Optimal Demand Response Scheduling With Real-Time Thermal Ratings of Overhead Lines for Improved Network Reliability

Kopsidas, Konstantinos; Kapetanaki, Alexandra; Leví, Víctor

doi:10.1109/tsg.2016.2542922

Cited by 69 publications

(39 citation statements)

References 27 publications

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“…The authors in [9] propose a distribution network investment model with DLR option to demonstrate the role of DLR in supporting distributed energy resources. Combined analysis of DLR and demand response in [10] identifies the synergy between these technologies. The authors in [11] apply a security constrained AC dispatch model to investigate the benefit of DLR in enhancing the system security.…”

Section: B Variables (Written Inmentioning

confidence: 99%

Understanding the Benefits of Dynamic Line Rating Under Multiple Sources of Uncertainty

Teng

Dupin

Michiorri

et al. 2018

IEEE Trans. Power Syst.

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Abstract--This paper analyses the benefits of dynamic line rating (DLR) in the system with high penetration of wind generation. A probabilistic forecasting model for the line ratings is incorporated into a two-stage stochastic optimization model. The scheduling model, for the first time, considers the uncertainty associated with wind generation, line ratings and line outages to co-optimize the energy production and reserve holding levels in the scheduling stage as well as the re-dispatch actions in the real-time operation stage. Therefore, the benefits of higher utilization of line capacity can be explicitly balanced against the costs of increased holding and utilization of reserve services due to the forecasting error. The computational burden driven by the modelling of multiple sources of uncertainty is tackled by applying an efficient filtering approach. The case studies demonstrate the benefits of DLR in supporting costeffective integration of high penetration of wind generation into the existing network. We also highlight the importance of simultaneously considering the multiple sources of uncertainty in understanding the benefits of DLR. Furthermore, this paper analyses the impact of different operational strategies, the coordination among multiple flexible technologies and installed capacity of wind generation on the benefits of DLR.

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Section: B Variables (Written Inmentioning

confidence: 99%

Understanding the Benefits of Dynamic Line Rating Under Multiple Sources of Uncertainty

Teng

Dupin

Michiorri

et al. 2018

IEEE Trans. Power Syst.

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“…Ignored the uncertainty of wind power. [89] Studied the impacts of DR scheduling on reliability and economic indices, particularly when emergency energy prices drive load recovery.…”

Section: Sourcementioning

confidence: 99%

Impacts of Demand-Side Management on Electrical Power Systems: A Review

et al. 2018

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Electricity demand has grown over the past few years and will continue to grow in the future. The increase in electricity demand is mainly due to industrialization and the shift from a conventional to a smart-grid paradigm. The number of microgrids, renewable energy sources, plug-in electric vehicles and energy storage systems have also risen in recent years. As a result, future electricity grids have to be revamped and adapt to increasing load levels. Thus, new complications associated with future electrical power systems and technologies must be considered. Demand-side management (DSM) programs offer promising solutions to these issues and can considerably improve the reliability and financial performances of electrical power systems. This paper presents a review of various initiatives, techniques, impacts and recent developments of the DSM of electrical power systems. The potential benefits derived by implementing DSM in electrical power networks are presented. An extensive literature survey on the impacts of DSM on the reliability of electrical power systems is also provided for the first time. The research gaps within the broad field of DSM are also identified to provide directions for future work.

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“…At present, for the modern power system with large scale and complex structure, the main purpose of scheduling is to ensure the safe operation of the system, ensure the reliability of the power supply of the user, and improve the economics of the system [9,10,11]. The fundamental problem is to solve the complex network.…”

Section: Artificial Intelligence Application Scenarios In Power Systemsmentioning

confidence: 99%

Application of Artificial Intelligence in the Field of Power Systems

Jizhi¹

2019

JEEE

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In recent years, the development of power systems has advanced by leaps and bounds. With the development of artificial intelligence, new directions have emerged. China has upgraded the development of artificial intelligence to a national strategy. A new proportion of new energy terminals is connected to the power grid. Modern power systems present complexity and uncertainty. Artificial intelligence technology will be an effective measure to solve complex system control and decision problems. Based on the application of artificial intelligence in the field of power system application. As a key link in the end-use of energy systems, the degree of intelligence of the power system will greatly affect the smooth implementation of the above technological innovations and advancements. At the same time, the pivotal link of the power system will cause the energy system to focus on the power system and Energy-related technologies are the basis for the integration and integration of the entire energy system. Therefore, it is essential to focus on the development of intelligent technologies in the power system. this paper expounds the application of artificial intelligence technology in power system scheduling, planning and power market.

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Optimal Demand Response Scheduling With Real-Time Thermal Ratings of Overhead Lines for Improved Network Reliability

Abstract: Monte-Carlo, real time thermal rating, risk. 22 NOMENCLATURE 23The symbols used throughout this paper are defined below.

Cited by 69 publications

References 27 publications

Understanding the Benefits of Dynamic Line Rating Under Multiple Sources of Uncertainty

Understanding the Benefits of Dynamic Line Rating Under Multiple Sources of Uncertainty

Impacts of Demand-Side Management on Electrical Power Systems: A Review

Application of Artificial Intelligence in the Field of Power Systems

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