Loesch, M.; Hufnagel, D. ; Steuer, S. ; Fabnacht, T. ; Schmeck, H.

A major component of the future Smart Grid is an adaptive demand side that allows to handle the fluctuating power supply based on renewable energies. In this paper, we present an evolutionary algorithm that allows for shifting electrical loads generated by heat pumps. Our approach is based on overheating the hot water storage in order to get a higher degree of freedom for scheduling. In our scenario, we assume time-variable price and load limitation signals as well as a prediction for local power generation from photovoltaic panels to incentivize the load shifting. Using these signals, we consider the future thermal demand to schedule the heat pump such that electricity costs are decreased. Our simulations show that heat pumps and hot water storages bear potential to shift loads over a time span of up to multiple hours, thus providing economical storage capacity. In doing so and based on electricity prices from the stock exchange, we were able to significantly decrease electricity costs for operating the heat pump.

Published in: Intelligent Energy and Power Systems (IEPS), 2014 IEEE International Conference on

Elsevier introduces IPP, SNIP & SJR: A new perspective in journal metrics for researchers and publishers

Cecati, C. ; Citro, C. ; Siano, P.

The integration of renewable energy systems (RESs) in smart grids (SGs) is a challenging task, mainly due to the intermittent and unpredictable nature of the sources, typically wind or sun. Another issue concerns the way to support the consumers' participation in the electricity market aiming at minimizing the costs of the global energy consumption. This paper proposes an energy management system (EMS) aiming at optimizing the SG's operation. The EMS behaves as a sort of aggregator of distributed energy resources allowing the SG to participate in the open market. By integrating demand side management (DSM) and active management schemes (AMS), it allows a better exploitation of renewable energy sources and a reduction of the customers' energy consumption costs with both economic and environmental benefits. It can also improve the grid resilience and flexibility through the active participation of distribution system operators (DSOs) and electricity supply/demand that, according to their preferences and costs, respond to real-time price signals using market processes. The efficiency of the proposed EMS is verified on a 23-bus 11-kV distribution network.

Sustainable Energy, IEEE Transactions on (Volume:2 , Issue: 4 ) - 2001

18/April/2007

In this report we discuss our implementation of a local path planning algorithm based on virtual potential field described in [1]. The algorithm uses virtual forces to avoid being trapped in a local minimum. Simulation and experiments are performed, and compared to the results presented in the paper. They show good performance and ability to avoid the local minimum problem in most of the cases.

Albert Y. Zomaya and Young Choon Lee, Chen Wang and Martin De Groot

A probabilistic algorithm is exhibited that calculates the gcd of many integers using gcds of pairs of integers; the expected number of pairwise gcds required is less than two.

We study the problem of scheduling repetitive real-time tasks with the Earliest Deadline First (EDF) policy that can guarantee the given maximal temperature constraint. We show that the traditional scheduling approach, i.e., to repeat the schedule that is feasible through the range of one hyper-period, does not apply any more. Then, we present necessary and sufficient conditions for real-time schedules to guarantee the maximal temperature constraint. Based on these conditions, a novel scheduling algorithm is proposed for developing the appropriate schedule that can ensure the maximal temperature guarantee. Finally, we use experiments to evaluate the performance of our approach.

A single Complementary Metal Oxide Semiconductor (CMOS) image sensor based on 0.35μm process along with its design and implementation is introduced in this paper. The pixel architecture of Active Pixel Sensor (APS) is used in the chip, which comprises a 256×256 pixel array together with column amplifiers, scan array circuits, series interface, control logic and Analog-Digital Converter (ADC). With the use of smart layout design, fill factor of pixel cell is 43%. Moreover, a new method of Dynamic Digital Double Sample (DDDS) which removes Fixed Pattern Noise (FPN) is used. The CMOS image sensor chip is implemented based on the 0.35μm process of chartered by Multi-Project Wafer (MPW). This chip performs well as expected.