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

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.

Renewable_electricity_self-consumption_REF - details

Test System Model Details