A Dynamic Market Mechanism for Markets with Shiftable Demand Response

Hansen, Jesper Rohr; Knudsen, Jesper; Kiani, Arman; Annaswamy, Anuradha M.; Stoustrup, Jakob

doi:10.3182/20140824-6-za-1003.00620

Cited by 22 publications

(24 citation statements)

References 15 publications

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“…The incremental and base price coefficients determine the behavior of the adjustable portion of the demand. The consumption values are constrained; P 0Daj and P Dsj must evolve so that in equilibrium, P 0Daj reaches a value no smaller than the derived value P [40], with the base cost prices for the three types of generators modeled changed to reflect current energy prices from the EIA's Electricity Power Annual report [41]. The base cost is calculated by taking into account the penalties pipelines imposes on generators for taking fuel off of the Algonquin NG pipeline which services the New England area [39].…”

Section: A Case Studymentioning

confidence: 99%

“…The values for the consumer utility coefficients are as listed in Table II. In order to limit the amount of adjustable demand so that the effects of NG uncertainty can be studied better, the values in bold for U Daj have been modified from what was used in [40]. The incremental cost coefficient c Daj is set at a larger negative value than the shiftable demand so that consumers have lower willingness to adjust consumption and have a higher base utility of using electricity, much like a data center which would not change their consumption of electricity even if prices rise to very high levels.…”

Section: A Case Studymentioning

confidence: 99%

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Foundations of Infrastructure-CPS

Annaswamy

Hussain

Chakrabortty

et al. 2016

2016 American Control Conference (ACC)

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Abstract-Infrastructures have been around as long as urban centers, supporting a society's needs for its planning, operation, and safety. As we move deeper into the 21st century, these infrastructures are becoming smart -they monitor themselves, communicate, and most importantly self-govern, which we denote as Infrastructure CPS. Cyber-physical systems are now becoming increasingly prevalent and possibly even mainstream. With the basics of CPS in place, such as stability, robustness, and reliability properties at a systems level, and hybrid, switched, and eventtriggered properties at a network level, we believe that the time is right to go to the next step, Infrastructure CPS, which forms the focus of the proposed tutorial. We discuss three different foundations, (i) Human Empowerment, (ii) Transactive Control, and (iii) Resilience. This will be followed by two examples, one on the nexus between power and communication infrastructure, and the other between natural gas and electricity, both of which have been investigated extensively of late, and are emerging to be apt illustrations of Infrastructure CPS.

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Section: A Case Studymentioning

confidence: 99%

Section: A Case Studymentioning

confidence: 99%

Foundations of Infrastructure-CPS

Annaswamy

Hussain

Chakrabortty

et al. 2016

2016 American Control Conference (ACC)

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“…In addition, each house has a smart meter involving a software agent that is able to communicate with other agents and trade electricity automatically via a regional electricity market. The software agent also controls the battery and time-shiftable loads [11]- [13]. This means that, to a certain extent, the agent is able to alter the electricity demand of the house.…”

Section: Introductionmentioning

confidence: 99%

Risk-Limiting Real-Time Pricing for a Regional Prosumers' Electricity Network with Distributed Solar Power Generation

Kawasaki

Takata

Fukui

et al. 2017

SICE Journal of Control, Measurement, and System Integration

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: In this paper, we propose a novel risk-limiting real-time pricing mechanism for a regional electricity network of prosumers with distributed solar power generation. The target system is a regional electricity network that consists of many prosumers, each equipped with a battery and a renewable energy-based generator. In particular, we assume that each prosumer is in possession of a solar power generator, i.e., photovoltaic cells. In the proposed market mechanism, each prosumer sets an asking price and bids for the amount of electricity that he/she sells or buys, In addition, he/she sets an asking price and bids for a parameter to cope with the uncertainty induced by solar power generation in a dayahead market, as well. It is a characteristic of regional electricity networks of prosumers that there is a strong correlation in the solar power generation of each house within a network. A market mechanism for a regional electricity network of prosumers with distributed solar power generation should consider such characteristics. The performance of the proposed mechanism is demonstrated numerically through a simulation experiment. It outperformed a conventional realtime pricing method that does not consider uncertainty, and a method that does not involve trading of the parameter for coping with uncertainty.

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“…The price p t satisfying Equation (29) balances supply and demand exactly and fulfills the constraint in Equation (27). It is known that the clearing price p t that satisfies Equation (29) uniquely exists.…”

Section: Overviewmentioning

confidence: 99%

“…A smart meter containing a software agent can trade electricity automatically through a regional electricity market. The smart meter also manages battery and shiftable devices [25][26][27] using smart grid technologies. The electricity network itself is connected to other outside electricity networks through a gateway.…”

Section: Prosumers' Decentralized Smart Gridmentioning

confidence: 99%

Convergent Double Auction Mechanism for a Prosumers’ Decentralized Smart Grid

et al. 2015

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Abstract:In this paper, we propose a novel automated double auction mechanism called convergent linear function submission-based double-auction (CLFS-DA) for a prosumers' decentralized smart grid. The target decentralized smart grid is a regional electricity network that consists of many prosumers that have a battery and a renewable energy-based generator, such as photovoltaic cells. In the proposed double-auction mechanism, each intelligent software agent representing each prosumer submits linear demand and supply functions to an automated regional electricity market where they are registered. It is proven that the CLFS-DA mechanism is guaranteed to obtain one of the global optimal price profiles in addition to it achieving an exact balance between demand and supply, even through the learning period. The proof of convergence is provided on the basis of the theory of LFS-DA, which gives a clear bridge between a function submission-based double auction and a dual decomposition (DD)-based real-time pricing procedure. The performance of the proposed mechanism is demonstrated numerically through a simulation experiment.

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A Dynamic Market Mechanism for Markets with Shiftable Demand Response

Cited by 22 publications

References 15 publications

Foundations of Infrastructure-CPS

Foundations of Infrastructure-CPS

Risk-Limiting Real-Time Pricing for a Regional Prosumers' Electricity Network with Distributed Solar Power Generation

Convergent Double Auction Mechanism for a Prosumers’ Decentralized Smart Grid

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A Dynamic Market Mechanism for Markets with Shiftable Demand Response

Cited by 22 publications

References 15 publications

Foundations of Infrastructure-CPS

Foundations of Infrastructure-CPS

Risk-Limiting Real-Time Pricing for a Regional Prosumers&apos; Electricity Network with Distributed Solar Power Generation

Convergent Double Auction Mechanism for a Prosumers’ Decentralized Smart Grid

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Product

Resources

About

Risk-Limiting Real-Time Pricing for a Regional Prosumers' Electricity Network with Distributed Solar Power Generation