Dispatch Methodology Research Articles

An approach to on-line power dispatch with ambient air pollution constraints

An on-line optimal environmental/economic dispatch methodology for electric power generation is developed in this paper. Aside from the conventional economic dispatch, constraints on air quality (such as those specified by the U.S. Environmental Protection Agency) are added to the minimum fuel cost problem. Using the integrated Gaussian puff model based on the statistical turbulent theory, rapid dynamic features of pollutant dispersion and its forecast surrounding the plants are emphasized. By applying a convex programming algorithm repeatedly, a set of marginal environmental imposts for the power plants at different times are obtained. Such imposts are incorporated with the fuel cost in the ordinary short-term economic dispatching program to indirectly account for the environmental impact of power generation on the quality of the ambient air. The approach is specifically taken to have little modification for existing economic dispatch programs and be implemented for real power networks. The proposed approach has been simulated in a power system with three plants and three monitoring points.

Real-Time Urban Power Dispatch with Ambient Air Quality Constraints

A power dispatch methodology for urban utility company facing ambient air quality constraints is developed. This approach consists of 1) a real-time air dispersion model for the urban area and its surrounding region, 2) a fuel minimization procedure which will generate a schedule to satisfy the demand and the constraints on pollution concentration. Forecast meteorological data and ambient air quality information are assumed available for the procedure.

A cost effective security dispatch methodology

This paper deals with the problem of formulating dispatching algorithms which must trade off power system operating cost with system security effects. Decision theory was used to structure optimization algorithms which dispatch a power system in accordance with different security strategies. The strategies themselves are dictated by how one wishes to treat probabilistic load variations and contingency events. The chief value of this research lies in providing an approach to unifying the techniques of stochastic power flows, contingency analysis and constrained optimization.