2results about How to "Improve Load Forecasting Accuracy" patented technology

The invention relates to the technical field of centralized heating, in particular to a heat supply pipe network dynamic balance adjusting system based on the Internet of Things, which comprises a sensing layer, a network layer, a control layer and an execution layer, and is characterized in that the sensing layer acquires parameters such as pipe network pressure, temperature and flow through a low-power-consumption sensor in a full-link manner, and transmits the parameters to the network layer through a LoRaWAN protocol; the network layer preprocesses data through an edge gateway and realizes encrypted transmission by means of 5G; the control layer integrates heat supply load prediction, particle swarm optimization and a self-learning algorithm, and accurately generates an adjustment instruction; the execution layer drives the electric adjusting ball valve to complete opening adjustment, and closed-loop control is formed. The flow deviation rate can be controlled within + / -4%, the indoor temperature fluctuation is smaller than or equal to 0.5 DEG C, energy consumption is reduced by 15%-20%, remote intelligent operation and maintenance are supported, the system is suitable for various scenes such as conventional residential quarters, large commercial complexes and old communities in cold regions, heat supply balance and energy saving performance are effectively improved, and application and popularization value is remarkable.

The application provides a kind of GAPSO algorithm-based power station load tracking method, including data acquisition and preprocessing, and related data of power grid and power station are collected and processed;A power grid load forecasting model based on GAPSO algorithm is constructed, variables are determined, and an optimized neural network is constructed;The charge-discharge strategy of energy storage power station is optimized, the objective function is established and solved;Real-time scheduling and response are carried out, data monitoring, decision-making and adjustment of power station state are carried out;Multi-objective optimization adjustment is carried out, function is constructed, solved and continuously improved.The application improves the load forecasting accuracy, optimizes the power station operation strategy, enhances the real-time scheduling and response capability, realizes the multi-objective comprehensive optimization, effectively improves the operation efficiency and adaptability of energy storage power station in power system.