Abstract
The need for flexible service provision in electric power systems has dramatically increased due to the growing penetration of variable energy resources, as has the need to ensure fair access and compensation for this provision. A swing contract facilitates flexible service provision with appropriate compensation because it permits multiple services to be offered together in bundled form with each service expressed as a range of possible values rather than as a single point value. This paper discusses a new swing-contract market design for electric power systems that permits swing contracts to be offered by any dispatchable resource. An analytical optimization formulation is developed for the clearing of a swing-contract day-ahead market that can be implemented using any standard mixed-integer linear programming solver. The practical feasibility of the optimization formulation is demonstrated by means of a numerical example.
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Notes
- 1.
The present study is a substantial extension of an earlier preliminary study [17] by the authors appearing in an electronic conference proceedings.
- 2.
As stressed in [1], the services extracted from resources can alternatively be expressed in terms of their frequency bandwidth characteristics. The general concept of a swing contract does not depend on the exact manner in which services are characterized.
- 3.
For example, CAISO defines the mileage of a planned power path for a dispatchable resource to be the summation of the absolute changes in the successive automated generation control (AGC) set points that are used to communicate power dispatch instructions to this resource [15].
- 4.
Current penalties for failure to follow dispatch instructions are administratively determined. For example, CAISO uses a comparison of AGC set points to actual telemetry in order to judge the accuracy with which dispatch instructions have been followed. It then adjusts mileage payments when a resource fails to provide the power movements called for by dispatch instructions [15].
- 5.
The availability price α requested by the seller of an SC, i.e., the SC’s offer price, is not considered to be part of the SC itself. In economics, physical commodities (e.g., apples) are considered separately from their offer prices. Similarly, standardized financial contracts (e.g., bonds) are treated as commodities that can be purchased in various market settings at possibly varying offer prices. In principle, this separation between a commodity/contract and its offer price facilitates price competition among commodity/contract sellers, thus increasing the likelihood that prices will be driven to efficient levels. See [21] for further discussion of this point.
- 6.
To help ensure the physical feasibility of offered SCs, an ISO might want to require all offered SCs to include in their performance payment methods some type of standardized failure-to-perform penalties. The severity of these penalties could be conditioned on the severity of past and current transgressions.
- 7.
- 8.
A GenCo is an entity that produces (supplies) power for an electric power grid. The term load is used in two senses: (i) to refer to an entity that consumes (absorbs) power from an electric power grid and (ii) to refer to the power demands of such entities. The term net load is defined to be power demand net of non-dispatchable generation, such as wind or solar power. An LSE is an entity that secures power, transmission, and related services at the wholesale level in order to service the load (power demands) of its retail customers. An ISO/RTO is an organization charged with the primary responsibility of maintaining the security of an electric power system and often with system operation responsibilities as well. The ISO/RTO is required to be independent, meaning it cannot have a conflict of interest in carrying out these responsibilities, such as an ownership stake in generation or transmission facilities within the power system.
- 9.
LMP is the pricing of electric power according to the timing and location of its withdrawal from, or injection into, an electric power grid.
- 10.
These system constraints include power balance constraints, line and generation capacity limits, down/up ramping restrictions, minimum down/up-time requirements, and reserve requirements.
- 11.
An example of a DRR would be an entity that manages a collection of distributed energy resources (DERs), such as household appliances. Even if individual DERs have relatively small amounts of down/up flexibility in their power usage due to local goals and constraints, a sufficiently large collection of these DERs could permit the extraction of down/up demand response services with substantial flexibility.
- 12.
See [14] for a discussion of the more general case in which offers can take the form of portfolios consisting of multiple SCs.
- 13.
As discussed in [14], option SCs seem to be a more suitable vehicle than firm SCs for handling contingency reserve requirements.
- 14.
See Table 5 in the Appendix for definitions of all terms appearing in the following equations. Although power levels pm(t) for all market participants \(m \in \mathbb {M}\) nominally appear in the objective function (2), it will be seen below that the constraints for this SC DAM optimization formulation restrict the power amounts for market participants with non-cleared SCs to be zero.
- 15.
The absolute value terms |pm(t)| in the objective function (2) do not pose any computational difficulty. Because the goal is to minimize this objective function, these absolute value terms can equivalently be represented in terms of linear inequality constraints, as follows. First, introduce new decision variables for the ISO: \(p^a_m(t), \forall m \in \mathbb {M}\), \(t \in \mathbb {T}\). Second, in the objective function (2), replace |pm(t)| by \(p^a_m(t)\), \(\forall m \in \mathbb {M}\), \(t \in \mathbb {T}\). Third, include the following additional linear inequality constraints in the constraint set: \( p^a_m \geq p_m ~\text{and}~ p^a_m \geq -p_m \, ,\, \forall m \in \mathbb {M}, t \in \mathbb {T}.\) Any solution for the resulting constrained minimization problem will then require \(p^a_m(t) = |p_m(t)|, \, \forall m \in \mathbb {M}, t \in \mathbb {T}.\)
- 16.
As in any market, increased competition among SC providers should reduce the need of an ISO to clear SCs that entail excess resource availability.
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Acknowledgements
This research has been supported in part by grants from the ISU Electric Power Research Center (EPRC), the Sandia National Laboratories (Contract No. 1163155), and the Department of Energy (DE-AR0000214 and DE-OE0000839). The authors are grateful to the editors and four reviewers for constructive comments and to Zhaoyu Wang and Shanshan Ma for helpful discussions related to the topic of this study.
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Li, W., Tesfatsion, L. (2018). A Swing-Contract Market Design for Flexible Service Provision in Electric Power Systems. In: Meyn, S., Samad, T., Hiskens, I., Stoustrup, J. (eds) Energy Markets and Responsive Grids. The IMA Volumes in Mathematics and its Applications, vol 162. Springer, New York, NY. https://doi.org/10.1007/978-1-4939-7822-9_5
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