DRDEWH
Demand Response using Domestic Electric Water Heaters
| Staff | Dr. Marcus Venzke |
| Start | 1. November 2015 |
| End | 30. June 2019 |
| Financing | TUHH |
Project Description
In electricity networks, produced and consumed power is the same at every point in time. Traditionally power plants are regulated to exactly produce the power needed by the consumers. However, more and more electricity is produced from wind and solar farms depending on weather conditions, not according to the consumer’s needs. This raises the question, how production and consumption can be balanced in the future. Demand response (DR) is an approach contributing to solve the issue by adapting the power consumption according to power availability. A known option is that suppliers fix and announce varying prices for different times of the next day (day ahead real time prices, DA-RTP) to make customers shift their consumption to save money.
The project investigates how domestic electric water heaters (DEWHs) can be used for demand response. It assumes that DEWHs are controlled locally based on dynamic prices following the DA-RTP paradigm to protect the residents’ privacy. Models are developed to describe DEWHs and its usage. These are used for optimization and heuristics to calculate retail prices. The resulting load profile of many DEWHs is analyzed for predictability and accuracy in relation to target schedules.
Downloads
Tobias Lübkert, Marcus Venzke and Volker Turau.
Raw data belonging to paper
"Calculating Retail Prices from Demand Response Target Schedules to Operate Domestic Electric Water Heaters".
Telematics, Hamburg University of Technology, August 2018.
Publications
Tobias Lübkert. Load Shaping of Thermostatically Controllable Devices by Constructing Retail Prices. PhD Thesis, Hamburg University of Technology, Hamburg, Germany, 2020.
@PhdThesis{Telematik_Luebkert_2020_Diss,
author = {Tobias L{\"u}bkert},
title = {Load Shaping of Thermostatically Controllable Devices by Constructing Retail Prices},
school = {Hamburg University of Technology},
address = {Hamburg, Germany},
year = 2020,
}
Abstract:
In the course of the energy transition the process of balancing power supply and demand becomes more challenging due to the uncertainty of renewable energy sources. Demand Response (DR) mechanisms encourage consumers to change their energy consumption, e.g. through time-varying electricity prices. This dissertation develops a price-based DR mechanism for cost-optimizing thermostatically controlled loads, which induces an aggregated load profile approximating a target schedule. A heuristic algorithm is developed to calculate suitable price signals. Simulations of realistic scenarios are analyzed to validate the functionality.
Tobias Lübkert, Marcus Venzke and Volker Turau. Calculating retail prices from demand response target schedules to operate domestic electric water heaters. Energy Informatics, 1(1):31, October 2018.
@Article{Telematik_EI_2018,
author = {Tobias L{\"u}bkert and Marcus Venzke and Volker Turau},
title = {Calculating retail prices from demand response target schedules to operate domestic electric water heaters},
pages = 31,
journal = {Energy Informatics},
volume = {1},
number = {1},
day = {10},
month = oct,
year = 2018,
}
Abstract:
The paper proposes a demand response scheme controlling many domestic electric water heaters (DEWHs) with a price function to consume electric power according to a target schedule. It discusses at length the design of an algorithm to calculate the price function from a target schedule. The price function is used by the control of each DEWH to automatically and optimally minimize its local heating costs. It is demonstrated that the resulting total power consumption approximates the target schedule. The algorithm was successfully validated by simulation with a realistic set of 50 DEWHs assuming perfect knowledge of parameters and water consumption. It is shown that the algorithm is also applicable to clusters of large numbers of DEWHs with statistical knowledge only. However, this leads to a slightly higher deviation from the target schedule.
Tobias Lübkert, Marcus Venzke, Nhat-Vinh Vo and Volker Turau. Understanding Price Functions to Control Domestic Electric Water Heaters for Demand Response. Computer Science - Research and Development, 81–92, February 2018.
@Article{Telematik_Demand_Response_DEWH_2017,
author = {Tobias L{\"u}bkert and Marcus Venzke and Nhat-Vinh Vo and Volker Turau},
title = {Understanding Price Functions to Control Domestic Electric Water Heaters for Demand Response},
pages = {81-92},
journal = {Computer Science - Research and Development},
volume = {},
month = feb,
year = 2018,
}
Abstract:
A well-known mechanism for demand response is sending price signals to customers a day ahead. Customers then postpone or advance their usage of electricity to minimize cost. Setting up price functions that adapt the customers' load to availability is a big challenge. This paper investigates the feasibility of finding day-ahead price functions to induce a desired load profile of Domestic Electric Water Heaters (DEWHs) minimizing their electricity cost for demand response. Bilevel optimization is applied for a single DEWH using a simplified linear model and full knowledge. This leads to a solvable bilevel problem and allows understanding optimality of price functions and resulting heating profiles. It is shown that with the resulting price functions the DEWH may select many significantly different heating profiles leading to the same cost. Thus the price does not uniquely induce the desired heating profile. The acquired knowledge forms the basis for a procedure to create price functions for controlling the load profile of many DEWHs.
Tobias Lübkert, Marcus Venzke and Volker Turau. Appliance Commitment for Household Load Scheduling Algorithm: A Critical Review. In 2017 IEEE International Conference on Smart Grid Communications (SmartGridComm), October 2017, pp. 527–532. Dresden, Germany.
@InProceedings{Telematik_SGC_2017,
author = {Tobias L{\"u}bkert and Marcus Venzke and Volker Turau},
title = {Appliance Commitment for Household Load Scheduling Algorithm: A Critical Review},
booktitle = {2017 IEEE International Conference on Smart Grid Communications (SmartGridComm)},
pages = {527-532},
day = {23-26},
month = oct,
year = 2017,
location = {Dresden, Germany},
}
Abstract:
The paper analyzes the behavior of two demand response algorithms, both claiming to minimize the energy cost regarding time-varying prices in an optimal way by iteratively scheduling heating phases of water heaters considering hot water consumption. Four issues of the well known algorithm by Du and Lu are identified, which lead to suboptimal behavior. Proposed enhancements lead to an algorithm similar to the second, recently published, method of Shah et al. The effect of each enhancement and its combinations are analysed simulatively reducing the costs.
Tobias Lübkert, Marcus Venzke and Volker Turau. Impacts of Domestic Electric Water Heater Parameters on Demand Response. Computer Science - Research and Development, 32:49–64, 2017.
@Article{Telematik_Demand_Response_DEWH_2016,
author = {Tobias L{\"u}bkert and Marcus Venzke and Volker Turau},
title = {Impacts of Domestic Electric Water Heater Parameters on Demand Response},
pages = {49-64},
journal = {Computer Science - Research and Development},
volume = {32},
year = 2017,
}
Abstract:
This paper analyzes the impact of the high dimen- sional parameter space of domestic electric water heaters (DEWH) for demand response (DR). To quantify the con- sumer comfort a novel metric is introduced considering a stochastic distribution of different water draw events. Incor- porating three control algorithms from literature, it is shown that all considered parameters of a DEWH except the heat conductivity have a significant impact on consumer satisfac- tion. The effect on DR is mainly influenced by the temper- ature range and the planning horizon, but also by the heat conductivity and the volume. In contrast, the rated power of the heating element and the nominal temperature have no significant impact on the effect on DR. The impacts are an- alyzed by varying these parameters in a simulation of 1000 DEWHs considering three different controllers: a common thermostat, an exchange price dependent nominal temper- ature changing mechanism and an energy scheduling algo- rithm proposed by Du and Lu.