A novel market mechanism is proposed to charge the uncertainty and credit the generation reserve in the Day-ahead market within a Robust Security-Constrained Unit Commitment (RSCUC) optimization framework. The increasing penetration of renewable energy in recent years has led to more uncertainties in power systems. These uncertainties have to be accommodated by flexible resources (i.e. upward a...

We propose a simple model that integrates twoperiod electricity markets, uncertainty in renewable generation, and real-time dynamic demand response. A load-serving entity decides its day-ahead procurement to optimize expected social welfare a day before energy delivery. At delivery time when renewable generation is realized, it sets prices to manage demand and purchase additional power on the r...

This paper quantifies the economic benefits associated with the introduction of greater spatial granularity in short-term pricing in the California wholesale electricity market. On April 1, 2009, California switched to a nodalpricing market with an integrated day-ahead forward market and real-time imbalance market from its original zonal market design with bilateral day-ahead scheduling, a real...

In recent decades, the traditional monopolistic energy exchange market has been replaced by deregulated, competitive marketplaces in which electricity may be purchased and sold at prices like any other commodity. As a result, deregulation of industry produced demand for wholesale organized marketplaces. Price predictions, are primarily meant to establish clearing price, have become significant ...

In this study, we investigate the maximum possible profit for a commercial office building participating in New York’s Day-Ahead Demand Response (DADR) program. We formulate an optimal control problem, assuming perfect knowledge of future weather, occupancy, and day-ahead electricity price predictions to examine this potential benefit. Then, a practical control strategy based upon the framework...

The quality of short-term electricity load forecasting is crucial to the operations and trading activities of market participants in an electricity market. In this paper, a multiple equation time series model for intra-day and day-ahead load forecasting is built. The model uses lagged load and temperature as the primary explanatory variables but makes effective use of diurnal characteristics an...

In [1] the use of VCG in matching markets is motivated by saying that in order to compute market clearing prices in a matching market, the auctioneer needs to know the true valuations of the bidders. Hence VCG and corresponding personalized prices are proposed as an incentive compatible mechanism. The same line of argument pops up in several lecture sheets and other documents related to courses...

This project is focused on the design of price forecasting tools for market operators and for market traders, taking into account the distinct purposes, data availability, and time horizons of the distinct users. Empirical price data from the MISO and RTE have been analyzed. A combined model is developed to forecast MISO day-ahead nodal prices. An ARIMA model is constructed to forecast RTE week...

General Equilibrium and the Emergence of (Non) Market Clearing Trading Institutions We consider a pure exchange economy, where for each good several trading institutions are available, only one of which is market-clearing. The other feasible trading institutions lead to rationing. To learn on which trading institutions to coordinate, traders follow behavioural rules of thumb that are based on t...

Purpose of the paper The Basel Committee regulations require the estimation of Value-at-Risk at 99% confidence level for a 10-trading-day-ahead forecasting horizon. The paper provides a multivariate modelling framework for multi-period VaR estimates for leptokurtic and asymmetrically distributed real-estate portfolio returns. The purpose of the paper is to estimate accurate 10-day-ahead 99% VaR...