2 results about "Bacteria foraging algorithm" patented technology

The present application relates to a kind of power transformer fault diagnosis method and system, storage medium.It includes the following steps: the content of each gas in the oil of power transformer obtained by oil chromatographic analysis, obtains original data;Original data is preprocessed, constructs feature vector, and is divided into training sample set and test sample set;Support vector machine is constructed based on training sample set;Support vector machine is optimized by improving bacterial foraging algorithm, and support vector machine fault diagnosis model is obtained;Test sample set T2 is input to support vector machine fault diagnosis model and carries out fault diagnosis.The present application combines data analysis diagnosis technology and intelligent algorithm, constructs support vector machine by obtaining data through oil chromatographic analysis, finds the global optimal parameter of support vector machine by improving bacterial foraging algorithm, improves the accuracy of diagnosis.

This invention provides a method, apparatus, and equipment for the coordinated optimization of power generation stations and diversified energy storage. The method includes: modeling components of a hybrid power system to quantify the indirect costs of intermittent renewable energy; constructing a multi-objective optimization model incorporating economic operating costs, pollution emission control, and voltage safety and stability; establishing a set of relevant constraints, designing a tiered energy storage dispatch strategy, and performing multi-scale power balancing; and solving the multi-objective optimization model using an improved bacterial foraging algorithm to determine the optimal power generation plan. This invention achieves an optimal power generation plan that balances economic, environmental, and stable operation requirements, effectively mitigating renewable energy fluctuations and solving the problem of existing technologies' difficulty in achieving multi-objective coordinated optimization. It provides an effective technical approach to improving the overall operational performance of novel hybrid power systems.