In this paper a new Hybrid technique of Artificial Neural Network (ANN) and Vector Evaluated Particle Swarm Optimization (VEPSO) is presented as a forecasting strategy for day-ahead price of electricity market. The proposed technique the proposed intelligent technique is applied to weights and bias of ANN to improve the learning capability through the minimum error. A comprehensive comparative ...

Purpose – Price forecasting is essential for risk management in deregulated electricity markets. The purpose of this paper is to propose a hybrid technique using wavelet transform (WT) and multiple linear regression (MLR) to forecast price profile in electricity markets. Design/methodology/approach – Price series is highly volatile and non-stationary in nature. In this work, initially complete ...

This paper proposes a swarm intelligence long-term hedging tool to support electricity producers in competitive electricity markets. This tool investigates the long-term hedging opportunities available to electric power producers through the use of contracts with physical (spot and forward) and financial (options) settlement. To find the optimal portfolio the producer risk preference is stated ...

Offshore wind farm (WF) projects have been promoted by support schemes as part of the expansion of renewable energy resources in Korea. This paper examines in detail how the Renewable Portfolio Standard (RPS), which was adopted post the Feed-in-Tariff scheme in 2012, has had a profound impact on the economic benefits of offshore WFs in Korea. A framework for analyzing the economic viability of ...

This paper proposes a swarm intelligence long-term hedging tool to support electricity producers in competitive electricity markets. This tool investigates the long-term hedging opportunities available to electric power producers through the use of contracts with physical (spot and forward) and financial (options) settlement. To find the optimal portfolio the producer risk preference is stated ...

Distributed storage systems at the end consumer level could provide a remarkable load shifting potential that could be used to increase the demand side’s flexibility without requiring behavioral changes from the end consumer. This article analyzes the economics of such storage systems with regard to the storage technology applied and the quality of price and load forecasts, which are needed to ...

This paper derives revenue-maximising and risk-constrained strategies for stochastic generators participating in electricity markets with a single-price balancing mechanism. The solution to this problem requires forecasts of multiple processes: the participant’s energy production, day-ahead and balancing electricity prices, and the system length. By formulating the problem from a probabilistic ...

A combined wavelet transform (WT) and multiple linear regression (MLR) based technique to forecast price profile in a single settlement real time electricity market has been presented. The historical price and load data has been decomposed into better-behaved wavelet domain constitutive subseries using WT and then combined with other time domain variables to form the set of input variables for ...

We study the costs of coal-fired electricity in the United States between 1882 and 2006 by decomposing it in terms of the price of coal, transportation costs, energy density, thermal efficiency, plant construction cost, interest rate, and capacity factor. The dominant determinants of costs at present are the price of coal and plant construction cost. The price of coal appears to fluctuate more ...