Demand response scheduling under uncertainty: Chance‐constrained framework and application to an air separation unit

Kelley, Morgan T.; Baldick, Ross; Bâldea, Michael

doi:10.1002/aic.16273

Cited by 31 publications

(17 citation statements)

References 40 publications

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“…The proposed approach improves the performance of the day-ahead market considering the high uncertainty of DR programs. The uncertainties in industrial DR scheduling are analyzed using a chanceconstraint formulation in [157]. In this method, an optimal DR scheme is proposed using electricity price and product demand uncertainty.…”

Section: Uncertainty In Drmentioning

confidence: 99%

An Overview of Demand Response: From its Origins to the Smart Energy Community

Honarmand¹,

Hosseinnezhad

Hayes

et al. 2021

IEEE Access

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The need to increase network efficiency, enhance reliability, and reduce environmental effects, as well as advances in communication infrastructures, have led to demand response (DR) becoming an essential part of smart grid operation. DR can provide power system operators with a range of flexible resources through different schemes. From the operational decision-making viewpoint, in practice, each scheme can affect the system performance differently. Therefore, categorizing different DR schemes based on their potential impacts on the power grid, operational targets, and economic incentives can embed a pragmatic and practical perspective into the selection approach. In order to provide such insights, this paper presents an extensive review of DR programs. A goal-oriented classification based on the type of market, reliability, power flexibility and the participants' economic motivation is proposed for DR programs. The benefits and barriers based on new classes are presented. Every involved party, including the power system operator and participants, can utilize the proposed classification to select a proper plan in the DR-related ancillary service ecosystem. The various enabling technologies and practical strategies for the application of DR schemes in various sectors are reviewed. Following this, changes in the procedure of DR schemes in the smart community concept are studied. Finally, the direction of future research and development in DR is discussed and analyzed.

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Section: Uncertainty In Drmentioning

confidence: 99%

An Overview of Demand Response: From its Origins to the Smart Energy Community

Honarmand¹,

Hosseinnezhad

Hayes

et al. 2021

IEEE Access

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“…Des Weiteren betrachten Obermeier et al den Aspekt der Lebensdauer kritischer Anlagenkomponenten [6,18]. Ein aktuelles Beispiel für DSM bei fluktuierender Energieverfügbarkeit am Beispiel einer LZA findet sich in Kelley et al [19].…”

Section: Simulation Und Optimierung Des Flexiblen Betriebs Von Luftzeunclassified

“…Ein aktuelles Beispiel für DSM bei fluktuierender Energieverfügbarkeit am Beispiel einer LZA findet sich in Kelley et al. 19.…”

Section: Betrieb Und Simulation Von Luftzerlegungsanlagenunclassified

Flexibler Betrieb von Luftzerlegungsanlagen

Klein

Fritsch

Haider

et al. 2020

Chemie Ingenieur Technik

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This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. Vor dem Hintergrund der Energiewende wird die aktuelle Forschung zum energieoptimalen, lastflexiblen Betrieb von Luftzerlegungsanlagen beschrieben. Zum einen wird ein realitätsgetreuer, druckgetriebener Ansatz zur dynamischen Simulation vorgestellt. Auf dessen Basis wird ein detailliertes, transientes Simulationsmodell einer realen Luftzerlegungsanlage, ein digitaler Zwilling, erstellt. Exemplarisch werden Simulationen extremer Betriebsszenarien, wie das Anfahren oder Abschalten des Hauptwärmeübertragers, der Trennkolonnen und der gesamten Luftzerlegungsanlage, beschrieben. Zum anderen wird die Lebensdauer des Hauptwärmeübertragers aufgrund der hohen thermischen Wechselbelastung mithilfe eines Prüfstands untersucht. Die aufgenommenen Daten dienen zur Ableitung und Validierung dreidimensionaler Simulationsmodelle.

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“…Anyhow, as DSM demands for flexible operation, process dynamics are of high interest in this context. To account for nonlinear dynamic variables in scheduling, methods are proposed, e.g., based on chance‐constraints 66 or moving horizon scheduling 67. Process dynamics are incorporated using scale‐bridging models that link the scheduling and the control layer of the process.…”

Section: Classification Of Solutions To Enhance Flexibilitymentioning

confidence: 99%

Challenges and Opportunities to Enhance Flexibility in Design and Operation of Chemical Processes

Riese

Grünewald

2020

Chemie Ingenieur Technik

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This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. Flexibility receives increased interest in chemical engineering and is discussed as one measure to deal with upcoming challenges for the chemical industry. In this paper, different types of flexibility are presented, and flexibility needs are illustrated. The focus is on the evaluation and classification of available solutions to enhance flexibility. Solutions and future challenges across all length scales of chemical engineering are discussed: from tailored catalyst properties to decoupling of processes by means of storage.

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Demand response scheduling under uncertainty: Chance‐constrained framework and application to an air separation unit

Cited by 31 publications

References 40 publications

An Overview of Demand Response: From its Origins to the Smart Energy Community

An Overview of Demand Response: From its Origins to the Smart Energy Community

Flexibler Betrieb von Luftzerlegungsanlagen

Challenges and Opportunities to Enhance Flexibility in Design and Operation of Chemical Processes

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