Load optimization and control method and system for short-process iron and steel enterprises considering process constraints

Abstract

This disclosure proposes a load optimization control method and system for short-process iron and steel enterprises that take into account process constraints, including the following steps: obtaining enterprise equipment parameters, number of heats, number of castings, duration of processing and transportation tasks of furnaces, and Composition of furnaces; Reconstruct the discrete-time RTN model based on the obtained data, and construct the production constraints of short-process iron and steel enterprises; set the objective function to minimize the cost of electricity purchase, and obtain the production load of the enterprise through the objective function and the solution model of production constraints The optimal control strategy, that is, the specific start and stop times of different individuals in various key electrical equipment. This disclosure accurately combines power consumption and production tasks under the premise of ensuring that the iron and steel enterprise's process restrictions are strictly satisfied, so that the load optimization control strategy formulated with the goal of minimizing the enterprise's electricity purchase cost has practical operability while improving the efficiency of the enterprise. economic benefits.

Description

technical field [0001] The present disclosure relates to the technical field of electric power demand response, and specifically relates to a load optimization control method and system for a short-process iron and steel enterprise taking into account process constraints. Background technique [0002] The statements in this section merely provide background information related to the present disclosure and may not necessarily constitute prior art. [0003] With the continuous increase of the proportion of renewable energy connected to the grid, the volatility and uncertainty of wind power and photovoltaic output will further increase the pressure on power grid peak regulation. In addition, the capacity of new energy transmission channels is insufficient and the development speed of conventional thermal power units is hindered. The traditional "source follows the load" operation mode can no longer meet the flexibility needs of large-capacity renewable energy. In this context...

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Problems solved by technology

The two methods introduced above have certain advantages in process modeling. However, when discussing the parallel operation of similar equipment, the model will become extremely complicated, and may even lead to unsolvable situations.

[0006] In order to more clearly explain the impact of materials, equipment, energy and other factors on steel production activities, the document "ZhangX, Hug G, Kolter Z, et al. Industrial demand response by steel plants with spinning reserve provision [C] / / 2015North American Power Symposium (NAPS), October 4-6, 2015, Charlotte, USA: 1-6" and "Zhang X, Hug G, Kolter Z, et al. Computational approaches for efficient scheduling of steel plants as demand response resource[C] / / 2016Power Systems Computation Conference (PSCC), June 20-24, 2016, Genoa, Italy: 1-7 "Using the method of discrete-time Resource Task Network (RTN) to explore the relationship between material flow and power consumption in the short-process steelmaking process The existing coupling relationship, and adjust the production arrangement in each time period accordingly to achieve the purpose of minimizing the electricity purchase cost of iron and steel enterprises. The main difference between it and the previous two methods is that the equipment elements, materials and energy are included in the category of resources In this way, the risk of the number of processing tasks increasing proportionally with the number of types of equipment is avoided, but the fixed time grid in this method makes the scheduling results obtained when the ratio of task duration to time interval length is not an integer appear certain. Due to the impact of rounding errors, it is difficult for adjacent processes in the production process to achieve a truly seamless connection, especially for continuous production tasks such as continuous casting, which may even be caused by inaccurate handover of front and rear furnaces. Accidents such as equipment damage and product quality degradation

[0007] Therefore, although the current research on load optimization and regulation of short-process iron and steel enterprises has achieved certain results, the existing technical solutions are still not accurate and comprehensive enough to consider the production constraints existing in the production process of iron and steel enterprises, which leads to the formulated load The optimization control scheme does not have engineering practicability and practical feasibility, and cannot guide enterprises to reduce the cost of electricity purchase to the greatest extent by reasonably changing the use time of production equipment

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