The expansion of residential demand response programs and increased deployment of controllable loads will require accurate appliance-level load modeling and forecasting. This paper proposes a conditional hidden semi-Markov model to describe the probabilistic nature of residential appliance demand, and an algorithm for short-term load forecasting. Model parameters are estimated directly from power consumption data using scalable statistical learning methods. Case studies performed using submetered 1-minute power consumption data from several types of appliances demonstrate the effectiveness of the model for load forecasting and anomaly detection.Index Terms-Hidden semi-Markov model, residential appliances, load model, short-term load forecast.
Abstract-The problem of multi-area interchange scheduling in the presence of stochastic generation and load is considered. A new interchange scheduling technique based on a two-stage stochastic minimization of overall expected operating cost is proposed. Because directly solving the stochastic optimization is intractable, an equivalent problem that maximizes the expected social welfare is formulated. The proposed technique leverages the operator's capability of forecasting locational marginal prices (LMPs) and obtains the optimal interchange schedule without iterations among operators.Index Terms-Inter-regional interchange scheduling, multiarea economic dispatch, seams issue.
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