Optimal Operation Mechanism Of A Smart Microgrid Based On Dynamic Demand Response

With the continuous development of human society,the demand for energy continues torise,and the deep exploitation of fossil energy has brought about an ever-increasing energy crisis and a sharp deterioration of the environment To solve this problem,people are eager to seek renewable energy-friendly energy as a new way to supply energy to replace traditional fossil energy.To this end,distributed power generation technology based on clean energy has received extensive attention and rapid development worldwide.Renewable energy sources such as wind and solar energy are mostly distributed energy.Compared with traditional fossil energy sources,distributed renewable energy is small in scale and close to the load point.By utilizing modern power electronics technology and distributed power generation tech-nology,the microgrid has become the moost important utilizing form of distributed renewable energy by fully taking the advantages of low-cost investment and low environmental impact of renewable energy.The microgrid is a small power grid,which can be coordinated and con-trolled by the distributed power generation unit and the energy storage equipment The internal power demand of the microgrid can be balanced in real time in the island operation mode.In the grid-connected mode,there is power exchange between the microgrid and the main network.In the island mode,the research on microgrid mainly focuses on the safe and reliable operation of the microgrid.In the grid-connected mode,its operational stability and power demand can be guarganteed.Therefore,the main concern in the grid-connected mode is the operational eco-nomic indicators.Research on the optimization of microgrid operation has become the focus of research in recent years.In this paper,for a typical microgrid,the demand side response coordinated by multiple time scales is used to ensure the balance between power supply and demand within the micro-grid,which improves the renewable energy consumption rate and the operation profit of the microgrid.The operation mechanism under the electricity market model is optimized The following work was carried out:(1)This paper firstly expounds the development history and development status of micro-grid construction and comprehensively summarizes the academic research status of microgrid planning and operation at home and abroad.Secondly,the current domestic and internation-al electricity market development have been summarized.The operation mode of the smart microgrid in the electricity market in the future is analyazed and discussed.(2)The basic mechanism of the smart microgrid is analyzed,and its energy supply system and load side are modeled.The basic principles and mathematical modelling of system equip-ment such as wind power generation system,photovoltaic power generation system,diesel en-gine power generation system and energy storage system are mainly studied.The operational characteristics of the large time-shiftable load and the interruptible load within the smart mi-crogrid are analyzed.This kind of responsive load participates in the demand side response is mathematical modelled,(3)The random nature of renewable energy causes microgrid operators to maximize the renewable energy consumption rate while ensuring a balance betwen supply and demand a huge challenge.In order to effectively improve the renewable energy consumption rate and the of microgrid,a two-stage optimization mechanism,named the operation optimization method of multi-time scale coordinated control,is proposed.In the first stage,profit of the microgrid operator and the time-of-use electricity price are regarded as the two decentralized optimization objectives.The particle swarm o ptimization algorithm is used to optimize day-ahead start-stop optiml unit commitment of the smart microgrid.The interior point method is used to optimize the time-of-use price which encourages users who are time-shifted to plan and adjust the next-day load.In order to fully absorb the renewable energy in the smart microgrid and improve the profit of the smart microgrid operator in the electricity market.In the second stage,the ultra-short-term forecasting of the balance of power supply and demand is carried out to schedule interruptible load and electric vehicle to participate in demand side response.Simulation studies have been carried out to verify the superiority of the operational mechanism.The renewable energy consumption rate and the average daily profit of the smart microgrid are both improved to a certain extent.(4)Due to the fast charge and discharge speed,electric vehicles have the potentiai to pro-vide frequency regulation service when taking ppart in the frequent regulation market.This paper proposes an optimization strategy based on the reinforcement learning algorithm for electric ve-hicles charging and discharging strategies.The overall goal is to respond to the regulation signals precisely sent by the operator of the main grid in the real-time frequency regulation market by controlling the electric vehicles in the parking lot.In order to achieve this,a reinforcement learn-ing algorithm is used to optimize the charging and discharging strategy of the electric vehicle,so that the electric vehicle aggregator can reasonably allocate the electric vehicle frequency adjust-ment power and the reference charging power in response to the adjustment signal to obtain the optimal adjustment performance.Based on the data of the PJM electricity market,simulation results show that the control performance is excellent under different kinds of frequency regu-lation signals,and the validity and feasibility of the charge and discharge strategy optimization method are verified.