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Recent reports from Independent System Operators (ISOs) have raised some concerns about the impact of convergence bids (CBs) on nodal electricity markets. In particular, in some cases, there are concerns about cases where CBs are profitable for some market participants without increasing market efficiency significantly or even decreasing market efficiency. The latter occurs when CBs create price divergence...
In this paper, an ensemble learning model, namely the random forest (RF) model, is used to predict both the exact values as well as the class labels of 24 hourly prices in the California Independent System Operator (CAISO)'s day-ahead electricity market. The focus is on predicting the prices for the Pacific Gas and Company (PG&E) default load aggregation point (DLAP). Several effective features,...
In this paper, a new scenario-based stochastic optimization framework is proposed for price-maker economic bidding in day-ahead and real-time markets. The presented methodology is general and can be applied to both demand and supply bids. That is, no restrictive assumptions are made on the characteristics of the pool and its agents. However, our focus is on the operation of time-shiftable loads with...
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