Abstract
Distributed power supply with the use of renewable energy sources and intelligent energy flow management has undoubtedly become one of the pressing trends in modern power engineering, which also inspired researchers from other fields to contribute to the topic. There are several kinds of micro grid platforms, each facing its own challenges and thus making the problem purely multi objective. In this paper, an evolutionary driven algorithm is applied and evaluated on a real platform represented by a private multistory carpark equipped with photovoltaic solar panels and several battery packs. The algorithm works as a core of an adaptive charge management system based on predicted conditions represented by estimated electric load and production in the future hours. The outcome of the paper is a comparison of the optimized and unoptimized charge management on three different battery setups proving that optimization may often outperform a battery setup with larger capacity in several criteria.
Highlights
The 20/20/20 targets defined as ’European climate and energy goals’ mean a 20% increase in the use of renewable energy sources (RES) combined with a 20% energy efficiency improvement by2020
This paper describes an experiment in a multistory carpark working as an Off-Grid platform able to store and charge electric vehicles [26]
While the A parameters were directly applied in the model, B values were multiplied by T and floored to correctly represent the time periods
Summary
The 20/20/20 targets defined as ’European climate and energy goals’ mean a 20% increase in the use of renewable energy sources (RES) combined with a 20% energy efficiency improvement by. The term Smart-Grid has been frequently used in the current decade due to a high number of proposals and applications extending the current concepts of centralized (On-Grid) and decentralized (Off-Grid) energy supplies These are the two main scenarios making use of the new sophisticated solutions based on data science, predictive analysis, unconventional modeling and mathematical optimization. This paper describes an experiment in a multistory carpark working as an Off-Grid platform able to store and charge electric vehicles [26]. This platform, having 36 EV chargers, two photovoltaic power plants, an energy storage system, a self-driven parking system and multiple controlling mechanisms, represents the most modern working application in this area, called Automated Parking System (APS). Our real physical deployment as well as real weather conditions, tree designed objective functions, the simulation during a year period and MOO with decomposition making use of differential evolution with a very high computational performance makes this proposal very unique
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