In the present study Artificial Neural Network (ANN) has been optimized using a hybrid algorithm of Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). The hybrid GA-PSO algorithm has been used to improve the estimation of electricity demand of the state of Tamil Nadu in India. The ANN-GA-PSO model uses gross domestic product (GSDP); electricity consumption per capita; income growth r...

This paper examines the application of artificial neural networks (ANNs) to the modelling and forecasting of electricity demand experienced by an electricity supplier. The data used in the application examples relates to the national electricity demand in the Republic of Ireland, generously supplied by the Electricity Supply Board (ESB). The paper focusses on three different time scales of inte...

In the restructured electricity industry, electricity pooling markets are an oligopoly with strategic producers possessing private information (private production cost function). We focus on pooling markets where aggregate demand is represented by a non-strategic agent. Inelasticity of demand is a main difficulty in electricity markets which can potentially result in market failure and high pri...

Forecasting electricity consumption has often prefered to treat socioeconomic activity and wealth as exogenous. The motivation for this research is to endogenize electricity consumption with economic activity by introducing electricity demand, and the interactions between electricity use and economic activity, into macroeconomic demand equations. In this paper, I create an energy and macroecono...

Driven by concerns regarding environmental sustainability, energy security, and economic growth, a fundamental transformation is taking hold in the electricity sector. Advanced communications technologies and information systems (IS) will play a central role in the realization of the ‘smart grid’, an intelligent and multi-directional electricity supply chain from generation to end-user consumpt...

Two of the most important technologies for future power systems to reduce greenhouse gas are electric vehicles (EVs) and renewable generation. When EVs become more common, the overall demand of electricity will significantly increase because EVs consume a large amount of electricity. Also, a daily load curve with EVs heavily depends on how much electricity EVs consume and when electricity is co...

In a competitive electricity market environment, power producers and consumers need, on one hand, accurate load and/or electricity consumption forecasting tools. These tools will ensure an a-priori knowledge on the amount of energy needed for production. On the other hand, forecasting electricity prices, may play a very important role for producers and consumers when planning bidding strategies...

In 2015, space heating and domestic hot water production accounted for around 40% of the Swiss final energy consumption. Reaching the goals of the 2050 energy strategy will require significantly reducing this share despite the growing building stock. Renewables are numerous but subject to spatial–temporal constraints. Territorial planning of energy distribution systems enabling the integration ...

High electricity demand peaks and uncertain supply from renewable energy sources have a significant impact on the electricity price and the network capacity. One mechanism proposed to tackle this issue is the use of real-time pricing (RTP) at the end customer level. Here electricity retail prices are set in real-time in response to varying supply-demand conditions in a way that reduces peak dem...

Renewable Energy based microgrids are being considered to provide electricity for the expanding energy demand in the grid distribution network and grid isolated areas. The technical challenges associated with the operation and controls are immense. Electricity generation by Renewable Energy Sources is of stochastic nature such that there is a demand for regulation of voltage output in order to ...