Optimal Scheduling of Energy Supply Entities in Home Area Power Network

Abstract

A developing concept of distributed energy resources (DERs) demonstrates high power in-feed from renewable energy sources (RESs). RESs mainly include solar and wind resources. Presently, the problem faces from these RESs, is their uncertain behavior of producing energy. This is due to the reason of varying wind speed and solar irradiations. The RESs can be incorporated at any scale in the power network and can be handled through centralized or de-centralized grid control mechanism. In this paper, we present a model of nano-grid, representing a medium scale smart home. It integrates roof-top photovoltaic (PV) panels, energy storage devices (ESDs) and smart loads along with grid-supplied energy. A cost minimization problem is proposed, that reduces the accumulated cost of energy consumed by a smart home. Hence, we adopt a power scheduling scheme, establishing an optimal strategy of supplying cost-effective energy to the user's load demands. It ensures, i) high utilization factor of installed PV; ii) cost-effective ESDs operations; iii) low-cost infeed from a grid, considering home area power network (HAPN) system constraints. Our scheduling scheme is based on mixed integer linear programming (MILP) framework, providing day-ahead optimal scheduling decisions for various energy supply entities. Simulation results demonstrate the real outlook of our implemented strategy, utilizing a cost-effective optimal blend of distinct energy sources.