Economic Valuation of Reserves in Power Systems With High Penetration of Wind Power

By Juan M. Morales, Antonio J. Conejo, Juan Pérez-Ruiz. IEEE Transactions on Power Systems, 2009

627 citations recorded by the source corpus.

Subfields: Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/0cfe3d430005543a026475ad7a131853e6c3b4fa

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In Electrical and Electronic Engineering

Citations in the corpus

A Convex Model of Risk-Based Unit Commitment for Day-Ahead Market Clearing Considering Wind Power Uncertainty (2015, methodology): “The objective function of SUC is usually the combination of the cost of here-and-now decisions and the expected cost associated with the redispatch of generators, the load shedding and wind curtailment in the wait-and-see decisions [8], [9].”
Solving Multiperiod OPF Problems Using an AC-QP Algorithm Initialized With an SOCP Relaxation (2017, methodology): “Some recent techniques for addressing uncertainty include adding a heuristically chosen set of scenarios to the OPF problem [50]– [52], assuming a closed-form uncertainty distribution to analytically reformulate the OPF problem [53], [54], and scenario approaches that offer performance guarantees [5”
Adaptive Robust Optimization With Dynamic Uncertainty Sets for Multi-Period Economic Dispatch Under Significant Wind (2014, background): “[18] deals with the selection of spinning and nonspinning reserves through a market-clearing model under stochastic wind power generation.”
Setting the Operating Reserve Using Probabilistic Wind Power Forecasts (2011, background): “[25] describe a two-stage stochastic programming problem to compute the optimal reserve level and the cost of providing such reserve.”
Multiarea Stochastic Unit Commitment for High Wind Penetration in a Transmission Constrained Network (2013, methodology): “The modeling contribution of the paper relies on the use of authentic and detailed data for evaluating the cost of large-scale renewable energy integration and its impact on day-ahead reserve requirements while accounting for transmission constrains and component failures.”
Opportunity Cost Bidding by Wind Generators in Forward Markets: Analytical Results (2011, background): “Other relevant work includes a detailed discussion of utility metrics for risk-averse traders [9], assessment of the cost of wind forecast errors [10] and real-time prices [11], advanced wind forecasting methods [12], operational strategies coordinating wind generation with reserves, storage, and hy”
Enterprise-wide optimization for industrial demand side management: Fundamentals, advances, and perspectives (2016, background): “Previous works have focused on the problem of deciding how much reserve is required in the grid (Wang et al., 2005; Morales et al., 2009; Xiao et al., 2011).”
Chance-Constrained Day-Ahead Scheduling in Stochastic Power System Operation (2014, methodology): “Reference [16] presents a UC model for balancing a high penetration level of wind energy with required spinning reserves.”
Distributionally Robust Co-Optimization of Energy and Reserve Dispatch (2016, methodology): “Provided with the PDFs of wind power, the unit commitment, economic dispatch and spinning reserve can be scheduled in the framework of stochastic optimization (SO), including the scenario based models [13]–[17] and the chance-constraints based models [18]–[21].”
Multi-Area Energy and Reserve Dispatch Under Wind Uncertainty and Equipment Failures (2013, background): “For example, [5], [8] and [10] consider only equipment failures (discrete in nature) as scenarios in the model, while references [6], [7] and [9] only consider wind uncertainty (continuous in nature) in their stochastic model.”
Large-Scale Integration of Deferrable Demand and Renewable Energy Sources (2014, neutral): “[6], Bouffard et al.”
Spinning Reserve Estimation in Microgrids (2009, methodology): “Similar to the classification of the analytical SR optimization methods, the stochastic SR optimization methods include successive iteration of stochastic UC [28], reliability constrained stochastic UC [29], and stochastic programming based on the cost/benefit analysis [11, 30-34].”
Finding Equilibria in the Pool-Based Electricity Market With Strategic Wind Power Producers and Network Constraints (2017, background): “In this paper, the total required up and down reserves of the power system are simplified as a function of the standard deviations of the forecasted wind power and total demand of the system as follows [19]”
Optimal bidding strategy of a strategic wind power producer in the short-term market (2015, background): “In this paper, these forecast errors are handled by up and down reserves, which are scheduled as functions of the standard deviations of the forecasted wind power and the total forecasted demand of the system as follows [24]:”
The role of demand response in single and multi-objective wind-thermal generation scheduling: A stochastic programming (2014, background): “In current power systems, ISOs (Independent System Operators) consider enough spinning and non-spinning reserves provided by generators for compensation of unpredictable nature of wind power [3].”
Pricing Electricity in Pools With Wind Producers (2012, background): “This model is extended in [6] to incorporate wind power producers.”
Chance-Constrained Two-Stage Unit Commitment Under Uncertain Load and Wind Power Output Using Bilinear Benders Decomposition (2016, methodology): “As a result, a deterministic UC model will be converted into a two-stage stochastic UC (SUC) model [9].”