better economic benefits.

Description

Technical field [0001] The present invention relates to the technical field of cross-DC mixed micron grid in the field of intelligent grid, and in particular to an interactive energy management method of a non-DC mixed microgrid system user. Background technique [0002] In recent years, in order to reduce the dependence of electric supply on fossil energy, renewable energy technologies such as carbon emissions, solar photovoltaic power generation technology, wind power technology, and other renewable energy technologies are applied to the microgrid. As a small and medium-sized distribution system in a region, the microgrid combines renewable energy, energy storage devices, and energy conversion devices to improve the flexibility, reliability, and energy efficiency of the power system, and improve the service of power users. quality. [0003] Traditional microgrid includes AC microgrid and DC microgrid, and they still have some problems in engineering practices. If the cost of co...

AI Technical Summary

Problems solved by technology

[0005] Existing methods for microgrid energy management are mostly based on energy scheduling from the perspective of reducing the operation and maintenance costs of the entire system, and linear programming optimization methods are often used to solve the problem, which requires the use of complex numerical calculations to obtain energy scheduling solutions; the existing technology is mainly for AC The microgrid or DC microgrid is deployed separately, and the energy management method of the hybrid microgrid is less considered, and the existing technology rarely considers the energy loss and conversion efficiency of AC-DC conversion

In addition, from the perspective of smart grid interaction, the existing energy management methods focus on the operation and management of the large grid side, which is not conducive to energy scheduling involving power users participating in the system, and is not conducive to providing users with better service quality

[0006] Investigating existing patents on energy management methods in microgrids, Chinese patent application CN2016110590061 (publication number CN107039975A, a dynamic photovoltaic microgrid energy management method), proposed an energy scheduling method for distributed energy systems based on neural network prediction , did not consider the energy loss during the AC-DC conversion process, nor did it consider the interaction between the power grid supply end and the power user; device), which focuses on the interaction of power supply-grid-load, and mainly optimizes the operation of the microgrid, and does not involve the energy dispatching problem under the architecture of the specific AC-DC hybrid microgrid; Chinese patent application 2017103054613 (public number CN106953362, grid-connected The energy management method and system of small microgrid), considering the operation and maintenance cost of the microgrid, using the particle swarm optimization algorithm to solve the optimal energy management method, but it requires relatively high computer performance, and the particle swarm optimization algorithm is easy tends to converge locally

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