Zhao Yang Dong

TL;DR: To reduce training time in multi-layer perceptron-based short-term load forecasting, a graphics processing unit (GPU)-based computing method is introduced and results show that GPU-based computing greatly reduces computational costs.

TL;DR: A real-time monitoring system applied in transmission lines based on ZigBee technology and mesh topology architectures that takes advantage of low power consumption, self-organization and self-healing of mesh network, and uses the F-AODVjr(F-Ad hoc On-Demand Distance Vector Routing) to establish a ZigBee wireless communication mesh network.

TL;DR: In this paper, an adaptive neuro-wavelet model for short-term electricity load forecast is proposed, which uses both historical load and temperature data, which have important impacts on load level, are used in forecasting.

TL;DR: In this article, the authors proposed a systematic modeling framework and constructs simulation platforms for coupled gas and power systems in an energy market environment, by applying the proposed approach to the Australian national electricity market (NEM) and gas market, the impacts of six types of market and system factors are quantitatively analyzed, including power transmission limits, gas pipeline contingencies, gas pipelines flow constraints, carbon emission constraints, power load variations, and non-electric gas load variations.

TL;DR: Stochastic search and optimisation algorithms originated from the natural evolution principles and are robust, adaptive and have found their application in a wide range of applications.