Hierarchical Predictive Load Control in Smart Grids

Brandstetter, Markus; Schirrer, Alexander; Miletić, Maja; Henein, Sawsan; Kozek, Martin; Kupzog, Friederich

doi:10.1109/tsg.2015.2477105

Cited by 26 publications

(15 citation statements)

References 29 publications

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“…In [17], a hierarchical iterative control algorithm is proposed to optimally balance grid load while meeting consumers power demand. This hierarchical architecture is based on the assumption that a certain proportion of the consumers can predict their consumption profile and adapt their control strategies to fulfill power consumption constraints.…”

Section: Related Workmentioning

confidence: 99%

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A New Triple Bargaining Game-Based Energy Management Scheme for Hierarchical Smart Grids

Kim

2019

IEEE Access

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This paper deals with the hierarchical structure of smart-grid systems. The major challenges of this structure are to balance electric power production and consumption within the hierarchical smart grid, and makes active use of the flexibility of a large number of power producing and consuming units. In this study, we present a new triple game based energy management scheme for the hierarchical smart-grid architecture. By using the Nash with claim, midpoint-constrained egalitarian and proportional bargaining solutions, the proposed approach can adaptively distribute the limited energy resource of smart-grid system. To reduce the computation complexity, these bargaining solutions are hierarchically applied based on the developed triple game model. According to the attractive characteristics of each bargaining solution, control decisions in our proposed scheme are mutually dependent on each other and can cause cascade interactions to reach a desirable system performance. The results obtained from the simulation analysis illustrate the effectiveness of the proposed scheme compared with the existing state-of-the-art protocols. Finally, we conclude advantages of our triple game based energy management scheme and identify research areas for future study.

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Section: Related Workmentioning

confidence: 99%

“…It is assumed that a simplified model of the power grid and a prediction based on historical data for the consumption profile of passive consumers are available. The proposed control algorithm has low-communication requirements and effectively deals with the case of noncompliant consumers [17].…”

Section: Related Workmentioning

confidence: 99%

A New Triple Bargaining Game-Based Energy Management Scheme for Hierarchical Smart Grids

Kim

2019

IEEE Access

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“…Another increasingly important application of MPC in smart grids is load curtailment, which enables safe operation of the grid during periods of high loads. The method reported in [77] relies on the existence of MPC controlled buildings in the grid. Overall, there is no other single control strategy for buildings in smart grids which features the same suitability and versatility as MPC.…”

Section: Which Building Control Strategy Is Best Suited For Integratimentioning

confidence: 99%

Ten questions concerning model predictive control for energy efficient buildings

Killian

Kozek

2016

Building and Environment

286

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“…Zhang et al 2016) or provided by a central controller (e.g. Brandstetter et al 2017). Other methods such as modeling adjusted residual load profiles and assessing the resulting changes in load flows can also be found (cf.…”

Section: Approaches To Dsm Of Space Heating Appliancesmentioning

confidence: 99%

Modeling the Value of Flexible Heat Pumps

Felten

2017

SSRN Journal

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Demand side management has been proposed as one means to improve integration of high shares of nondispatchable renewables-based electricity generation. Among other technologies, residential heat pumps are seen as suitable application for demand side management. Thus, we present a model of an air-water heat pump combined with a thermal energy storage. This heating system supplies heat to a floor-heated building. All subsystem dynamics (thermal energy storage, heating zone, water circuit of the floor heating, heated floor) are modeled in detail. That is dynamics are described by differential equations which are based on thermodynamic first principles. In terms of heat pump operation, we derive several model-predictive control strategies following different objectives. These strategies aim at the minimzation of electricity consumption, procurement prices or operational costs. The difference in operational costs of the flexible operation and of the non-optimized operation represents the value of this flexibility option. The model is designed to assess manifold technical setups and economic conditions and, thereby, lays the foundation for further detailed analyses.

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Hierarchical Predictive Load Control in Smart Grids

Cited by 26 publications

References 29 publications

A New Triple Bargaining Game-Based Energy Management Scheme for Hierarchical Smart Grids

A New Triple Bargaining Game-Based Energy Management Scheme for Hierarchical Smart Grids

Ten questions concerning model predictive control for energy efficient buildings

Modeling the Value of Flexible Heat Pumps

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