Publikationen

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.

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.

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.

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.

Abstract: The Deterministic and Synchronous Multi-Channel Extension (DSME) of the IEEE 802.15.4 standard provides a data link layer for time division multiple access in wireless mesh networks. The authors present openDSME, a portable implementation for hardware and simulators which promises reliable message transfer suitable for applications in demanding industrial environments. A demonstration has been developed to illustrate the performance of openDSME in a simulated network and to show its benefits over CSMA/CA.

Abstract: Providing dependability is still a major issue for wireless mesh networks, which restrains their application in industrial contexts. The widespread CSMA/CA medium access can provide high throughput and low latency, but can not prevent packet loss due to collisions, especially in very large and dense networks. Time slotted medium access techniques together with a distributed slot management, as proposed by the Distributed Synchronous Multi-channel Extension (DSME) of the IEEE 802.15.4 standard, are promising to provide low packet loss, high scalability and bounded end-to-end delays. However, our implementation, openDSME, exposed some weaknesses. While the allocated slots allow for reliable data transmission, the slot management itself is conducted via CSMA/CA and is thus vulnerable to packet loss, eventually leading to an inconsistent slot allocation. This paper uses the UPPAAL framework for formal analysis and verification of the slot management process. The analysis identifies weaknesses of the slot allocation process under communication and node failures. However, it is shown that inconsistencies are eventually resolved and improvements to the procedure are proposed that reduce the negative impact of failed slot allocation procedures significantly.

Abstract: Reliable wireless solutions for large-scale automation are a major challenge today. The IEEE 802.15.4 standard forms the basis for many open and proprietary implementations. To reflect current state-of-the-art techniques, the IEEE has amended standard 802.15.4 with new MAC-layers such as TSCH, which resembles WirelessHART, and the Deterministic and Synchronous Multi-Channel Extension (DSME). This paper introduces openDSME, our implementation of IEEE 802.15.4 DSME. DSME aims at preventing packet collisions through slot reservation in networks where conventional CSMA/CA is not reliable enough. In this document, we will outline core features of DSME and openDSME, and present details of our implementation. Additionally, current research efforts on connected topics will be highlighted.

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.