Regional Integraged Energy Optimization Control Methods Based On Edge Computing

Under the background of the increasing shortage of traditional energy sources in the world,the complementarity of multiple energy sources and the coordination of source,storage and load have become an effective way for the economic operation of the power grid.Edge computing technology gives the regional integrated energy system the ability to perform in-situ data transmission,storage,and calculation at the distribution network level,effectively addressing the inherent difficulties of the regional integrated energy system,such as the complex data and high volatility of new energy,to provide new regional energy systems To optimize the scene and direction.Based on the application of edge computing technology,this paper studies the optimization and control methods of regional integrated energy systems.The main work and results are as follows:(1)It is proposed that the characteristics of edge computing match the inherent needs of the regional integrated energy system.The characteristics of edge computing technology such as low latency,high security and low cost are analyzed,and it is found that as a technology that provides communication,computing,storage and perception functions at the edge of the network,it is suitable for the current regional integrated energy system to face equipment interconnection and massive data demand.The advantages of edge computing technology in regional integrated energy system are combed,and the application architecture of edge computing function is proposed.Finally,the practical application of face recognition and identity verification through edge computing proves that edge computing effectively improves the efficiency of the regional integrated energy system in processing local large-capacity data.(2)A load forecasting method based on meteorological factors is proposed.First,the forecasting principles of two load forecasting models,differential moving average autoregressive model and long and short-term memory neural network model,are analyzed.The analysis finds that the two forecasting models have complementary historical information discovery capabilities.Based on the characteristics of edge computing technology that can perceive information in real time and provide instant computing power,an adaptive method of combining forecasting weights using meteorological changes as reference coefficients is proposed,and a method of using real-time data to modify forecasted values is further proposed.Through the example verification,the method proposed in this paper reduces the prediction error.(3)Aiming at the problem that the regional integrated energy system has a flexible topology and it is difficult to carry out overall optimization,the method of using the alternating multiplier method for double-layer distributed optimization is studied.The edge computing technology provides the local area computing power while taking into account the characteristics of multi-region communication transmission.Combined with the edge computing technology’s functional advantages of real-time perception of electric vehicle status and communication scheduling,a distribution suitable for this feature is proposed.Optimization method.The calculation example shows that the result obtained by using the proposed method is close to the centralized optimization result and has practicality.(4)Aiming at the serious problem of three-phase imbalance caused by the access to a large number of distributed equipment in the regional integrated energy system,a double-layer adaptive three-phase imbalance treatment method is proposed.First,the interaction between edge computing equipment and energy storage equipment in the integrated energy system is studied.According to the principle that the three-phase unbalance of the regional integrated energy system is the load unbalance,an outer layer optimization model aimed at reducing the three-phase load unbalance is proposed.On this basis,the overall charge and discharge strategy of the energy storage device obtained by the outer layer optimization is constrained,and two search algorithms of greedy algorithm and A * algorithm are used to optimize and reduce the call time of the energy storage device.At the same time,an internal and external data interaction mechanism was established to give a reiterated calculation process for the possible situation that the internal energy storage device could not respond immediately,which improved the adaptability of the method.Analysis of calculation examples shows that this method can effectively reduce the three-phase unbalance of the system,thereby reducing network loss and voltage deviation,and improving the power quality management level of the system.Finally,the research contents of the full text are summarized,and the future is expected to rely on the improvement of the computing power of edge computing chips,and the refined load forecasting and demand response modeling of the integrated energy system to further improve the level of regional integrated energy system optimization and regulation.