A Customized Evolutionary Algorithm for Multiobjective Management of Residential Energy Resources

摘要

Dynamic tariffs are expected to become a relevant pricing scheme in the context of smart grids. In this framework, active management of residential loads can play an important role to optimize the usage of end-use energy resources while minimizing energy cost. This paper presents an evolutionary algorithm to optimize the integrated usage of multiple residential energy resources (local generation, shiftable loads, thermostatically controlled loads, and storage systems) considering a large set of management strategies. Customized solution encoding and operators are developed for different groups of loads. The multiobjective model considers as objective functions the minimization of the energy cost and the minimization of end-user's dissatisfaction associated with management strategies. Results have shown that significant savings can be achieved mainly through demand response actions implemented over thermostatically controlled loads. Savings are also dependent on the end-user's preferences and degree of willingness to accept automated control.