A linear programming method for the scheduling of pumped-storage units with oscillatory stability constraints

Jeng, Lin-Her; Hsu, Yuan‐Yih; Chang, B.S.; Chen, K.K.

doi:10.1109/59.544631

Cited by 15 publications

(1 citation statement)

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“…In [1], an approach, which attempts to combine the advantages of dynamic programming, Lagrange duality and network flow programming technique while avoiding their shortcomings, is developed to solve the short-term scheduling problem of the PSU. In [2], the differential dynamic programming is firstly employed to reach the most economical schedule for the PSU; then a linear programming method is used to refine the preliminary schedule in order to improve the damping for the inter-area mode. In [3], an extension of the Baleriaux methodology representing the chronological aspects of reservoir operation is presented, where the production costing problem is decomposed into a sequence of chronological hydro reliability problems.…”

Section: Introductionmentioning

confidence: 99%

The Equilibrium Model of Electricity Market with Consideration of the Pumped Storage GenCo

Yang¹,

Lu²,

Shi³

2012

AMR

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Pumped storage is the largest-capacity form of grid energy storage available. A multi-period oligopolistic model for analyzing the bidding strategies of pumped storage GenCo (PSG) is proposed in this paper. In the pumping periods, the pumped storage unit (PSU) is simulated as a special load. While in generating periods, PSU is treated as a normal generator. In this model, all GenCos are assumed to exercise Cournot strategies to maximize their own profits. The resulting equilibrium formulation is established in terms of a mixed linear complementarity problem. The purpose of this paper is to provide an efficient simulation tool for the PSG to determine its bidding strategy in an oligopolistic environment. The proposed model can also be used to study various factors that may impact PSG’s profit. Results of a six-bus test system are analyzed to illustrate the characteristics of the proposed model.

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Section: Introductionmentioning

confidence: 99%