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Ferroalloy Plant is the energy-hungry factory, it’s main equipment used for producing ferroalloy is submerged arc furnace. The energy smelting process needed mainly comes from electrical energy, electrical energy is converted into heat energy to melt furnace burden. The different furnace condition needs of different electrical energy, electricity requirements in different furnace condition can be met by power supply system, which directly affect the smelting speed, product quality, energy consumption and energy losses, etc. Therefore, determination of reasonable power supply system in view of the different furnace condition, providing reasonable secondary voltage and current value, for ferroalloy plant reasonable control smelting time, increase productivity and alloy quality, to achieve the purpose of saving energy and reducing consumption has important significance.The paper on the basis of consulting a large number of relevant data and literatures, summarizes development present situation and development trend of the submerged arc furnace, applications of neural network in metallurgical industry as well as mechanical equipment, smelting process of submerged arc furnace and some treatment on the abnormal situation. With No.801 furnace of Sinosteel Jilin Ferroalloy Co., Ltd eighth branch as research background, the analysis of the smelting principle and process of the submerged arc furnace, based on energy balance on supply energy (electric energy and chemical heat release) and demand energy (consumption and wastage energy) establish the power input model, and determine the required total electric quantity; Based on the electrode position have judgment on three smelting stage of submerged arc furnace producing ferroalloy(including arc ignition、charging stage, melting stage, refining stage). But, because of the electrode position scarcely changed in the refining stage, can’t have accurate judgement of the end of the refining period, so the paper forecasting molten iron temperature and carbon content of refining period by using neural network predictive model, when molten iron temperature and carbon content meet the technological requirements, refining period is over, namely the end time. The simulation results verify the validity and the accuracy of the models. Then put forward various power input method in accordance with the electricity demand of each stage. Theoretically propose a new power input method:In meeting the constraint condition that there is the smallest loss amount in power supply in unit of time, determine voltage values at all stages of submerged arc furnace, which are combined with electricity demand of all phases, it is concluded that the current value. Lastly, the energy input optimization platform is established to realize the proposed method by JSP technology.Through the simulation analysis, validation proposed energy input method can shorten the time of smelting -arc furnace, reduce the consumption. And provide the theoretical basis for realizing that saving energy and reducing consumption in the production process of submerged arc furnace.
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