Abstract

The exploitation of fossil fuels is undoubtedly responsible of environmental problems such as global warming and sea level rise. Unlike energy plants based on fossil fuels, energy plants based on renewable energy sources may be sustainable and reduce greenhouse gas emissions. However, they are unpredictable because of the intermittent nature of environmental conditions. For this reason, energy storage technologies are needed to meet peak energy demands thanks to the stored energy. Moreover, the renewable energy systems composing the plant must be optimally designed and operated. Therefore, this paper investigates the challenge of the optimal design and energy management of a grid connected renewable energy plant composed of a solar thermal collector, photovoltaic system, ground source heat pump, battery, one short-term thermal energy storage and one seasonal thermal energy storage. To this aim, this paper develops a methodology based on a genetic algorithm that optimally designs a 100% renewable energy plant with the aim of minimizing the electrical energy taken from the grid. The load profiles of thermal, cooling and electrical energy during a whole year are taken into account for the case study of the Campus of the University of Parma (Italy).

Highlights

  • In recent years, several attempts have been made to reduce greenhouse gas emissions by means of the integration of Renewable Energy Sources (RESs) within energy plants

  • The current paper aims at investigating the optimal design and energy management of a grid connected Renewable Energy Plant (REP) considering the thermal, cooling and electrical energy demands of the Campus of University of Parma (Italy)

  • The Photovoltaic system (PV) and Solar Thermal Collector (STC) areas are normalized with respect to the available area in Scenario B, the Ground Source Heat Pump (GSHP) size is normalized with respect to the cooling peak power of the campus, while the capacities of the Thermal Energy Storages (TESs)/Seasonal TESs (STESs) and Battery Energy Storage (BES) are expressed in hours by dividing their capacities by the thermal and electrical peak power, respectively

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Summary

Introduction

Several attempts have been made to reduce greenhouse gas emissions by means of the integration of Renewable Energy Sources (RESs) within energy plants. To this aim, the European Commission has planned, for the power sector, an increase of the RES share to more than 80 % by 2050 [1]. In Europe, most of heating and cooling energy demand is still covered by means of fossil fuel, so that several studies (e.g., [4]) recommended the combined production of heating and power. It is worth noting that energy storage technologies promote RES integration, since the exceeding energy can be stored and subsequently exploited based on user energy demand. Energy storage increases the flexibility of the energy plant, while energy losses during start-up and shut-down manoeuvres can be reduced [5]

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