03:30 PM - 03:55 PM
Strategic Bidding Under Wind Uncertainty: A Robust Equilibrium Method
In this work, we present a practical method for strategic GenCos to properly hedge against wind uncertainty and guarantee the revenue security using a robust optimization. First the strategic offering problem is formulated as a bilevel programming, which the upper-level problem represents the profit maximization for the strategic GenCos subject to the unit constraints and to the Independent System Operator (ISO) problem as the lower-level optimization problem. The lower optimization problem represents the market clearing mechanism by minimizing the overall operation cost based on power systems security and reliability in the presence of wind power. The upper-level and lower-level problems are tightly coupled since the upper-level problem provides the optimal bidding parameter for the lower-level problem and the lower-level problem determines the Locational Marginal Prices (LMPs) and the production quantities. The LMPs and production quantities that follow from the lower-level problem have a direct effect on the strategic bidding parameter as a result of the upper-level problem.
03:55 PM - 04:20 PM
Electric Vehicle Aggregator/System Operator Coordination for Optimal Charging Scheduling and Services Procurement
We present the necessary adaptations in market clearing algorithms to integrate aggregated fleets of electric vehicles in typical North American electricity markets. We show how aggregation and market coordination are indeed necessary to avoid potential generation capacity shortages and to obtain the best use of generation resources for fleet charging.
04:20 PM - 04:45 PM
Optimization of Wind, Diesel and Battery Systems for Remote Areas
Hybrid energy systems are often designed by simulation. In that case, rules of dispatching must be settled by deciders and influence results. We present a linear-integer programing model to find the optimal design and dispatching scenario without rules. The best implantable rules are then extracted from these results.
04:45 PM - 05:10 PM
Improving the Mixed Integer Linear Programming (MILP) Formulation for Unit Commitment Problems
We present two ways to improve the MILP formulation for the unit commitment problem. The first is a new class of inequalities that give a tighter description of the feasible generator schedules. The second is a modified orbital branching technique that exploits the symmetry created by identical generators.