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Renewable energy-based generation facilities emerging in microgrids are modifying many traditional principles of economic dispatch because of the variability and uncertainty of their output characteristics. Since the power generation from renewable resources is difficult to anticipate, a real-time adjustment of generation schedules is necessary after more forecast information becomes available. Intra-hour, or ultra-short-term dispatch, allows microgrid operators to frequently update generators’ outputs for providing power supplies efficiently in an uncertain operating condition. However, several technical challenges such as information availability, control architecture, and computational burden make it difficult to find an optimal generation schedule at runtime. This work addresses the intra-hour economic dispatch problem by designing a closed-loop distributed model predictive control (DMPC) that reduces potential variations in the determined generation schedules. At first, optimization problems regarding the behaviors of several participants in a microgrid are formulated. Then, the procedures for achieving the real-time power balance under ramp-rate constraints are detailed. Simulation results present the efficiency of the proposed DMPC for the optimal intra-hour economic dispatch when multiple types of generation resources are considered in a microgrid.

Power system operation has been a very complex and interesting problem, and currently has gathered more attention because of new elements in the network. New elements such as renewable sources, demand response, electric vehicles, and energy storage systems, are crucial because of their stochastic behavior. Stochastic variables present new challenges for the system operator, who must prevent future changes in the network status by taking efficient decisions with available information and guarantee the system security. In this document we show that Model Predictive Control (MPC) might be appropriate to solve the economic dispatch problem when feasible future events are considered. A case study is solved from different perspectives of the system operator, which is able to consider or neglect future events. Results show that MPC efficiently solves the economic dispatch problem when considering future events and ramp rate constraints.

This paper applies the conceptual framework applied in the work of Oum et al. to hedge retailers against price-quantity fluctuations in spot electricity markets, and extends it to power generators, in order to design suitable power options with optimal strike prices from a market maker's perspective. These options are then used to hedge agents against price and quantity fluctuations by maximizing a static expected utility problem. An infinite collection of derivatives (“exotic option”) emerges as the solution of both price and quantity hedging. This exotic option is approximated with a portfolio composed by bonds, forward/futures contracts, and a fixed number of put and call options, employing a plausible replicating strategy. The theoretical framework is tested within the context of the Colombian power market, and is applied to month-ahead and quarterly-ahead hedging during on-peak hours. The proposal addresses major problems such as lack of liquidity and anonymity of the current bilateral electricity trading scheme in Colombia.