An Online Algorithm Optimally Self-tuning to Congestion for Power Management Problems
نویسندگان
چکیده
We consider the classical power management problem: There is a device which has two states ON and OFF and one has to develop a control algorithm for changing between these states as to minimize (energy) cost when given a sequence of service requests. Although an optimal 2-competitive algorithm exists, that algorithm does not have good performance in many practical situations, especially in case the device is not used frequently. To take the frequency of device usage into account, we construct an algorithm based on the concept of “slackness degree.” Then by relaxing the worst case competitive ratio of our online algorithm to 2 + ε, where ε is an arbitrary small constant, we make the algorithm flexible to slackness. The algorithm thus automatically tunes itself to slackness degree and gives better performance than the optimal 2-competitive algorithm for real world inputs. In addition to worst case competitive ratio analysis, a queueing model analysis is given and computer simulations are reported, confirming that the performance of the algorithm is high.
منابع مشابه
An Improvement over Random Early Detection Algorithm: A Self-Tuning Approach
Random Early Detection (RED) is one of the most commonly used Active Queue Management (AQM) algorithms that is recommended by IETF for deployment in the network. Although RED provides low average queuing delay and high throughput at the same time, but effectiveness of RED is highly sensitive to the RED parameters setting. As network condition varies largely, setting RED's parameters with fixed ...
متن کاملCongestion Management through Optimal Allocation of FACTS Devices Using DigSILENT-Based DPSO Algorithm- A Real Case Study
Flexible AC Transmission Systems (FACTS) devices have shown satisfactory performance in alleviating the problems of electrical transmission systems. Optimal FACTS allocation problem, which includes finding optimal type and location of these devices, have been widely studied by researchers for improving variety of power system technical parameters. In this paper, a DIgSILENT-based Discrete Parti...
متن کاملCongestion Management in Power Systems Via Intelligent Method
In the deregulated power systems, transmission congestion is one of the significant and main problems of the electrical networks which can cause incremental cost in the energy. This problem has resulted to new challenging issues in different parts of power systems which there was not in the traditional systems or at least had very little importance. Transmission congestion happens when the maxi...
متن کاملLocating of Series FACTS Devices for Multi-Objective Congestion Management Using Components of Nodal Prices
Congestion and overloading for lines are the main problems in the exploitation of power grids. The consequences of these problems in deregulated systems can be mentioned as sudden jumps in prices in some parts of the power system, lead to an increase in market power and reduction of competition in it. FACTS devices are efficient, powerful and economical tools in controlling power flows through ...
متن کاملDesign of A Self-Tuning Adaptive Power System Stabilizer
Power system stabilizers (PSSs) must be capable of providing appropriate stabilization signals over abroad range of operating conditions and disturbances. The main idea of this paper is changing aclassic PSS (CPSS) to an adaptive PSS using genetic algorithm. This new genetic algorithm based onadaptive PSS (GAPSS) improves power system damping, considerably. The controller design issue isformula...
متن کامل