Midterm generation planning in competitive markets for electrical energy and reserve using a linear programming algorithm

Due to the deregulation of the electricity industry, generating companies are exposed to price uncertainties in their planning process. On the other hand, companies can benefit from the opportunity to enter new markets, e.g. markets for reserve. Hence, tools for generation and trading planning must be able to meet the new demands of taking both the uncertainties and new marketing opportunities into account. However, the growing complexity of the planning process leads to significantly growing computation times, especially for large generating systems. Thus, the modeling accuracy that is necessary to achieve an adequate quality of results in an acceptable computation time for practical application has to be discussed. In this paper, an algorithm based on Linear Programming (LP) is presented that takes into account the provision of reserve by thermal units in the state of operation. A comparison to an LP algorithm disregarding the provision of reserve and an optimization method using Lagrangian Relaxation, which provides a high modeling accuracy, is performed.