Renewable_electricity_self-consumption_REF
Renewable_electricity_self-consumption_REF - Title
Renewable_electricity_self-consumption_REF Test System Model
Renewable_electricity_self-consumption_REF - overview
Test System Model Overview
Author / organization: Frank Meinke-Hubeny, Pieter Valkering / VITO-EnergyVille
Component Models: -
Test Parameters: General input parameters are documented in: Meinke-Hubeny, F.; de Oliveira, L.; Duerinck, J. Energy transition in Belgium: Choices and costs; EnergyVille, 2017 The most significant test parameters are:
- Demand profile HEAT
- Demand profile COOKING
- Demand profile HOT WATER
- Demand profile LIGHTING & MULTI
- PV Generation
- Elc Storage costs
- Thermal Storage costs
Methods for data synthesis are described in D3.4.
Outputs/Measured Parameters:
- Electricity storage uptake (inflow and outflow)
- Thermal storage uptake (inflow and outflow)
- Self-consumption and impact of elc consumption from the low voltage grid (flow from ELCLOW to ELCRES)
Renewable_electricity_self-consumption_REF - input
Input
Related System Configuration
Belgium National Scale (VITO/EnergyVille)
Related Test Case
Renewable_electricity_self-consumption_REF
Related Use Case
Renewable_electricity_self-consumption_REF - description
Short Description
This test case is used to verify that self-consumption of renewable energy sources in a coupled heat and power network improved using distributed power-to-heat appliances compared to a base scenario without power-to-heat. This means that energy flows flowing out of the network are reduced. At the same time energy imports should not increase. Relevant effort variables of both networks, i.e., bus voltages, supply temperatures and differential pressures, must stay within the allowable range. Also, the loading of the transformer is not allowed to reach critical levels. Otherwise the test fails.
Electric boilers are used as power-to-heat appliances. They consist of an electric heater, for the conversation of power to heat, and a thermal energy storage, for the (short-term) storage of generated heat. To plan the operation of the storage unit and the electric heater, a model predictive controller is used. The aim of the controller is to minimize negative residual load of the electric network. To enable this planning, negative residual load in the electric as well as heat demand in the heat network need to be known/predicted. This test assumes perfect knowledge of these time-series data and, thus, does not focus on the quality of predictions.
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Renewable_electricity_self-consumption_REF - details
Test System Model Details
Title of Test | Renewable_electricity_self-consumption_REF | ||
Author / Organization | Frank Meinke-Hubeny, Pieter Valkering / VITO-EnergyVille | ||
Reference to Test Case | Modelling of renewable electricity self-consumption within the residential sector | ||
Test Rationale | We test the uptake of renewable electricity self-consumption under a reference scenario |
Specific Test System | The test specification pertains to the system configuration of the partial residential model as described in the TC. | ||||||||||||||||||||||||||
Test and Output Parameters | Test Parameters: General input parameters are documented in: Meinke-Hubeny, F.; de Oliveira, L.; Duerinck, J. Energy transition in Belgium: Choices and costs; EnergyVille, 2017. The most significant test parameters are:
Methods for data synthesis are described in D3.4. Outputs / Measured Parameters:
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Test Design | The test design follows the typical assumptions and guidelines for a TIMES simulation. The variation of test parameters is determined by the optimizer. |
Component Models | - | ||
Initial System State | The initial system state is documented in: Meinke-Hubeny, F.; de Oliveira, L.; Duerinck, J. Energy transition in Belgium: Choices and costs; EnergyVille, 2017. | ||
Temporal Resolution | 12 2-hourly consecutive time periods representing one day, with a total of 10 non-consecutive days representing a year, totalling 120 time slices. | ||
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 | Various uncertainties apply. These are treated by developing different scenarios as described in related test specifications. - | ||
Storage of Data | Model results are exported by the software interface (TIMES Veda) and stored in database format. This format can be viewed by the so-called Veda-Back End or by other data base software. |