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Probabilistic Zonal Reserve Requirements for Improved Energy Management and Deliverability With Wind Power Uncertainty

Byungkwon Park, Zhi Zhou, Audun Botterud, Prakash Thimmapuram

2020IEEE Transactions on Power Systems33 citationsDOIOpen Access PDF

Abstract

In power systems with high penetration of renewable energy resources, uncertainty and variability of these stochastic resources introduce additional challenges for the operation of power systems. To improve the power system's reliability in the face of uncertainty, reserves are required as additional generation capacity to rebalance the power system following random disturbances. However, reserve deliverability is not guaranteed, because it may encounter potential transmission line congestion. Zonal reserve requirements can address this issue, but operators lack efficient ways to allocate reserves to zones while accounting for wind power forecast uncertainty. We propose a methodology for probabilistic zonal reserve requirements to address wind power forecast uncertainties. This method estimates the probability distribution of line flows based on the system generation margin and injection shift factor. This estimate is then used to construct pre-defined and post-zonal reserve requirements. Case studies demonstrate that the proposed method efficiently schedules energy and reserves to balance energy and manage deliverability with wind power forecast uncertainty. We also discuss operational implications of the proposed method.

Topics & Concepts

Probabilistic logicElectric power systemWind powerReliability engineeringReserve requirementRenewable energyComputer scienceReliability (semiconductor)Electricity generationMathematical optimizationPower (physics)EngineeringMathematicsElectrical engineeringEconomicsMonetary policyArtificial intelligenceMonetary economicsPhysicsCentral bankQuantum mechanicsElectric Power System OptimizationPower System Reliability and MaintenanceEnergy Load and Power Forecasting
Probabilistic Zonal Reserve Requirements for Improved Energy Management and Deliverability With Wind Power Uncertainty | Litcius