Congestion Management of a Deregulated Power System Using Fuzzy Logic

Regulated Power System is widely accepted and practised in several countries. The entire electric utility of this traditional system is entirely owned and managed by one organization or commonly the government. The dictation right, monopoly concept and with no third party to ensure the efficiency of the management had caused this structure of industry become less competitive and less efficient. When this problem arises, the solution is not a better set of rules, but a structural change. With the ongoing liberalization of electricity markets, it is now moving towards the era of Deregulated Power System. This is a type of restructuring in Power Industry. The general mechanism of deregulation is to unbundle the Generation, Transmission and Distribution into generating companies (GENCOs), transmission companies (TRANSCOs) and distribution companies (DISTCOs). This unbundled system is very competitive as multiple GENCOs would compete among themselves to supply DISTCOs electric utility through short or long term contracts while the consumers are free to select any GENCOs that provide them with the best service and best price. Therefore, deregulation will be the future of realizing sustainable development at high efficiency. However, in open access environment where the consumers and distributors are free to choose their own generation supplier, transmission congestion is a major concern of this unbundled system. Transmission congestion is the condition where power that flows across transmission lines and transformers exceeds the physical limits of those lines. The main reasons for congestion management are due to the increase demand of electricity usage, the construction of transmission is expensive and the pressure from environmental groups that restrict construction of transmission. The chances of transmission lines getting over-loaded is comparatively higher under deregulated operation because vary parts of the system are owned by different companies and under varying service charges. Several conventional methods were used to manage congestion in transmission line. These methods are Linear Programming Method, Newton-Raphson Method, Quadratic Programming Method, Nonlinear Programming Method and Interior Point Method. The disadvantages of these conventional methods are complex mathematical formulation, unable to solve real-world large-scale power system problems, poor convergence and the system is slow when the variables are large. In recent years, Artificial Intelligence Method is frequently used as it can solve highly complex problems. Fuzzy Logic is one of the types under this Artificial Intelligence Method. Hence, in this paper, Fuzzy Logic approach is implemented for congestion management. This approach deals with approximation rather than precision. The simple rule-based of Fuzzy Logic is using “IF X AND Y THEN Z”. The load flow of the transmission line will be used to model Fuzzy Logic in controlling transmission congestion and tested using IEEE Reliability Test System-1996 (RTS-96). The results showed the congestion level for Weekly Load and Daily Load using the data in IEEE RTS-96. With the congestion level, the price can be further determined by the distributor according to Zonal Pricing Method and Nodal Pricing Method.