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Comprehensive model of corporate control of energy


Management, as much as possible reduce the number of control variables and the number of constraints, but allows the smallest sub-objective function describes the energy relationship between the base corresponds to the actual process that works to achieve the basic goals and objectives consistent with the theory. Constraints can be re-written as: fal1XI + al2x2 + ... ... s (≥) bl {a1lxl + a2 + ... ... s (≥) b2 (3) [... ... ... ... ... ... in the actual modeling process, the application of different methods, availability of different forms of models,abercrombie marseille, model complexity, constraints, form of expression, accuracy and complexity of the solution are different. Using linear programming, the constraints factor and the process parameters in the model,abercrombie france, coefficient were linear, often quantitative treatment, the resulting model and constraints on the model of objective control, easy to implement from the engineering. Subsystem energy minimum target control model: Minz = clxl + c2x ~ O-c3x3 + ... ... (4) falIXl + al2x2 + ... ... s (≥) bl {a21xl + a22x2 + ... ... s (≥) 1) 2 (5 ) L ... ... ... ... .... . Among them, (4) is the smallest objective function, the simultaneous expression (5) is the constraint equations. Minimum objective function for energy optimization, use a variety of visual programming language for numerical solution, such as visual programming using VB language to control the operation of the interface model,sac hermes birkin, through the controls, forms, menus and program code to establish sub process, function to implement the process. Subsystem optimization process: (1) the preparation of the objective function of the subsystem to achieve the minimum energy solution of the VB program can also be used to solve VBscript scripting language to write programs, and commissioning. (2) the number of input constraints. (3) the number of input control variables. (4) Enter the minimum objective function Minz = clxl + c2x2 + c3x ... ... (5) input constraint equations (2) the corresponding matrix element of the augmented matrix of the data. (6) in order to solve. Obtain the optimal solution, which gives the best value for the control variables, the control variables take the best variable group, the optimal objective function value of z to determine the data output. The number of sub-systems form a large system, in a similar way to establish large-scale systems of energy minimum objective function model, additional large-scale systems of constraints: constraints equations. Further optimization solution, enterprises get the minimum energy consumption and the sub-optimal solution objective function of the minimum energy control target value. A l0 per _ monitoring Chan Jian put down the application of the method in the west of a small business in the ferroalloy been applied, are presented below. The company mainly produces 65 #, 75 # ferrosilicon alloy products, electric two storage capacity of 5000kVA and 1800kVA, including power transformers,abercrombie france, crane, gantry crane, feeding systems, broken systems, boiler room, finished products such as electricity facilities. These electrical equipment, the average working time 16h, products, tons of power consumption of 9570kWh / t, power consumption accounts for 73% of product cost. Energy-efficient model with a systematic method of planning control and production management, through three months of production statistics contrast, reduced power consumption of the product t 9416kWh / t, lower power consumption than the original tonnes of 1.61%. As the ferroalloy plant information management system, inadequate investment, the use of systematic support for energy-saving model control conditions are not ideal, as well as on the factory fan and water pump frequency control transformation of lack of financial resources, leading only to a certain extent, the implementation of systematic control of energy-saving model. Nevertheless, the company's fuel consumption is also included in other comprehensive control and management of the range model, the statistics, the total power consumption from 65% to product cost 63.9%, other 3.6% lower average energy consumption , achieved some energy savings, in order to create efficiency. lI, ≯ ≥ ≤ 0 give an example using the dip-hsiang optimal control model is an integrated energy companies to reduce energy consumption, lower production costs, reduce operating costs in important ways. Companies to ensure completion of the normal production tasks, profit targets at the same time, through scientific, systematic and comprehensive model of control, achieve the overall objective function of the minimum energy targets, so their actual energy minimum. Under normal circumstances, their actual total energy consumption of total energy consumption and corporate objective function value of the total deviation from the idealized, and often have a greater deviation from the optimal control model with integrated energy-saving method of this soft science which can be a better solution issue. Of course, the comprehensive energy saving should also include: an integrated application of new technologies, the establishment of enterprises and efficient dynamic database; best allocation of resources (including human resources); optimal or near optimal use of existing resources. For these enterprises, is a more generalized energy, another on these issues will be explored. (Editor of / Xiao Zhaohui)
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