Two Stage Approach to Optimize Electricity Contract Capacity Problem for Commercial Customers.

The electricity tariffs available to Polish customers depend on the voltage level to which the customer is connected as well as contracted capacity in line with the user demand profile. Each consumer, before connecting to the power grid, declares the demand for maximum power which is considered a contracted capacity. Maximum power is the basis for calculating fixed charges for electricity consumption. Usually, the maximum power for the household user is controlled through a circuit breaker. For the industrial and business users the maximum power is controlled and metered through the peak meters. If the peak demand exceeds the contracted capacity, a penalty charge is applied to the exceeded amount which is up to ten times the basic rate. In this article, we present a solution for entrepreneurs which is based on the implementation of two stage approach to predict maximal load values and the moments of exceeding the contracted capacity in the short-term, i.e., up to one month ahead. The forecast is further used to optimize the capacity volume to be contracted in the following month to minimize network charge for exceeding the contracted level. As shown experimentally with two datasets, the application of multiple output forecast artificial neural network model and genetic algorithm for load optimization delivers significant benefits to the customers.