Abstract
The increasing resort to renewable energy distributed generation, which is needed to mitigate anthropogenic CO2 emissions, leads to challenges concerning the proper operation of electric distribution systems. As a result of the intrinsic nature of Renewable Energy Sources (RESs), this generation shows a high volatility and a low predictability that make the balancing of energy production and consumption difficult. At the same time, the electrification of new energy-intensive sectors (such as heating) is expected. This complex scenario paves the way for new sources of flexibility that will have more and more relevance in the coming years. This paper analyses how the electrification of the heating system, combined with an electric flexibility utilisation module, can be used to mitigate the problems related to the fluctuating production of RES. By using Power-to-Heat (P2H) technologies, buildings are able to store the overproduction of RES in the form of thermal energy for end-use according to the principle of the so-called Virtual Energy Storage (VES). A context-aware demand flexibility extraction based on the VES model and the flexibility upscale and utilisation on district-level through grid simulation and energy flow optimisation is presented in the paper. The involved modules have been developed within the PLANET (PLAnning and operational tools for optimising energy flows and synergies between energy NETworks) H2020 European project and interact under a unified co-simulation framework with the PLANET Decision Support System (DSS) for the analysis of multi-energy scenarios. DSS has been used to simulate a realistic future energy scenario, according to which the imbalance problems triggered by RES overproduction are mitigated with the optimal exploitation of the demand flexibility enabled by VES.
Funder
Horizon 2020 research and innovation program
Subject
Energy (miscellaneous),Energy Engineering and Power Technology,Renewable Energy, Sustainability and the Environment,Electrical and Electronic Engineering,Control and Optimization,Engineering (miscellaneous)
Cited by
14 articles.
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