Model Based Simulation Study on Corporate-wide Load Dispatch Optimization with Pollution Control

摘要

With the popular utility deregulation and more stringent regulations on power plant pollution, economically scheduling and operating power generation from the corporate level has become evidently important. In addition to the fact that load forecast and production scheduling are more dynamic at the corporate level, each boiler unit at the plant level also has to face the challenge of reducing exhaust gas pollution. In coal-fired units, the task normally boils down to reducing NO{sub}x, SO{sub}2, and opacity levels below certain limits mandated by the Environmental Protection Agency. These limitations can be normally translated to NO{sub}X or SO{sub}2 control setpoints during each units daily operation. Significant reduction in pollutant level can bring in credit (in term of dollar amount) for the company that directly leads to financial savings. However, pollution control inevitably incurs cost. For a power company with multiple boiler units, it is often difficult to determine the load dispatch profile, and also specify the optimal pollutant control levels for all of the different units, such that the overall material and maintenance cost is minimal, while the environmental pollution constraints are also met at the same time. To solve these two coupled objectives, our paper will present a study result on the optimal determination of load dispatch and pollution control setpoints in a multi-units environment. A simulation model is developed to characterize the cost effect caused by regulating the pollutant control setpoint for each boiler unit for a different load dispatch pattern. A strategy is then proposed to determine the optimal load profile and pollutant control setpoint for all boiler units in consideration. The optimization can be performed over an interested prediction horizon. The user can use the model to simulate the optimization result for different kind of production scenarios. The power company decision maker benefits from this model based optimization simulation by knowing better the potential of the cost saving for a given amount of electricity generation while respecting all pollution regulation constraints. Existing data from real plant operations will be gathered and compiled to support a case study for this approach.