A multi-timescale hybrid stochastic/deterministic generation scheduling framework with flexiramp and cycliramp costs
Abstract Flexible ramping products (flexiramp), provided by entitled resources to meet net demand forecast error, are the underpinning for the accommodation of the substantial uncertainties associated with variable wind power. This paper proposes an enhanced flexiramp modeling approach, cast in a hybrid stochastic/deterministic multi-timescale framework. The framework employs a chance-constrained day-ahead scheduling method, as well as deterministic scheduling on intra-hourly basis (real-time scheduling), to allow optimal procurement planning of the flexiramp products in both timescales. A stepwise and piecewise demand price curve is also proposed to calculate the flexiramp surplus procurement price. Non-generation resource (NGR), referring to energy storage, is implemented to provide extra flexibility. Additionally, cycling ramping cost (cycliramp), introduced to model operational and maintenance costs and reduce the wear and tear of generators, is also included as a penalty. Numerical tests are conducted on 6-bus and 118-bus systems. Results demonstrate the merits of the proposed scheduling model as well as the effects of flexiramp and cycliramp costs in the multi-timescale scheduling. Highlights An HSD-MTS framework is proposed for optimal flexiramp procurement. Flexiramp surplus piecewise cost function and flexiramp reserve are introduced. Discrete PDF chance-constrained programming is utilized in day-ahead scheduling. PDR is adopted to linearize the chance constraints and expedite the computation. Results show the elasticity of HSD-MTS in flexiramp procurement in DASO and RTDO.
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