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Simulating the Operation of Markets for Bulk-Power Ancillary Services

Eric Hirst and Brendan Kirby

Year: 1998
Volume: Volume19
Number: Number 3
DOI: 10.5547/ISSN0195-6574-EJ-Vol19-No3-3
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The U.S. Federal Energy Regulatory Commission (FERC) requires electric utilities to offer six ancillary services. Most of the tariffs filed with FERC price these services on the basis of traditional cost-of-service (embedded) costs, Because most of these services are provided by generating units, however, it should be possible to create competitive markets for them. This paper describes, the structure of, and results from, a spreadsheet model that simulates markets for seven services: losses, regulation, spinning reserve, supplemental reserve, load following, energy imbalance, and voltage support. The model also analyzes, system control, although this service will continue to be provided solely by the system operator under cost-based prices. Developing this computer model demonstrated the likely complexity of markets for energy and ancillary services. This complexity arises because these markets are highly interdependent. For example, the cost of regulation (the frequent change in generator outputs to track the minute-to-minute fluctuations in system load) depends strongly on which units, are already being dispatched to provide energy and losses, their variable costs, and their operating levels relative to their maximum and minimum loading points.

Analyzing and Forecasting Zonal Imbalance Signs in the Italian Electricity Market

Francesco Lisi and Enrico Edoli

Year: 2018
Volume: Volume 39
Number: Number 5
DOI: 10.5547/01956574.39.5.flis
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In this paper, within the Italian electricity market, we analyse the features and the dynamics of the imbalance sign, defined as the sign of the algebraic sum of energy bought and sold by the national Transmission and System Operator during the real-time balancing of the electric network. The analyses provide evidence that the probability of having a positive (negative) sign exhibits a serial dependence structure and a dependence on the load periods, as well as on past history. Based on this evidence, we build a suitable model for zonal sign dynamics, and we use it for an out-of-sample forecasting exercise concerning the probability of a positive imbalance sign, πt. The results show that the zonal imbalance sign is 'predictable.' An economic evaluation of the benefits of using the proposed model is also provided. Keywords: Balancing and ancillary services markets, IPEX market, Zonal imbalance sign, Binary data models, Forecasting

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