A per-node granularity decentralized optimal power flow for radial distribution networks with PV and EV integration

Tang, Chong; Liu, Mingbo; Liu, Qingkai; Dong, Ping

doi:10.1016/j.ijepes.2019.105513

Cited by 13 publications

(13 citation statements)

References 33 publications

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“…As the use of solar energy grows, distribution system operators (DSOs) are increasingly likely to pay attention to the impact of PV intermittency on optimum power flow (OPF) and voltage control. One efficient strategy to address such PV integration difficulties is to fully use DR capabilities [88]. In addition, technological advancements have enabled systems to incorporate a variety of inverter control strategies.…”

Section: Blockchain-supported Demand Response In Smart Gridsmentioning

confidence: 99%

Overview of Demand-Response Services: A Review

2022

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It is essential for the electricity sector to analyze and determine the distribution capacity throughput and apply new methods aimed at increasing the capacity of the transmission system. Consequently, the transition to modern electricity networks is two-sided, i.e., involving technological and social modifications. The demand response (DR) redistributes consumption away from peak times when grid load and costs are the highest. It incentivizes customers to use electricity when supply is high and inexpensive due to various market mechanisms. The present DR policy proposals stress the importance of fostering behavioral change through competitive pricing and customer participation in reducing carbon emissions and implementing smart energy solutions (including monitoring tools, such as smart meters and applications). The internet of things (IoT) has been applied to ensure adaptive monitoring of energy consumption and cost-effective and adequate demand-side management (DSM). The article is based on the research of the most recent sources of DR implementation methods applied at the power distribution level. It explains the main concepts, classifications, and entities implementing DSM programs, and suggests new visions and prospects for DSM and DR. Moreover, it discusses the application of blockchain technology potential for the internet of energy.

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Section: Blockchain-supported Demand Response In Smart Gridsmentioning

confidence: 99%

Overview of Demand-Response Services: A Review

2022

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“…This section demonstrates the P‐OPF simulations and validation performed by the proposed methods discussed in the literature [34–69]. The P‐OPF problem in electric power systems considers the integration of RE sources such as WT and PV.…”

Section: Discussionmentioning

confidence: 99%

“…Furthermore, a new frequency and duration analysis technique was used for the P‐OPF solution, showing that the proposed method is highly accurate and robust [47]. To verify the accuracy of the proposed algorithm in [48], various comparisons of voltage magnitudes and angles were presented. The authors in reference [49] claimed that the proposed method is robust, accurate, and can effectively tackle any correlation between stochastic input variables.…”

Section: Discussionmentioning

confidence: 99%

Advanced studies for probabilistic optimal power flow in active distribution networks: A scientometric review

Ullah

Wang

et al. 2022

IET Generation Trans & Dist

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In the active distribution networks (ADNs), the emerging trend of high penetration of sustainable energy sources such as wind turbines, photovoltaics, and the forthcoming integration of energy storage devices and additional dynamic loads like plug-in-electric vehicles (PEVs) influences to change the nature of electric distribution networks. Consequently, it deteriorates power quality and reliability in terms of unacceptable voltage rise-drop, harmonic distortion, voltage unbalance, and excessive power loss. In this context of transition into the active distribution network, the probabilistic optimal power flow (P-OPF) in the ADN is considered an important tool that helps the distribution grid operators for defining the optimal settings of the system's control variables. However, the optimal solution of P-OPF becomes highly complex while considering the multiple variables, timevarying characteristics and operational uncertainties associated with sustainable resources, consumer behaviour and electricity market prices. This review aims at promoting the research and discussion of P-OPF studies in the context of ADNs characteristics and challenges. First, we perform a data-driven and visualized scientometric analysis of 1988 quality documents retrieved from the Scopus during the last ten years using VOSviewer software. Second, an in-depth investigation of the recent and emerging techniques for solving the P-OPF problem is presented. Third, a set of recommendations and highlights of future challenges for P-OPF in ADNs are offered. The review findings showed high interest among the scientific community in sustainable energy source integration, given the recent rise in publications and citations. Also, there is still a lack of innovative optimization techniques that can adequately handle the current issues associated with P-OPF and objectives with fair computational efficiency and accuracy. Finally, this paper offers a guide for P-OPF researchers to navigate the recent studies considering the sustainable sources, spot the new research frontiers, and identify the most impactful countries and publishers.

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“…DP in [54] allows for the optimum charge schedule for EVs to be identified so that all supply and demand-based rates of energy and costs can be reduced taking account of the multiple driving habits of each driver. Quadratic programming (QP) is used in [37] to solve the problem of optimal power flow in a fully decentralized distribution network with massive penetration of PV and EV. Optimization model under QP is used in [56] to decrease the total grid power for the utilities and performs the EV user's smart charging/discharging management.…”

Section: Optimization Algorithmsmentioning

confidence: 99%

Smart charging impact on electric vehicles in presence of photovoltaics

Hajar

Guo

Hably

et al. 2021

2021 22nd IEEE International Conference on Industrial Technology (ICIT)

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The emergence of electric vehicles (EVs) promises to be the turning point of sustainable energy and, in particular, renewable energy production in the world. EV Charging will generate substantial extra demand for electricity. Renewable energy, including solar and wind power, can be met in the grid technically and economically. Recent studies have shown that smart charging of EV can increase the synergy between photovoltaics (PV), electrical transmission and electricity usage, resulting in technological and economic advantages. Given the increasing emphasis on this area, this analysis summarizes an overview on smart charging studies taking into account PV power output and consumption of electricity.

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A per-node granularity decentralized optimal power flow for radial distribution networks with PV and EV integration

Cited by 13 publications

References 33 publications

Overview of Demand-Response Services: A Review

Overview of Demand-Response Services: A Review

Advanced studies for probabilistic optimal power flow in active distribution networks: A scientometric review

Smart charging impact on electric vehicles in presence of photovoltaics

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