A novel energy service model and optimal scheduling algorithm for residential distributed energy resources

We propose a novel decision-support tool that aims to optimize the provision of residential energy services from the perspective of the end-user. The tool is composed of a novel energy service model and a novel distributed energy resources scheduling algorithm. The proposed model takes into account the time-varying demand and benefit that end-users derive from different services, and assigns the benefit to the energy that realizes the service. The scheduling algorithm determines how distributed energy resources available to the end-users and under their control should be operated so that the net benefit of energy services is maximized based on the energy service models, and their technical characteristics and capabilities. The scheduling is a challenging optimization problem; hence, a heuristic simulation-based approach based around cooperative particle swarm optimization is used. The paper presents a case study where this decision-support tool is used to optimize the provision of desired energy services in a ‘smart’ home that includes a number of controllable loads, energy storage and photovoltaic generation.

▶ End-user benefit from an energy service is higher than the cost of its acquisition. ▶ The demand and perceived benefit from energy services changes with time. ▶ Scheduling of DER can optimize the acquisition of energy services.