LMES_COLLECTOPIA_seasonal storage
LMES_COLLECTOPIA_seasonalstorage - title
LMES_COLLECTOPIA_seasonal storage Test System Model
LMES_COLLECTOPIA_seasonalstorage - overview
Test System Model Overview
Author / organization: Stephan Seidelt, Daniel Fehrenbach / EIFER
Component Models:
Test Parameters: Cost parameters, heat and electricity demands as well as CO2 grid factor from France are used
Outputs/Measured Parameters:
- overall system costs
- capacities of the technologies
LMES_COLLECTOPIA_seasonalstorage - input
Input
Related System Configuration
Collectopia (EDF) System Configuration
Related Test Case
Related Use Case
LMES_COLLECTOPIA_seasonalstorage - description
Short Description
A Local multi energy system (LMES) can consist of many different energy production technologies, such as gas-driven boilers and CHPs, HPs, PV panels, DHN, electricity and heat storage facilities as well as imports and exports of electricity from the grid. The electricity and heat demands of the buildings located in a LMES have to be met at all times, either by self-production or by imports from the external grid. The overall costs of the LMES are the discounted net total of all CAPEX, OPEX, fuel costs, electricity imports as well as revenues from exports. In addition, CO2 emissions can be considered with the help of a CO2 price. A least-cost planning approach determines the configuration of the LMES with the lowest overall costs.
The test case is used to calculate the system costs of the Collectopia Reference Energy Systems (RES) to find out if seasonal storage is economically feasible considering CO2 savings.
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LMES_COLLECTOPIA_seasonalstorage - details
Test System Model Details
| Title of Test | LMES_COLLECTOPIA_seasonalstorage | ||
| Author / Organization | Stephan Seidelt, Daniel Fehrenbach / EIFER | ||
| Reference to Test Case | Sesaonalstorage | ||
| Test Rationale | A Local multi energy system (LMES) can consist of many different energy production technologies, such as gas-driven boilers and CHPs, HPs, PV panels, DHN, electricity and heat storage facilities as well as imports and exports of electricity from the grid. The electricity and heat demands of the buildings located in a LMES have to be met at all times, either by self-production or by imports from the external grid. The overall costs of the LMES are the discounted net total of all CAPEX, OPEX, fuel costs, electricity imports as well as revenues from exports. In addition, CO2 emissions can be considered with the help of a CO2 price. A least-cost planning approach determines the configuration of the LMES with the lowest overall costs. |
| Specific Test System |
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| Test and Output Parameters | Test parameters: Cost parameters, heat and electricity demands as well as CO2 grid factor from France are used. Output parameters:
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| Test Design | The test design follows the typical assumptions and guidelines for an ETEM simulation. The variation of test parameters is determined by the optimizer. |
| Component Models | Conversion/storage process (see deliverable D4.1, Appendix C.3, page 73) | ||
| Initial System State | -- | ||
| Temporal Resolution | hourly | ||
| Evolution of System State and Test Signals | The evolution of the system state is determined by the simulation (i.e., system optimization over the full time range). | ||
| Source of Uncertainty Stopping Criteria | The test considers a timeline of 40 years, so uncertainty is implicit. Uncertainties notably include the evolution of techno-economic, demand and energy price parameters. These uncertainties are considered through scenario analysis. | ||
| Storage of Data | SmILES data format |