Short-Term Planning of Real Electric Power Distribution Systems Using Equivalent Models

Abstract

The short-term planning of electrical distribution systems is a decision-making process that ensures proper performance, system security and guarantees the quality of the power supplied to end users. In the last years, the formulation and solution of this problem has faced great challenges due to modern technologies integration and the final consumer's preferences. To cope with these challenges, sophisticated optimization algorithms are developed to integrate these technologies into the electrical distribution network and provide a high-quality service. Finally, it remains a challenge to formulate a strategy that considers multiple objectives and it satisfies the network needs. In this context, to develop a method to solve the problem is the objective that must be obtained in this research project. From the point of view of mathematical optimization, the difficulty of the problem is increased due to the number of decision variables considered in the mathematical model. On the other hand, one of the limitations of these strategies is the scalability of these formulations when complex distributions networks are analyzed. Therefore, this research project proposes a strategy to reduce these limitations, for which the short-term planning problem will be formulated for equivalent distribution systems. This strategy consists of two steps, in the first the development of a simplification algorithm to represent the complexities of a distribution network in an equivalent system. The second step is to investigate the planning methodology, which should consider multiple planning actions to maximize the efficiency of the network. In the modeling phase, renewable energy-based sources and energy storage systems should be considered, where, the benefits of each technology can be exploited. Inherently, the operation of renewable energy-based sources and the demand consumption of the electrical distribution system present estimation errors, therefore, the formulation should be extended to optimization models based on uncertainties. Considering the development of this strategy, the objective is to obtain a computational tool that can be used to find investment plans applies to large distribution systems, where it will be adaptive and useful for the decision maker and thus improve the operation of the network and ensure the quality of the electric energy supplied. To validate the proposed methodology, cases studies and numerous tests in distribution systems available in the literature should be performed under different conditions to demonstrate the efficiency and robustness of the tool that should be developed.