Application of artificial immune system to domestic energy management problem

[EN] The connection of devices in a smart home should be done optimally, this helps save energy and money. Numerous optimization models have been applied, they are based on fuzzy logic, linear programming or bio-inspired algorithms. The aim of this work is to solve an energy management problem in a domestic environment by applying an artificial immune system. We carried out a thorough analysis of the different strategies that optimize a domestic environment system, in order to demonstrate the ability of an artificial immune system to find a successful optima that satisfies the problem constraints

Real-Time Implementation of a STATCOM on a Wind Farm Equipped With Doubly Fed Induction Generators

Voltage stability is a key issue to achieve the uninterrupted operation of wind farms equipped with doubly fed induction generators (DFIGs) during grid faults. This paper investigates the application of a static synchronous compensator (STATCOM) to assist with the uninterrupted operation of a wind turbine driving a DFIG, which is connected to a power network, during grid faults. The control schemes of the DFIG rotor- and grid-side converters and the STATCOM are suitably designed and coordinated. The system is implemented in real-time on a Real Time Digital Simulator. Results show that the STATCOM improves the transient voltage stability and therefore helps the wind turbine generator system to remain in service during grid faults

NSC54316

Control of power systems relies on the availability and quality of sensor measurements. However, measurements are inevitably subjected to faults caused by sensor failure, broken or bad connections, bad communication, or malfunction of some hardware or software. These faults, in turn, may cause the failure of power system controllers and consequently, severe contingencies in the power system. To avoid such contingencies, this paper presents a sensor evaluation and (missing sensor) restoration scheme (SERS) by using auto-associative neural networks (auto encoders) and particle swarm optimization. Based on the SERS, a missing-sensor-fault-tolerant control is developed for controlling a static synchronous series compensator (SSSC) connected to a power network. This missing-sensor fault-tolerant control (MSFTC) improves the reliability, maintainability, and survivability of the SSSC and the power network. The effectiveness of the MSFTC is demonstrated by a real-time implementation of an SSSC connected to the IEEE 10-machine 39-bus system on a Real Time Digital Simulator and TMS320C6701 digital signal processor platform. The proposed fault-tolerant control can be readily applied to many existing controllers in power systems