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Summary form only given: In power market studies, the forecast of locational marginal price (LMP) relies on the load forecasting results from the viewpoint of planning. It is well known that short-term load forecasting results always carry certain degree of errors mainly due to the random nature of the load. At the same time, LMP step changes occur at critical load levels (CLLs). Therefore, it is...
A key requirement of electric system operation is the ability of system operators to manage all types of variability and uncertainty. Integrating large-scale wind power into electric system operation increases variability and uncertainty that can impact supply and demand balance performance requirements. Many Independent System Operators (ISOs) are in the process of addressing these challenges. The...
This paper proposes a novel technique to forecast day-ahead electricity prices based on Panel Cointegration (PC). The current researches on the electricity price forecasting focus on the analysis of unstable economic time series. However, due to the difference of the allocation of power resource and consumption in different regions, the time series of electricity consumption and sales price in a single...
This paper discusses risk management, contracting, and bidding for a wind power producer. A majority of the wind power in the United States is sold on long-term power purchase agreements, which hedge the wind power producer against future price risks. However, a significant amount is sold as merchant power and therefore is exposed to fluctuations in future electricity prices (day-ahead and real-time)...
In this paper, issues related to price forecasting in a smart grid environment are discussed. In such an environment, demand-side resources are enabled to play a bigger role in the operation of electricity markets, compared to the limited demand-side market participation in most of the existing markets. The response of the demand-side to price forecasts could impact the formation of price patterns,...
This paper presents a forecasting technique to predict next-day electricity spot prices and volatilities. Our technique combines a fundamental model formulated as supply stack modeling, with an econometric analysis based on the GARCH methodology. Empirical results from the wholesale electricity market of Great Britain are discussed.
This paper proposes a stochastic time-series based method to simulate the volatility of intermittent renewable generation and distributed storage devices along timeline. The proposed method can calculate the optimal timeline for different electricity markets and power systems. In practice, the proposed method is potentially useful for designing market rules and evaluating different design options...
The deregulation of the Electricity sector in US has led to a tremendous increase in the inter-regional wholesale electricity trade between neighboring utilities or regions. Valuable insights into such imports/exports ahead of time have become crucial market intelligence for the various academicians and market players associated with the industry. In this paper, it is demonstrated that the Box-Jenkins...
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