A MILP framework for electricity tariff-choosing decision process in smart homes considering ‘Happy Hours’ tariffs

Abstract

Nowadays, electricity end users can choose among a huge variety of different electricity plans on a deregulated energy market. The wide variety of tariffs besides the advent of novel agents like smart consumers and prosumers, are becoming the tariff-choosing process more complex. This paper proposes a MILP optimization framework which aims at facilitating this task. More precisely, the main endings of the developed framework are: (i) determine the most suitable tariff for smart consumers and prosumers based on historical consumption data, (ii) determine the optimal hours to be hired for a so-called ‘Happy hours’ tariff plan. In addition, other useful results can be directly obtained from the developed tool. The developed approach carries out a MILP optimization framework for optimal scheduling a series of flexible appliances through various characteristic days obtained from clustering historical collected data. This process is repeatedly executed for the different tariff options and, finally, the most attractive one is selected. A case study on the Spanish retail market for a benchmark prosumer environment is used for showing the capabilities of the developed framework.