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In the face of extreme events, e.g., hurricanes, the transmission systems, especially the transmission lines, are affected across time and space. To mitigate these impacts on the day-ahead market from a probabilistic perspective, a resilient unit commitment (UC) problem is formulated as a two-stage distributionally robust and robust optimization (DR&RO) problem. In the first stage, the commitment, energy, and reserves of generators are pre-scheduled to minimize the operational cost, responding to the worst load forecasting and line failure scenario in the operating day. The operating status of transmission lines are depicted by a novel uncertainty set with a distributionally chance constraint considering the repair of failed lines. This chance constraint is reformulated to its deterministic equivalence. Using both load shedding and generation curtailment, recourse problems are formulated in the second stage considering the time-varying operating status of transmission lines. The formulated DR&RO problem is solved using a hybrid Benders decomposition and column-and-constraint generation scheme. Simulations are conducted on the modified IEEE reliability test system (RTS) and two-area IEEE RTS-96 under hurricanes. Results verify the effectiveness of the proposed method, in comparison with prevalent two-stage stochastic and robust optimization methods. [ABSTRACT FROM AUTHOR]

Uncertainty and geographical diversity of wind speeds create risk for a wind power generation company (WGenco) to make the maximum profit from power market trading. A probabilistic approach is proposed to estimate the profit of a WGenco considering geographical diversity and uncertainty of wind speeds and market prices. The objective of the optimization problem is to assist a WGenco to do the optimal bidding in market trading in order to make the maximum profit under various market and wind speed uncertainties. The point estimate method (PEM) has been improved to facilitate stochastic modeling of the aggregated power output of wind turbine generators in different locations in the problem formulation. The principal component analysis (PCA) is used to manage correlated wind speeds. [ABSTRACT FROM AUTHOR]

This paper presents a probabilistic approach in the modeling of stand-alone microgrids to predict their operational adequacy performance considering uncertainty of energy storage system (ESS), photovoltaic system (PVS) and conventional generator (CG). Instead of using the daily or hourly time step, operating period a minutely time step is considered to incorporate the effect of fast ramp up/down of system components on microgrid operating adequacy through expected energy not supplied (EENS) and expected energy not used (EENU), due to load and resource variations. A time varying state of charge (SOC) model is proposed to determine power output of an ESS in reliability modeling. The reliability of a PVS is modeled in detail based on the total cross-tied configuration (TCTC) of photovoltaic (PV) cells and arrays. The proposed technique and indices will be useful for system planners to select the type and size of microgrid systems that contain alternative energy sources and storage. [ABSTRACT FROM PUBLISHER]

Based on the decentralized sliding mode control, a load frequency controller is designed in this paper for multi-area interconnected power systems with matching and unmatched uncertainties. The proportional and integral switching surface is constructed for each area to improve system dynamic performance in reaching intervals. The robust controller is proposed by the reaching law method to assure that frequency fluctuation converges to zero after a load and operation point variation. A three-area interconnected power system is studied to illustrate the effectiveness of the proposed decentralized sliding mode control scheme. [ABSTRACT FROM PUBLISHER]

In a power system with high wind power penetration, reliability-based reserve expansion is a major problem of system planning and operation due to the uncertainty and fast fluctuation of wind speeds. This paper studied the impact of high wind power penetration on the system reserve and reliability from long-term planning point of view utilizing universal generating function (UGF) methods. The reliability models of wind farms and conventional generators are represented as the corresponding UGFs, and the special operators for these UGFs are defined to evaluate the customer and the system reliabilities. The effect of transmission network on customer reliabilities is also considered in the system UGF. The power output models of wind turbine generators in a wind farm considering wind speed correlation and un-correlation are developed, respectively. A reliability-based reserve expansion method is proposed to determine the conventional reserve required for power systems with high wind power penetration. The IEEE-RTS has been modified to illustrate the applications of the proposed method. [ABSTRACT FROM PUBLISHER]