5results about How to "Reduce network loss" patented technology

The invention relates to the technical field of power system safety, and provides a power distribution system safety operation optimization method and system based on low inertia. The invention discloses a power distribution system safe operation optimization method based on low inertia. The method comprises the following steps: constructing an evaluation model based on a minimum inertia demand by taking minimization of the total operation cost of a system as an optimization target; under a set constraint condition, solving the evaluation model based on the minimum inertia demand by using a grey wolf algorithm to obtain a minimum inertia demand value at each moment; in the process of searching the minimum inertia demand value at each moment, the grey wolf algorithm adopts a convergence factor to determine a search area; the convergence factor is represented as the fractional order power of the ratio of the difference value of the maximum number of iterations and the current number of iterations to the maximum number of iterations. Response reliability of the system to sudden disturbance can be improved.

This invention proposes a two-stage optimization method for distribution networks integrating electric vehicles (EVs) and distributed generation. In the first stage, an orderly scheduling of EVs is achieved by establishing a user participation dispatch probability model and a dynamic electricity price model considering load. The optimized EV load is then superimposed onto the distribution network reconfiguration optimization model in the second stage. Finally, network reconfiguration and distributed generation output are used to reduce network losses and node voltage deviations across the entire distribution network. The proposed method reduces peak-to-valley load differences. Considering user participation rates, it not only reduces user charging costs but also improves node voltage levels and reduces network losses.

The invention relates to the technical field of power distribution network optimization control, in particular to a power distribution network collaborative optimization control method fusing cable planning and charging load, which enables a planning scheme and an operation strategy to adapt to source load fluctuation in advance by constructing a photovoltaic and charging load probability model, and enables the planning scheme and the operation strategy to adapt to different scenes. A cooperative scheduling strategy of a transformer, a reactive power compensation device and a charging load is optimized and formulated day by day, network-source-load active cooperation is realized, network loss is reduced, equipment utilization efficiency is improved, cable investment cost and long-term operation cost are optimized in a unified manner, a scheme with the lowest comprehensive cost in the whole life cycle is automatically screened out, and the system is suitable for large-scale popularization and application. Long-term economic loss caused by traditional planning and operation splitting is avoided, full-period verification and extreme working condition testing are carried out on the optimal cooperation scheme through digital twin simulation, safety, economic and performance indexes are quantitatively evaluated, an optimization-verification decision closed loop is formed, the scheme is ensured to be feasible, and the implementation risk is reduced.

The application provides a micro-grid planning and designing method, comprising: obtaining historical load and voltage of a power distribution network node and historical load and module performance parameters of each micro-grid; inputting the historical load and voltage of the power distribution network node into an outer power distribution network operation control model to obtain upper and lower limits of exchanged power of each micro-grid and the power distribution network and a first optimal power curve; inputting the upper and lower limits of exchanged power of each micro-grid and the historical load and module performance parameters of each micro-grid into each inner micro-grid optimization configuration model to obtain the number of each module of each micro-grid and a second optimal power curve of the access point of each micro-grid and the power distribution network; comparing the first optimal power curve and the second optimal power curve corresponding to each micro-grid to determine the number of each module of each micro-grid; and the implementation of the application can simplify the micro-grid planning and designing, procurement, manufacturing and assembly process, improve the safety and reliability of the micro-grid and the power distribution network, improve the comprehensive utilization rate of internal energy of the micro-grid and reduce the operation network loss of the power distribution network.

The invention discloses a park micro-grid regulation and control system and method based on a fusion terminal. The system comprises a micro-grid management and control system and the fusion terminal. The method comprises the steps that a fusion terminal collects and preprocesses multi-source data; the micro-grid management and control system receives the real-time operation state data uploaded by the fusion terminal, constructs a multi-target optimization model for optimization, and constructs a full-dimensional constraint condition; the micro-grid management and control system executes multi-target optimization scheduling to generate a regulation and control strategy; and the fusion terminal issues and executes the regulation and control instruction, and carries out closed-loop feedback adjustment at the same time. Multi-protocol data fusion is realized through the fusion terminal, a'source network load storage and charging 'island is broken, and global + real-time regulation and control are realized through cloud-edge collaboration; through multi-objective optimization scheduling, the operation cost is effectively reduced, the network loss is reduced, the new energy consumption rate is improved, the capability of coping with distributed energy fluctuation of the micro-grid is enhanced, and the operation reliability of the system is improved.