ScienceDirect IFAC-PapersOnLine 48-30 (2015) 524–528 Available online at www.sciencedirect.com 2405-8963 © 2015, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved. Peer review under responsibility of International Federation of Automatic Control. 10.1016/j.ifacol.2015.12.433 © 2015, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved. Keywords: Energy storage, predictive control, power systems, renewable energy systems. 1. INTRODUCTION The constant increase in energy demand and the prevail- ing interest to reduce the global greenhouse gas emis- sions in order to avoid potentially dangerous climate changes, according to the latest climate models, suggest a new paradigm for the operation of electric power sys- tems, which assumed a large amount of renewable energy sources. The European Union initiatives such as the Eu- rope 2020 and the Swiss Energy Strategy 2050 put forward a series of long-term policy plans to assist EU and Switzer- land in becoming competitive low-carbon economies and in expanding the renewable energy sectors as described in Kirchner (2013). Parallel to the enforcement of these strategies, investments into the existing power grids along with their upgrades and improvements have had a direct impact on the price of the electricity, as explained in Yuan-Kang (2005). Future mechanisms to manage the pricing of electricity are re- quired. Present energy consumption habits are subject to concern and fixed electricity rates do not offer incentives for the energy consumers to change the current energy consumption patterns. Future changes in the consumption pattern, which that can be enforced by the power utility sectors, will use more flexible tariff schemes such as fixed rates and schemes with 2 or more tariffs as described in Ding et al. (2010). Self-consumption is defined as the possibility for a private electricity consumer to connect a photovoltaic (PV) sys- tem for his/her own use, while making it possible to receive an incentive for the non-consumed electricity, which can ⋆ The work reported in this paper was financed by the Swiss Competence Center for Energy Research, SCCER-FURIES. be either fed back to the utility grid, or charge an energy storage system or both. This mechanism is already prac- tised by some EU countries such as Germany, Switzerland, Italy, and Spain, as explained in Masson and Orland (July 2013). Some of the benefits of the self-consumption scheme are to encourage the installation of PV systems, which is a topic directly related with the Swiss Energy Strategy 2050 and at the same time produces savings in the electricity bills. In this work, a control approach to optimally manage the power flow in a micro-grid is investigated. The use of managed power flow allows placing emphasis on the self-consumption of a PV array in a building and thus indirectly minimizes the consumption of electricity from the utility grid. The approach is based on the utility of an advanced control scheme and includes a battery energy storage system (BESS) in the topology, which can participate in supplying energy to the load depending on the price of electricity in the grid. Two tariff schemes are considered on the grid to validate the approach using real measurements. Model-base Predictive Control (MPC) was selected as a control scheme for managing the power flow. MPC is a powerful approach that has been widely used to approach all kinds of problems in different engineering fields as described in Camacho and Alba (2013); Ferrari-Trecate et al. (2004); Zong et al. (2012). One of its advantages is the possibility to include different constraints in the problem formulation. The objective of this sophisticated control technique is to predict a future behavior of the variables under study over a time desired frame. The predictions are evaluated on a cost function that has to Abstract: In this work, a new framework for control of power flow of an energy storage is proposed. As part of the framework, an advanced controller for manipulating the power flow of an energy storage system, a photovoltaic (PV) source, and the utility grid is developed. The new controller relies on the Model-based Predictive Control (MPC) concept. The proposed controller realizes an optimal control scheme that maximizes the local self-consumption of renewable energy source. At the same time, the energy consumption supplied by the electric grid is minimized subject to its price posted in the grid. The presented approach is evaluated through computer-aided simulations using data available from a real installation in Switzerland. The data consists of photovoltaic panels, industrial building as a load as well as a battery energy storage system (BESS). Institute of Energy Systems and Fluid Engineering, Zurich University of Applied Sciences, Switzerland. F. R. Segundo Sevilla, V. Knazkins, C. Park and P. Korba Advanced Control of Energy Storage Systems for PV Installation Maximizing Self-Consumption ⋆