"INVESTIGATION ON THE OPTIMAL TECHNO-ECONOMIC SOLUTION FOR THE STORAGE OF ELECTRICAL ENERGY CURTAILMENTS OF RES PROJECTS IN GREEK NON-INTERCONNECTED ISLANDS"

In 21^st century major energy policy changes declare the explicit direction of societies towards the low carbon era. Particular emphasis is given in electrical energy production using renewable energy sources.  In this direction, inter alia, huge electricity quantities produced by traditional and polluting production units must be replaced by the green energy of Wind Generators, Photovoltaic Plants and other RES Units. 

However, embodiment of big quantities of intermittent energy in Energy Systems brings about remarkable problems in its absorption due to technical limitations of Transmission and Distribution networks especially in isolated Energy Systems such that of the Greek Islands. A characteristic case is that of Lesvos Island where 5GWh of electrical energy was not absorbed by the network from two wind farms of 9MW installed capacity in 2015. A method that could contribute to face with the problem of power rejections is, as it is universally acknowledged, the integration of Energy Storage Systems in networks.

In the context of the proposed research the possibility of Storage, especially in the electrochemical form, to contribute to the Renewable Energy increase in Greek isolated Islands will be investigated. Lesvos Island will be used as the model of the research.

The research will consist of two parts:

1. i) Modelling the operation of existing energy system of the Island the possibility of minimization of renewable energy rejections will be investigated through the integration of Battery Storage System

ii) In a second level the optimized mix of Renewables in combination with the most suitable type or types of Battery Storage Technology and traditional generators, as well as, the sensitivity of this mix to future Demand differentiations will be investigated focusing on the maximization of Renewable Energy’s contribution in Demand together with the minimization of operational System cost.