A Metaheuristic Approach to Evaluate Long Term Marginal Prices and the Impact of Uncertainties and Regulatory Decisions

• Type: Article in International Conference Proceedings Book
• Date: 2000

Authors

Teresa Ponce de Leão (Author) FEUP; João Tomé Saraiva (Author) FEUP

Conference proceedings International

Title: Proceedings of the 6th PMAPS - Int. Conf. on Probabilistic Methods Applied to Power Systems

Pages: 1-8

6th PMAPS - Int. Conf. on Probabilistic Methods Applied to Power Systems

Other information

Abstract (EN): In recent years utilities went through great changes due to the implementation of competition mechanisms. This move is progressively decoupling the flow of energy from the flow of money with the emergence of distribution wiring companies and retailers. This separation implies the identification of costs of the distribution wiring sector, the adoption of regulatory policies, the implementation of incentive schemes to improve the quality of service and the preparation of tariff schemes to remunerate the use of networks. The driving forces directing the tariff selection problem are the economical efficiency, the simplicity and transparency. Tariffs should also be used to transmit signals in order to optimize the use of networks. In this scope, Marginal Pricing is considered as the most transparent and fair approach to assign costs to the users of the system. Due to the investment problem, the optimization formulation used to compute long term Marginal Prices has discrete nature with the inherent solution difficulties. In the approach presented in this paper we formulate a multiobjective expansion planning problem integrating fuzzy models to represent loads. We adopted Simulated Annealing to solve this combinatorial expansion planning problem, leading to the computation of average nodal optimal marginal prices of distribution networks. At the end of paper the proposed methodology is illustrated with a case study based on a 15 kV Portuguese distribution network.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 8