Multi-Objective Demand Side Management at Distribution Network Level in Support of Transmission Network Operation

Ponoćko, Jelena; Milanović, Jovica V.

doi:10.1109/tpwrs.2019.2944747

Cited by 31 publications

(7 citation statements)

References 41 publications

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“…System Composition. In order to realize the real-time evaluation of cotton growth status, the leaf area index (LAI) of surface plant N content and dry matter accumulation of surface plant were used as standards to establish the cotton growth status model based on IMS multiarea technology [12].…”

Section: Methodsmentioning

confidence: 99%

Monitoring and Analysis of Cotton Planting Parameters in Multiareas Based on Multisensor

Fan

Zhang

Wang

et al. 2022

Mathematical Problems in Engineering

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In order to realize cotton growth monitoring, a cotton planting monitoring system based on image processing technology was proposed. The system requires camera to collect cotton canopy images, leaf areometer to detect the leaf area index, and spectrometer to detect the normalized vegetation index ( NDVI ) and the vegetation index ( RVI ). Due to different types of data, based on the establishment of the output transmission system, the canopy coverage was calculated by the image processing method, and there was a linear relationship between canopy coverage NDVI and RVI . The leaf area index (LAI) of N content was established, and the model of dry matter accumulation and canopy coverage was exponential. The experiment result shows that the linear and exponential coefficients of the model k and b increased with the increase of the nitrogen application rate. The fitting determination coefficient remained high under different nitrogen application rates. The fitting coefficient R2 of the three models in the two test fields ranged from 0.83 to 0.923, which also met the needs of model evaluation. The system was used to detect the cotton field with good accuracy.

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Section: Methodsmentioning

confidence: 99%

Monitoring and Analysis of Cotton Planting Parameters in Multiareas Based on Multisensor

Fan

Zhang

Wang

et al. 2022

Mathematical Problems in Engineering

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“…As more advanced solutions, demand side management is proposed to support accommodation of more RES in distribution networks [18], [19], [20]. Different Demand Response (DR) methods are in place to provide flexibility.…”

Section: Introductionmentioning

confidence: 99%

Real-Time Control of Power Exchange at Primary Substations: An OPF-Based Solution

Estebsari

Patti

Bottaccioli

2020

2020 IEEE International Conference on Environment and Electrical Engineering and 2020 IEEE Industrial and Commercial Power Syst

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Nowadays, integration of more renewable energy resources into distribution systems to inject more clean energy introduces new challenges to power system planning and operation. The intermittent behaviour of variable renewbale resources such as wind and PV generation would make the energy balancing more difficult, as current forecasting tools and existing storage units are insufficient. Transmission system operators may withstand some level of power imbalance, but fluctuations and noise of profiles are undesired. This requires local management performed or encouraged by distribution system operators. They could try to involve aggregators to exploit flexibility of loads through demand response schemes. In this paper, we present an optimal power flow-based algorithm written in Python which reads flexibility of different loads offered by the aggregators from one side, and the power flow deviation with respect to the scheduled profile at transmission-distribution coupling point from the other side, to define where and how much load to adjust. To demonstrate the applicability of this core, we setup a realtime simulation-based test bed and realised the performance of this approach in a real-like environment using real data of a network.

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“…However, these methods fail to meet the requirement at point of common coupling (PCC) when more than one network is integrated. Recently, there has been extensive research on transmission network support by DNs, either maintaining the voltage at PCC or reactive power exchange between transmission and distribution network within a specified range 21 , 22 . Future studies should focus on a centralized real-time short-term voltage control strategy for DNs.…”

Section: Energy Storage Technologies In Smart Distribution Networkmentioning

confidence: 99%

Operational planning steps in smart electric power delivery system

Jayachandran

Reddy

Padmanaban³

et al. 2021

Sci Rep

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This paper presents a comprehensive review of advanced technologies with various control approaches in terms of their respective merits and outcomes for power grids. Distributed energy storage control is classified into automatic voltage regulator and load frequency control according to corresponding functionalities. These control strategies maintain a power balance between generation and demand. Besides, three basic electric vehicle charging technologies can be distinguished, i.e. stationary, quasi-dynamic and dynamic control. For realizing charge-sustaining operation at minimum cost quasi-dynamic and dynamic strategies are adopted for in-route charging, while stationary control can only be utilized when the electric vehicle is in stationary mode. Moreover, power system frequency stability and stabilization techniques in non-synchronous generator systems are reviewed in the paper. Specifically, a synchronverter can damp power system oscillations and ensure stability by providing virtual inertia. Furthermore, it is crucial to manage the massive information and ensure its security in the smart grid. Therefore, several attack detection and mitigation schemes against cyber-attacks are further presented to achieve reliable, resilient, and stable operation of the cyber-physical power system. Thus, bidirectional electrical power flows with two-way digital control and communication capabilities have poised the energy producers and utilities to restructure the conventional power system into a robust smart distribution grid. These new functionalities and applications provide a pathway for clean energy technology. Finally, future research trends on smart grids such as IoT-based communication infrastructure, distributed demand-response with artificial intelligence and machine learning solutions, and synchrophasor-based wide-area monitoring protection and control (WAMPC) are examined in the present study.

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Multi-Objective Demand Side Management at Distribution Network Level in Support of Transmission Network Operation

Cited by 31 publications

References 41 publications

Monitoring and Analysis of Cotton Planting Parameters in Multiareas Based on Multisensor

Monitoring and Analysis of Cotton Planting Parameters in Multiareas Based on Multisensor

Real-Time Control of Power Exchange at Primary Substations: An OPF-Based Solution

Operational planning steps in smart electric power delivery system

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