Swarm Intelligence to the Solution of Profit-Based Unit Commitment Problem with Emission Limitations

Abstract

As the electrical industry restructures, many of the traditional algorithms for controlling generating units need modification or replacement. In the past, utilities had to produce power to satisfy their customers with objectives to minimize costs, and all demand/reserve was met. However, it is not necessary in restructured system. In the restructured environment, generation companies (GENCOS) schedule their generators with objective to maximize their own profit without regard for system social benefits. This leads to profit based unit commitment (PBUC) problem. One of the main contributions to the emission of greenhouse gases into the atmosphere, which is thought to be responsible on our environment, is through the use of fossil-fuelled power plants. As a consequence of growing environmental concern, governments are acting in the way to regulate greenhouse gas emission. A major step in this direction is the Kyoto Protocol, which is with the objective of “stabilization and reconstruction of greenhouse gas concentrations in the atmosphere at a level that would prevent dangerous anthropogenic interference with the climate system”. However, the recent advent of emission allowance trading has renewed interest in the environmentally constrained UC problem. In the new emission-constrained competitive environment, a GENCO with thermoelectric facilities faces the optimal trade-off problem of how to make the present profit by the management of the energy available in fossil fuels for power generation without excessive emission. Since maximizing profit and minimizing emission are conflicting objectives, a swarm intelligence approach is proposed in this paper to obtain compromised solutions. The binary particle swarm optimization is used to solve the PBUC problem and real-valued particle swarm optimization (RPSO) is used to solve the economic load dispatch which is a sub problem of PBUC. A six generating unit system and a eleven generating unit system have been taken, and the proposed algorithm is applied to solve it for the PBUC with emission limitations. From the comparison of results, the ability of the proposed algorithm is demonstrated in the aspects of solution quality and computational efficiency.