**Day-Ahead Optimal Battery Operation in Islanded Hybrid Energy Systems and Its Impact on Greenhouse Gas Emissions**

### **Juan M. Lujano-Rojas, José M. Yusta, Jesús Sergio Artal-Sevil \* and José Antonio Domínguez-Navarro**

Department of Electrical Engineering, Universidad de Zaragoza, Calle María de Luna 3, 50018 Zaragoza, Spain; lujano.juan@gmail.com (J.M.L.-R.); jmyusta@unizar.es (J.M.Y.); jadona@unizar.es (J.A.D.-N.)

**\*** Correspondence: jsartal@unizar.es

Received: 24 October 2019; Accepted: 26 November 2019; Published: 30 November 2019

**Abstract:** This paper proposes a managemen<sup>t</sup> strategy for the daily operation of an isolated hybrid energy system (HES) using heuristic techniques. Incorporation of heuristic techniques to the optimal scheduling in day-head basis allows us to consider the complex characteristics of a specific battery energy storage system (BESS) and the associated electronic converter efficiency. The proposed approach can determine the discharging time to perform the load peak-shaving in an appropriate manner. A recently proposed version of binary particle swarm optimization (BPSO), which incorporates a time-varying mirrored S-shaped (TVMS) transfer function, is proposed for day-ahead scheduling determination. Day-ahead operation and greenhouse gas (GHG) emissions are studied through different operating conditions. The complexity of the optimization problem depends on the available wind resource and its relationship with load profile. In this regard, TVMS-BPSO has important capabilities for global exploration and local exploitation, which makes it a powerful technique able to provide a high-quality solution comparable to that obtained from a genetic algorithm.

**Keywords:** vanadium redox flow battery; genetic algorithm; binary particle swarm optimization; time-varying mirrored S-shaped transfer function; greenhouse gas emissions
