This paper describes a coordination process between GENCOs and the ISO for congestion management and reducing the risk of failure to supply loads. The algorithm underlining the coordination technique is the security-c...
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ISBN:
(纸本)0780375203
This paper describes a coordination process between GENCOs and the ISO for congestion management and reducing the risk of failure to supply loads. The algorithm underlining the coordination technique is the security-constrained price-based unit commitment (SPUC) which is implemented in two statges. At first, GENCOs apply priced-basedunitcommitment (without transmission security constraints), schedule their generating units and submit their energy and capacity bids to the ISO for maximizing their revenues. The ISO obtains transmission information as well from TRANSCOs via OASIS. Using the two sets of generation and transmission data, the ISO executes inter-zonal and intra-zonal congestion management and contingency analysis for minimizing line flow violations and the risk supplying loads. As part of this package, the ISO would have a chance to minimize both transmission flow and reactive (bus voltage) violations. If transmission flow violations persist after the adjustments are made, the solution would provide a signal to GENCOs, based on Benders decomposition, for modifying their initial bids. Accordingly, additional constraints will be introduced in GENCOs for rescheduling generating units and submitting modified bids to the ISO.
This paper describes a coordination process between GENCOs and the ISO for congestion management and reducing the risk of failure to supply loads. The algorithm underlining the coordination technique is the security-c...
详细信息
This paper describes a coordination process between GENCOs and the ISO for congestion management and reducing the risk of failure to supply loads. The algorithm underlining the coordination technique is the security-constrained price-based unit commitment (SPUC) which is implemented in two stages. At first, GENCOs apply priced-basedunitcommitment (without transmission security constraints), schedule their generating units and submit their bids to the ISO for maximizing their profits. The ISO obtains transmission information as well from TRANSCOs via OASIS. The ISO executes congestion management and contingency analysis for minimizing line flow violations and the risk supplying loads. If transmission flow violations persist after the adjustments are made, the solution would provide a signal to GENCOs for modifying their initial bids. Accordingly, additional constraints will be introduced in GENCOs for rescheduling generating units and submitting modified bids to the ISO. Two 36 unit GENCOs are used to demonstrate the efficiency of the proposed algorithm. (C) 2003 Elsevier Science B.V. All rights reserved.
Virtual power plant (VPP) concept was developed to integrate distributed energy resources (DERs) into the grid in order that they are seen as a single power plant by the market and power system operator. Therefore, VP...
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Virtual power plant (VPP) concept was developed to integrate distributed energy resources (DERs) into the grid in order that they are seen as a single power plant by the market and power system operator. Therefore, VPPs are faced with optimal bidding, and identifying arbitrage opportunities in a market environment. In this study, the authors present an arbitrage strategy for VPPs by participating in energy and ancillary service (i.e. spinning reserve and reactive power services) markets. On the basis of a security-constrained price-based unit commitment, their proposed model maximises VPP's profit (revenue minus costs) considering arbitrage opportunities. The supply-demand balancing, transmission network topology and security constraints are considered to ensure reliable operation of VPP. The mathematical model is a mixed-integer non-linear optimisation problem with inter-temporal constraints, and solved by mixed-integer non-linear programming. The result is a single optimal bidding profile and a schedule for managing active and reactive power under participating in the markets. These profile and schedule consider the DERs and network constraints simultaneously, and explore arbitrage opportunities of VPP. Results pertaining to an illustrative example and a case study are discussed.
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