Empowering Energy Communities through Geothermal Systems
Abstract
:1. Introduction
- The definition of a community based on thermal (cooling/heating and domestic hot water) and electric sharing composed of different user sectors;
- The use of economic analysis according to REDII and its Italian transposition for an electric and thermal REC;
- The modelling of existing buildings using real data from audit and simulations in order to characterise the energy loads of REC;
- The use of real data related to the geothermal wells;
- The energy index definition used to evaluate the benefits of a geothermal-based community.
2. Methods
2.1. Buildings’ Energy Model
- User 1: 2 working adults, 2 children of school age;
- User 2: 2 working adults, 1 child of school age, 1 elderly person;
- User 3: 2 retired elderly people;
- User 4: 2 working adults.
- The dynamic hourly demand of residential buildings has been evaluated with the EdilClima v.6 software that uses the dynamic approach of the standard UNI EN ISO 52016-1 [34]. It includes simplified hourly dynamic calculation methods for assessing energy needs for heating and cooling, internal temperatures, and other relevant thermal parameters. At the beginning of the simulation the initial indoor temperature is equal to 20 °C. Weather-related parameters are chosen from an archive of hourly climatic data, including the hourly values of outdoor temperature, direct and diffuse solar irradiance, outdoor relative humidity, vapour pressure, and average wind speed (“Typical years” provided by Italian Technical Committee). Internal Heat Gains, such as occupants, lighting, appliances, and equipment, are assumed considering the standard ISO18523-1 [35]. Thermal Properties of the Building are chosen according to the Italian Minister’s Decreed ‘Minimal Requirements’ for new buildings. The method requires that the element class and the total thermal capacity of the structure, expressed in kJ/m2K, are defined for each opaque building component. Each element of the building envelope (opaque or transparent component) is discretised in a number of parallel layers separated by internal, external, and internal nodes from the building element. This method is detailed in Equations (1)–(5).
- -
- To accurately assess the thermal loads of office buildings for both heating and cooling, a detailed simulation was conducted in the TRNBuild 18 environment through the multizone building model. This component model deals with the thermal balances of a building. The building model in Type 56 is a non-geometrical balance model with one air node per zone, representing the thermal capacity of the zone air volume and capacities that are closely connected, like furniture, with the air node. The existing transfer function method of the building model TYPE 56 for walls can be used for solving the one-dimensional heat conduction problem. The Transfer Function Method (TFM) in TRNSYS’s building model TYPE 56 is essential for simulating the thermal behaviour of buildings. TFM dynamically calculates heat transfer in buildings, modelling the response to indoor and outdoor temperature variations. It represents indoor temperature and heat flux as functions of past outdoor conditions and internal heat gains. TFM balances computational efficiency with accuracy by simplifying heat transfer into linear equations, making it suitable for detailed energy analysis. The boundary (like external weather, adjacent structures, ground conditions, and internal loads) and initial conditions (such as starting temperatures, HVAC system status, and moisture content) are defined by the user. The occupancy schedule of office rooms covers a range of 1–10 person from 7 a.m. to 8 p.m. In line with Italian regulations and the climatic region encompassing Naples, the heating period spans from 15 November to 31 March [36], while the cooling season is selected between 1 June and 30 September. The periods between these seasons (1 April–31 May and 1 October–14 November) do not demand space heating or cooling.
2.2. Environmental Analysis
2.3. Socio-Economic Plan Analysis for Electric Sharing
- -
- OCEl represents the operating cost associated with yearly electricity demand;
- -
- CO&M includes the maintenance and management costs of plants, including the software for REC management and two employed persons for technical staff. This parameter is null under TS conditions.
3. Case Study
3.1. Geothermal Area
3.2. Building and User Description
3.3. System Configuration and Components
4. Results
4.1. Energy Results
4.2. Environmental Results
4.3. Economic Results
- For the first case (C#1), and are fixed to 0.30 €/kWh by considering the electricity price from 2021, before the energetic conflict involving Ukraine and Russia, and 53.40 €/MWh, which corresponds to the minimum price at which the geothermal plant’s energy can be sold to the PG [47].
- For the second case (C#2), and are fixed to 0.39 €/kWh by considering an increment of 30% of unit electricity price after the energetic conflict and to 69.42 €/MWh, which corresponds to an increment of 30% with respect to the minimum price for geothermal energy to sell to the PG.
- For the third case (C#3), and are fixed to 0.48 €/kWh by considering an increment of 60% of unit electricity price after the energetic conflict and to 111.07 €/MWh, which corresponds to an increment of 60% with respect to the minimum price for geothermal energy sell to the PG.
Symbol | Description | Unit | Value (C#1/C#2/C#3) |
---|---|---|---|
Unit price for electricity taken from PG | €/kWh | 0.30/0.39/0.48 | |
Economic incentive for self-consumption REC | €/MWh | 118 | |
Unit price for electricity sell to PG | €/MWh | 53.4/69.4/111 | |
Economic cost for two workers on REC staff | k€/y | 64 | |
Economic cost of ORC maintenance calculated as 5% of investment cost | k€/y | 75 | |
Economic cost for management software for RECs | k€/y | 13 | |
Operating cost for electricity for residential user | €/y | 1424 * | |
Income for residential user | k€/y | 12 | |
ZORC | Investment cost for ORC | k€ | 1500 |
Zwells | Well investment cost | k€ | 130 |
Zpumps | Hydronic pump investment cost | € | 3031 |
ZGHEs | GHEs investment cost | k€ | 90.5 |
ZDHN | DHN investment cost | k€ | 2275 |
CM | Maintenance cost | k€/y | 199.7 |
4.4. Additional Considerations
5. Conclusions
- For electricity consumption, the geogrid system allows for a reduction of 82% of primary energy;
- The index of self-consumption and self-sufficiency are equal to 85% and 89%, respectively;
- The SPB changes from four to two as a function of the market conditions;
- The environmental impact caused by the geogrid system allows for a reduction of 81.2% of CO2 emissions with respect to the traditional configuration for electricity that uses the Italian electricity mix to supply electric energy consumption and 100% of thermal energy.
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
Abbreviations
ORC | Organic Rankine Cycle |
RES | Renewable Energy Source |
RED | Renewable Energy Directive |
IEMD | Internal Electricity Market Directive |
REC | Renewable Energy Community |
CEC | Citizen Energy Community |
DHC | District Heating and Cooling |
DHCN | District Heating and Cooling Network |
DHW | Domestic Hot Water |
EPI | Energy Poverty Index |
HHD | Heating Degree Days |
PG | Power Grid |
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Zone | Geothermal Source Temperature | |
---|---|---|
Greece (Aristino—Alexandroupolis area) | 99 °C | [27] |
Thailand | About 100 °C | [28] |
Mexico | About 100 °C | |
Island | >110 | |
Bulgaria | 100 °C | |
Hungary | 108 °C | |
Romania | About 90 °C | |
Germany (north east) | 120 °C | [29] |
Turkey | 240 °C | [30] |
Italy (Ferrara) | About 100 °C | [31] |
Italy (Phlegrean Fields) | Up to 240 °C |
Building Element | Transmittance [W/m2K] | Thickness [m] | g-Value [−] | Longwave Emission Coefficient [−] | Solar Absorptance [−] |
---|---|---|---|---|---|
External Walls, First floor | 0.740 | 0.34 | - | 0.9 | 0.6 |
External Wall | 0.843 | 0.34 | - | 0.9 | 0.6 |
Inner Wall | 0.293 | 0.12 | - | - | - |
Ground Floor | 1.78 | 0.46 | - | - | - |
Ceiling | 1.30 | 0.24 | - | - | - |
Roof | 1.69 | 0.20 | - | 0.9 | 0.6 |
Window | 1.40 | - | 0.76 | - | - |
Parameter | Description |
---|---|
[J/K] | Zone internal thermal capacity |
[m2] | Area of the building element “eli” |
[m2] | Sum of areas of all construction elements “elk = 1…eln” |
[W/m2K] | Convective coefficient for the inner surface |
[W/m2K] | Radiative coefficient for the inner surface |
[W/m2K] | Conductance between the “pli” node and the “pli-1” node |
[°C] | Internal surface temperature of the building element “eli” |
[°C] | Temperature at the “pli” node |
[°C] | Supply air temperature of the ventilation flow “vei” |
[W/K] | Convective fraction of the internal inputs |
[W/K] | Convective fraction of solar inputs |
[W/K] | Convective fraction of heating and cooling inputs |
[W/K] | Global heat transfer coefficient for ventilation, for ventilation flow “vei” |
[W/K] | Global heat transfer coefficient through thermal bridges |
[W] | Global contribution of internal heating |
[W] | Contribution of directly transmitted solar heating to the zone |
[W] | Heating or cooling load |
[J/m2K] | Thermal capacity |
Sola absorption coefficient | |
[W/m2] | Solar irradiance (hourly, diffuse) |
[W/m2] | Solar irradiance (hourly, direct) |
[W/m2] | Thermal radiation to the sky |
Water Temperature at the Wellhead | 145 °C |
Average Flow Rate | 59 kg/s |
Specific Heat of the Geothermal Fluid | 4.19 kJ/kgK |
Density | 1.08 kg/L |
Building | Heating Demand [kW] | Cooling Demand [kW] |
---|---|---|
Office-F | 383 | 707 |
Office-I | 270 | 498 |
Office-G | 306 | 565 |
Residential-1 | 333 | 545 |
Residential-2 | 158 | 285 |
Residential-3 | 142 | 243 |
Residential-4 | 142 | 243 |
Residential-5 | 142 | 243 |
Building | Electricity Demand [MWh/y] |
---|---|
Office-F | 1367 |
Office-I | 911 |
Office-G | 1215 |
Residential-1 | 76.0 |
Residential-2 | 42.6 |
Residential-3 | 42.6 |
Residential-4 | 42.6 |
Residential-5 | 42.6 |
C#1 | C#2 | C#3 | |
---|---|---|---|
REC | |||
[€/y] | 360,774 | 360,774 | 360,774 |
[€/y] | 23,771 | 30,902 | 49,443 |
[€/y] | 133,543 | 173,607 | 213,670 |
[€/y] | 251,001 | 218,069 | 196,547 |
[€/y] | 25,757 | 58,689 | 80,211 |
TS | |||
or [€/y] | 1,121,812 | 1,458,355 | 1,794,899 |
REC vs. TS | |||
SPB [y] | 4 | 3 | 2 |
[€/y] | 1,096,054 | 1,399,666 | 1,714,688 |
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Battaglia, V.; Ceglia, F.; Laudiero, D.M.; Maione, A.; Marrasso, E.; Vanoli, L. Empowering Energy Communities through Geothermal Systems. Energies 2024, 17, 1248. https://doi.org/10.3390/en17051248
Battaglia V, Ceglia F, Laudiero DM, Maione A, Marrasso E, Vanoli L. Empowering Energy Communities through Geothermal Systems. Energies. 2024; 17(5):1248. https://doi.org/10.3390/en17051248
Chicago/Turabian StyleBattaglia, Vittoria, Francesca Ceglia, Davide Maria Laudiero, Alessandro Maione, Elisa Marrasso, and Laura Vanoli. 2024. "Empowering Energy Communities through Geothermal Systems" Energies 17, no. 5: 1248. https://doi.org/10.3390/en17051248