Research And Implementation Of Power Demand-Side Response System Based On CrowdSourcing

With the rapid development of the economy and the continuous increase in electricity demand,the situation of power supply-demand imbalance caused by insufficient power supply is becoming more common.In the past,the solutions mostly involved macro-level regulation by the government and power companies to optimize power supply,while ignoring the commodity nature of electricity.Recent years,the Chinese government has been promoting the market-oriented reform of the electricity sector,with one goal being to use market mechanisms to match supply and demand,and improve the efficiency of electricity production and utilization.As the electricity market trading system continues to improve,more and more demand-side response market regulatory mechanisms are being gradually established,such as peak and valley pricing,tiered pricing,and interruptible load regulation projects.However,there are still some problems with demand-side resources participating in electricity market transactions,such as inadequate channels,high response uncertainty,poor reliability,and high regulation costs of power company,which constrain the full potential of demand response resources.The demand response crowdsourcing model proposed and established in this study combines the concept of crowdsourcing with demand-side response.A demand response crowdsourcing system was designed and implemented to encapsulate the participation of demand-side users in electricity market transactions as demand-side response crowdsourcing tasks.This provides a smooth channel for demand-side users to participate in electricity market transactions,while utilizing the crowdsourcing model to coordinate their behaviors,reducing the uncertainty of demand-side users’ participation in electricity market transactions,and lowering power company regulation costs.It has achieved the purposes of reducing power consumption,maintaining the balance of power supply and demand,and improving the efficiency of power generation and utilization at the same time.In response to the limited cost control of power companies and the low willingness of demand-side users to participate in demand-side response,this research proposes a multi-objective particle swarm algorithm based on Latin Hypercube Sampling and evaluation integral reset.This algorithm explores the impact of subsidy incentive values on the willingness of demand-side users to participate in electricity market transactions.It optimizes the calculation of subsidy allocation schemes for demand-side response crowdsourcing tasks from a static perspective and helps power companies achieve a higher completion rate and quality of electricity market transaction crowdsourcing tasks within the cost control threshold.With the algorithm,the completion rate of demand-side response crowdsourcing tasks increased by 25.4%,the high-quality rate increased by 30.0%,and the relative profit increased by 29.0%.In response to the problem of uncertainty in demand-side users’ participation,the research proposes utilizing the multi-agent deep gradient strategy algorithm to study the demand-side response crowdsourcing task allocation decision model from a dynamic perspective.This method purposefully invited demand-side users,increased the proportion of effectively distributed demand-side response tasks,helped to alleviate the burden on the demand-side response management system,improved the efficiency of demand-side response crowdsourcing task completion,and enhanced the certainty and reliability of demand-side user participation in electricity market transactions.With the algorithm,the completion rate of demandside response crowdsourcing tasks increased by 16.04%,and the relative profit increased by 10.91%.Furthermore,by integrating the aforementioned models and algorithms,the research designs and implements a Web application service for a demand-side response crowdsourcing system based on crowdsourcing concepts to provide support for power company users and demand-side users.