Many Demand Side Management (DSM) approaches use energy prices as steering signals. This paper shows that such steering signals may result in power quality problems and high losses. As an alternative, this paper proposes to use desired (e.g., flat) power profiles as steering signals and presents an efficient scheduling algorithm that can follow desired power profiles. This paper investigates the complexity of price and profile steering, and presents an algorithm for profile steering.The evaluation of this algorithm studies the results of a best possible uniform pricing and profile steering for a case of 121 houses, each with an electrical vehicle of which the power consumption can be controlled and shifted in time. In contrast to the other evaluated approaches, our profile steering algorithm results in a much flatter profile and keeps the voltage between 220 V and 235 V at each node. It reduces distribution losses by 57 % compared to no control, and by 48 % compared to uniform pricing.

CλaSH is a functional hardware description language that borrows both its syntax and semantics from the functional programming language Haskell. Polymorphism and higherorder functions provide a level of abstraction and generality that allow a circuit designer to describe circuits in a more natural way than possible with the language elements found in the traditional hardware description languages.Circuit descriptions can be translated to synthesizable VHDL using the prototype CλaSH compiler. As the circuit descriptions, simulation code, and test input are also valid Haskell, complete simulations can be done by a Haskell compiler or interpreter, allowing high-speed simulation and analysis.

Many multicore processors are capable of decreasing the voltage and clock frequency to save energy at the cost of an increased delay. While a large part of the theory oriented literature focuses on local dynamic voltage and frequency scaling (local DVFS), where every core's voltage and clock frequency can be set separately, this article presents an in-depth theoretical study of the more commonly available global DVFS that makes such changes for the entire chip. This article shows how to choose the optimal clock frequencies that minimize the energy for global DVFS, and it discusses the relationship between scheduling and optimal global DVFS. Formulas are given to find this optimum under time constraints, including proofs thereof. The problem of simultaneously choosing clock frequencies and a schedule that together minimize the energy consumption is discussed, and based on this a scheduling criterion is derived that implicitly assigns frequencies and minimizes energy consumption. Furthermore, this article studies the effectivity of a large class of scheduling algorithms with regard to the derived criterion, and a bound on the maximal relative deviation is given. Simulations show that with our techniques an energy reduction of 30% can be achieved with respect to state-of-the-art research. ! 0018-9340 (c)

Changes in our electricity supply chain are causing a paradigm shift from centralized control towards decentralized energy management. Within the framework of decentralized energy management, devices that offer flexibility in their load profile play an important role. These devices schedule their flexible load profile based on steering signals received from centralized controllers. The problem of finding optimal device schedules based on the received steering signals falls into the framework of resource allocation problems. We study an extension of the traditional problems studied within resource allocation and prove that a divide-and-conquer strategy gives an optimal solution for the considered extension. This leads to an efficient recursive algorithm, with quadratic complexity in the practically relevant case of quadratic objective functions. Furthermore, we study discrete variants of two problems common in decentralized energy management. We show that these problems are NP-hard and formulate natural relaxations of both considered discrete problems that we solve efficiently. Finally, we show that the solutions to the natural relaxations closely resemble solutions to the original, hard problems.This research is conducted within the EASI project (12700) supported by STW and Alliander and the EU FP7 project e-balance (609132).

Modern computers allow software to adjust power management settings like speed and sleep modes to decrease the power consumption, possibly at the price of a decreased performance. The impact of these techniques mainly depends on the schedule of the tasks. In this article, a survey on underlying theoretical results on power management, as well as offline scheduling algorithms that aim at minimizing the energy consumption under real-time constraints, is given.