Energy storage day-ahead scheduling to reduce grid energy export and increase self-consumption for micro-grid and small power park applications

Developments in energy storage technology will start to play a prominent role in overcoming the problems of generation intermittency by providing the ability to shift demand to times when generation is available. However, exploiting the potential of this technology requires the design of an optimal charging and discharging schedule to allow its integration with the energy network that brings maximum advantage to both the system and the user. This paper introduces a mathematical model for generation and demand forecasting with energy storage scheduling that can be used for micro-grid and small power park applications. The proposed solution models the physical limitations associated with the energy storage technology used, which will constrain charge and discharge schedules beyond what can be forecast for them. A case study of a community feeder with large PV installations is presented to demonstrate the effectiveness of the model. Day-ahead charge and discharge schedules were produced that increased self-consumption within the system and reduced energy export to the grid. The main contribution of this work is the design of a generic parametrized forecasting and energy storage scheduling tool that will be a platform for further development to specialized storage technology and its potential scalability.