Decision-Making for Crisis Management of Power Distribution Networks

Abstract

1 IntroductionPower distribution network is the endpoint of long, expensive process of power generation, transfer and distribution. The task of this sector is to deliver generated power to subscribers and consumers. In fact, in case of failure incidence in distribution sector, all the expenses to generate and transfer power would be fruitless. On the other hand, due to extent of power distribution network, it is subject to various adverse events. Many of these events occur because of network exhaustion or unpredictable events such as atmospheric ones and unexpected events. Therefore, network reliability is a crucial parameter in distribution network exploitation. On the other hand, occurrences such as storm, flood, and earthquake results in simultaneous blackouts in distribution network. In turn, these blackouts results in subscribers` dissatisfaction as well as increase in undistributed energy of distribution sector that is considerable in terms of economic. Decision-making in such situation is a difficult and complex process that should be taken by network managers to decrease failure time and undistributed energy. Since facilities are restricted during crisis, decisions should be taken considering several parameters and attempts to find optimum. Currently, crisis management decisions are made in distribution sector practically without using advanced software models, while using existing facilities such as advanced computer models and algorithms blackout times and undistributed energy can be reduced to the lowest. In the present article, different types of decision-making models during crisis are examined and a model is presented using Excel spreadsheet to show their performance.2 Necessity of Using Decision-making ModelsDecision-making models can be traced back to pre-IIWW periods. At that time, many mathematicians like Kolmogorov began using linear decision-making models. After IIWW, with complexity of decision-making issues, operational research was introduced as an effective method to solve very complicated issues [2]. In today world, company managers are faced with complex challenges. At the moment, many of successful companies in various fields try to implement different processes in format of various decision-making models. Currently, different issues in social, martial, and economic issues are solved using decision-making models. From environment pollution control to increase in airline profitability, all are achieved through precise computer modeling. Now, there is no successful company not using different modeling method for its decisions [1]. Power distribution companies due to their important role is the field of country`s power supply, can benefit from these models to significantly increase their performance. In this article, only one example of efficient decision-making models during crisis is presented, though there are many models can be used in distribution companies. Major benefits of using decision-making models are:1. A marked decrease in blackout time2. Decrease in undistributed energy, and thus economy saving3. Decrease in expenses of fixing outage and efficient use of existing facilities4. Increase in subscribers` satisfaction5. Decrease in tension and stress in workplace, and thus decrease in accidents during workIn fact, it can be said that decision-making models are powerful tools guiding managers during crisis. In this article, a simple model of linear planning is introduced to make an optimal decision during crisis. Since proposed model is solved using Excel software in Windows it can easily be integrated into other network management software such as ENOX or other software. Using proposed methods and adding them to network management software can incredibly increase network management capabilities.3 Decision-making Models and Their ImplementationDecision-making models are divided into two categories: 1) deterministic models in which all parameters are assumed deterministic, and 2) probability models that are provided in uncertain situation [3]. …