It is very important to forecast electricity price in a deregulated electricity market for choosing the bidding strategy, and it is the most important signal for other players. It engulfs information for both customers and producers in order to maximize their profit. Thus, choosing the best method of price forecasting is a crucial task to have the most accurate forecast. In this paper the price...

In this paper, for efficient energy consumption through the residential demand response in the smart grid, an optimization algorithm, which can provide a schedule plan for the home appliance usages, is proposed. In order to minimize the average electricity price based on the time-varying electricity price in conjunction with the peak hourly load, which decides the capacity of the electric suppl...

The electricity market is a very peculiar market due to the large variety of phenomena that can affect the spot price. However, this market still shows many typical features of other speculative (commodity) markets like, for instance, data clustering and mean reversion. We apply the diffusion entropy analysis (DEA) to the Nordic spot electricity market (Nord Pool). We study the waiting time sta...

Energy companies with commitments to meet customers’ daily electricity demands face the problem of hedging load and price risk. We propose a joint model for load and price dynamics, which is motivated by the goal of facilitating optimal hedging decisions, while also intuitively capturing the key features of the electricity market. Driven by three stochastic factors including the load process, o...

In Beijing, China, the rational consumption of energy is affected by the insufficient linkage mechanism of the energy pricing system, the unreasonable price ratio and other issues. This paper combines the characteristics of Beijing’s energy market, putting forward the society-economy equilibrium indicator R maximization taking into consideration the mitigation cost to determine a reasonable pri...

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 ...

The American electric power industry is undergoing dramatic changes in the way it is structured and regulated. As of June of 1998, state utility regulators, state legislatures or both in 17 states had made the decision to implement retail competition within 5 years or less. Competition in electricity markets and associated new opportunities for expanded interregional electricity trading could r...

Market based valuation of generation assets is a critical problem in competitive power markets. Previous approaches to this problem has included modeling the cash flow from a generator as a spread option between electricity and fuel prices, which ignores the effect of flexibility and startup costs. Simulation based approaches with full unit commitment constraint have been presented, but they ar...

This article argues that competitive electricity markets are prone to the same cycles of boom and bust that appear in commodity markets and in a specialized industry like real estate. The article then demonstrates how boom and bust might appear in the western electricity system using computer simulation. A “business as usual” simulation shows that the west might be at the crest of a building bo...

The electricity market, monopolistic in nature, with government price regulation, poses a serious challenge for policy makers with respect to the cost-effectiveness of emissions trading, particularly in Asian countries. This paper argues that a cap-and-trade regulatory system for indirect emissions combined with a rate-based allocation system for direct emissions can achieve market efficiency e...