Fuzzy Logic
Fuzzy Logic based Controller to improve Demand Side Management
Nivedita Patnaik
Department of Electrical Engineering Indian Institute of Technology, Kharagpur – 721302, India
Abstract Energy demand management or Demand Side Management (DSM) involves actions that influence the pattern of energy consumption by consumers. In this paper a fuzzy logic based approach towards shifting the average power demand of residential electric water heaters has been discussed. Power system demand side management programs are strategies designed to alter the shape of the load curve. This paper targets both customer satisfaction and utility unit commitment savings, based on a fuzzy load model for the direct load control of appliances. Problem Definition Load management is the process of balancing the supply of electricity on the network with the electrical load by adjusting or controlling the load rather than the power station output. For example, the cost of electricity is highest when the air conditioning load is greatest during hot afternoons. Load management programs or DSM programs are programs that intentionally alter the load shape of the customer by deliberate utility (an organisation that maintains the infrastructure for public service) intervention. It is seen that in a typical city, the power consumed is maximum over the 8:00 am to 5:00 pm duration. With the ever increasing demand of electricity, even electric utility companies is faced with overwhelming demand peaks associated with a large amount of power being consumed at the same time. So, electric utility companies come up with price incentives for customers who participate in load management programs. Otherwise, these companies introduce a real time pricing strategy by which customers pay more for the electric power they use during high demand periods and less during low demand periods. Some statistics collected at a typical residential area showed that the electric water heater was the single largest contributor
Nivedita Patnaik
Department of Electrical Engineering Indian Institute of Technology, Kharagpur – 721302, India
Abstract Energy demand management or Demand Side Management (DSM) involves actions that influence the pattern of energy consumption by consumers. In this paper a fuzzy logic based approach towards shifting the average power demand of residential electric water heaters has been discussed. Power system demand side management programs are strategies designed to alter the shape of the load curve. This paper targets both customer satisfaction and utility unit commitment savings, based on a fuzzy load model for the direct load control of appliances. Problem Definition Load management is the process of balancing the supply of electricity on the network with the electrical load by adjusting or controlling the load rather than the power station output. For example, the cost of electricity is highest when the air conditioning load is greatest during hot afternoons. Load management programs or DSM programs are programs that intentionally alter the load shape of the customer by deliberate utility (an organisation that maintains the infrastructure for public service) intervention. It is seen that in a typical city, the power consumed is maximum over the 8:00 am to 5:00 pm duration. With the ever increasing demand of electricity, even electric utility companies is faced with overwhelming demand peaks associated with a large amount of power being consumed at the same time. So, electric utility companies come up with price incentives for customers who participate in load management programs. Otherwise, these companies introduce a real time pricing strategy by which customers pay more for the electric power they use during high demand periods and less during low demand periods. Some statistics collected at a typical residential area showed that the electric water heater was the single largest contributor
References: B.J. LaMeres, M.H. Nehrir, A multiple-block fuzzy logic-based electric water heater demand-side management strategy for levelling distribution feeder demand profile, Electric Power Systems Research 56 (2000). B.J. LaMeres, M.H. Nehrir, V. Gerez, Controlling the average residential electric water heater power demand using fuzzy logic, Electric Power Systems Research 52(3) (1999). 7