The DOI matches its Crossref record; 12 of the 13 references it cites were found in a registry or an index.
Inverter VAR control for distribution systems with renewables
Open accessAbstract
Motivated by the need to cope with rapid and random fluctuations of renewable generation, we presents a model that augments the traditional Volt/VAR control through switched controllers on a slow timescale with inverter control on a fast timescale. The optimization problem is generally nonconvex and therefore hard to solve. We propose a simple convex relaxation and prove that it is exact provided over-satisfaction of load is allowed. Hence Volt/VAR control over radial networks is efficiently solvable. Simulations of a real-world distribution circuit illustrates that the proposed inverter control achieves significant improvement over the IEEE 1547 standard in terms of power quality and power savings.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“these conditions require some bus to be able to draw infinite power, which is referred to as load over-satisfaction in the literature. For example, the conditions given in [9], [13], [14] require load over-satisfaction on some/all of the buses.”
From Optimal power flow in distribution networks (2018) · cites this paper as [9]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“To summarize, all sufficient conditions in the literature that guarantee the exactness of the SOCP relaxation require removing some of the constraints in OPF, and do not hold in practice.”
From Optimal power flow in distribution networks (2018) · cites this paper as [9]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“Proposition 1 ( [9]) The SOCP relaxation is exact if p i = -∞ and q i = -∞ for i ∈ N + .”
From Optimal power flow in distribution networks (2018) · cites this paper as [9]
Experimental — accuracy not yet measured
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Ipakchi, A., & Albuyeh, F. (2009) · IEEE Power and Energy Magazine · doi:10.1109/mpe.2008.931384 · Cited by 1,644
Optimal sizing of capacitors placed on a radial distribution system
Baran, M. E., & Wu, F. F. (1989) · IEEE Transactions on Power Delivery · doi:10.1109/61.19266 · Cited by 1,536
Turitsyn, K. S., Šulc, P., Backhaus, S., & Chertkov, M. (2010) · IEEE Power Engineering Society General Meeting · doi:10.1109/pes.2010.5589663 · Cited by 233
Grainger, J. J., & Civanlar, S. (1985) · IEEE Transactions on Power Apparatus and Systems · doi:10.1109/tpas.1985.318842 · Cited by 231
Civanlar, S., & Grainger, J. J. (1985) · IEEE Transactions on Power Apparatus and Systems · doi:10.1109/tpas.1985.318844 · Cited by 209
Evaluation of Conservation Voltage Reduction (CVR) on a National Level
Schneider, K. P., Fuller, J., Tuffner, F., & Singh, R. (2010) · doi:10.2172/990131 · Cited by 208
Local Control of Reactive Power by Distributed Photovoltaic Generators
Turitsyn, K., Sulc, P., Backhaus, S., & Chertkov, M. (2010) · 2010 First IEEE International Conference on Smart Grid Communications · doi:10.1109/smartgrid.2010.5622021 · Cited by 200
Distribution System Voltage Performance Analysis for High-Penetration Photovoltaics
Liu, E., & Bebic, J. Z. (2008) · doi:10.2172/924648 · Cited by 162
Impact of distributed generation on volt/var control in distribution networks
Niknam, T., Ranjbar, A. M., & Shinari, A. R. (2004) · doi:10.1109/ptc.2003.1304390 · Cited by 145
Optimal power flow over tree networks
Bose, S., Gayme, D. F., Low, S. H., & Chandy, K. M. (2011) · Allerton Conference on Communication, Control, and Computing · doi:10.1109/allerton.2011.6120323 · Cited by 91
Self-citation
Research works printed but not linked: 2
- grant, 0, "CVX Matlab Software for Disciplined Convex Programming " [Online]
- sojoudi, 2011, Network Topologies Guaranteeing Zero Duality Gap for Optimal Power Flow Problem
Cited by
Sorted by citations
Branch Flow Model: Relaxations and Convexification—Part I
Farivar, M., & Low, S. H. (2013) · IEEE Transactions on Power Systems · doi:10.1109/tpwrs.2013.2255317 · Cited by 1,541
Self-citationA Survey of Distributed Optimization and Control Algorithms for Electric Power Systems
Molzahn, D. K., Dörfler, F., Sandberg, H., Low, S. H., Chakrabarti, S., Baldick, R., & Lavaei, J. (2017) · IEEE Transactions on Smart Grid · doi:10.1109/tsg.2017.2720471 · Cited by 1,278
Self-citationConvex Relaxation of Optimal Power Flow—Part I: Formulations and Equivalence
Low, S. H. (2014) · IEEE Transactions on Control of Network Systems · doi:10.1109/tcns.2014.2309732 · Cited by 934
Self-citationConvex Relaxation of Optimal Power Flow -- Part I: Formulations and EquivalencePreprint
Low, S. H. (2014) · Cited by 593
Self-citationConvex Relaxation of Optimal Power Flow—Part II: Exactness
Low, S. H. (2014) · IEEE Transactions on Control of Network Systems · doi:10.1109/tcns.2014.2323634 · Cited by 605
Self-citationExact Convex Relaxation of Optimal Power Flow in Radial Networks
Gan, L., Li, N., Topcu, U., & Low, S. H. (2014) · IEEE Transactions on Automatic Control · doi:10.1109/tac.2014.2332712 · Cited by 516
Self-citationAdaptive VAR Control for Distribution Circuits With Photovoltaic Generators
Yeh, H., Gayme, D. F., & Low, S. H. (2012) · IEEE Transactions on Power Systems · doi:10.1109/tpwrs.2012.2183151 · Cited by 460
Self-citationDistribution Locational Marginal Pricing (DLMP) for Congestion Management and Voltage Support
Bai, L., Wang, J., Wang, C., Chen, C., & Li, F. F. (2017) · IEEE Transactions on Power Systems · doi:10.1109/tpwrs.2017.2767632 · Cited by 448
Convex Models of Distribution System Reconfiguration
Taylor, J. A., & Hover, F. S. (2012) · IEEE Transactions on Power Systems · doi:10.1109/tpwrs.2012.2184307 · Cited by 460
Nick, M., Cherkaoui, R., & Paolone, M. (2014) · IEEE Transactions on Power Systems · doi:10.1109/tpwrs.2014.2302020 · Cited by 435
Mahmud, N., & Zahedi, A. (2016) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2016.06.030 · Cited by 382
Optimal inverter VAR control in distribution systems with high PV penetration
Farivar, M., Neal, R., Clarke, C., & Low, S. H. (2012) · IEEE Power Engineering Society General Meeting · doi:10.1109/pesgm.2012.6345736 · Cited by 358
Self-citationThe QC Relaxation: A Theoretical and Computational Study on Optimal Power Flow
Coffrin, C., Hijazi, H., & Hentenryck, P. V. (2015) · IEEE Transactions on Power Systems · doi:10.1109/tpwrs.2015.2463111 · Cited by 342
Convex Relaxation of Optimal Power Flow Part II: Exactness
Low, S. H. (2014) · Cited by 319
Self-citation1Exact Convex Relaxation of Optimal Power Flow in Radial NetworksPreprint
Gan, L., Li, N., Topcu, U., & Low, S. H. (2016) · Cited by 301
Self-citationTwo-Timescale Voltage Control in Distribution Grids Using Deep Reinforcement Learning
Yang, Q., Wang, G., Sadeghi, A., Giannakis, G. B., & Sun, J. Q. (2019) · IEEE Transactions on Smart Grid · doi:10.1109/tsg.2019.2951769 · Cited by 295
Review on Implementation and Assessment of Conservation Voltage Reduction
Wang, Z., & Wang, J. (2014) · IEEE Transactions on Power Systems · doi:10.1109/tpwrs.2013.2288518 · Cited by 289
PowerModels. JL: An Open-Source Framework for Exploring Power Flow Formulations
Coffrin, C., Bent, R. W., Sundar, K., Ng, Y., & Lubin, M. (2018) · Power Systems Computation Conference · doi:10.23919/pscc.2018.8442948 · Cited by 286
Equilibrium and dynamics of local voltage control in distribution systems
Farivar, M., Chen, L., & Low, S. H. (2013) · IEEE Conference on Decision and Control (CDC) · doi:10.1109/cdc.2013.6760555 · Cited by 279
Self-citationMulti-Time Step Service Restoration for Advanced Distribution Systems and Microgrids
Chen, B., Chen, C., Wang, J., & Butler-Purry, K. L. (2017) · IEEE Transactions on Smart Grid · doi:10.1109/tsg.2017.2723798 · Cited by 260
Lei, S., Chen, C., Song, Y., & Hou, Y. (2020) · IEEE Transactions on Smart Grid · doi:10.1109/tsg.2020.2985087 · Cited by 247
Business models for distributed energy resources: A review and empirical analysis
Burger, S. P., & Luke, M. (2017) · Energy Policy · doi:10.1016/j.enpol.2017.07.007 · Cited by 228
The Power Grid Library for Benchmarking AC Optimal Power Flow AlgorithmsPreprint
Babaeinejadsarookolaee, S., Birchfield, A. B., Christie, R. D., Coffrin, C., DeMarco, C. L., Diao, R., Ferris, M. C., Fliscounakis, S., Greene, S., Huang, R., et al. (2019) · arXiv (Cornell University) · doi:10.48550/arxiv.1908.02788 · Cited by 220
Decentralized Energy Management for Networked Microgrids in Future Distribution Systems
Gao, H., Liu, J., Wang, L., & Wei, Z. (2017) · IEEE Transactions on Power Systems · doi:10.1109/tpwrs.2017.2773070 · Cited by 212
Mlilo, N., Brown, J. L., & Ahfock, T. (2021) · Technology and Economics of Smart Grids and Sustainable Energy · doi:10.1007/s40866-021-00123-w · Cited by 211
Distributed Optimal Power Flow Algorithm for Radial Networks, I: Balanced Single Phase Case
Peng, Q., & Low, S. H. (2016) · IEEE Transactions on Smart Grid · doi:10.1109/tsg.2016.2546305 · Cited by 208
Self-citationOpportunities and challenges for data center demand response
Wierman, A., Liu, Z., Liu, I., & Mohsenian‐Rad, H. (2014) · International Green and Sustainable Computing Conference · doi:10.1109/igcc.2014.7039172 · Cited by 202
Convex quadratic relaxations for mixed-integer nonlinear programs in power systems
Hijazi, H., Coffrin, C., & Hentenryck, P. V. (2016) · Mathematical Programming Computation · doi:10.1007/s12532-016-0112-z · Cited by 199
Robust Coordinated Optimization of Active and Reactive Power in Active Distribution Systems
Gao, H., Liu, J., & Wang, L. (2017) · IEEE Transactions on Smart Grid · doi:10.1109/tsg.2017.2657782 · Cited by 197
AC-feasibility on tree networks is NP-hard
Lehmann, K., Grastien, A., & Van Hentenryck, P. (2016) · IEEE Transactions on Power Systems · doi:10.1109/tpwrs.2015.2407363 · Cited by 221
Caramanis, M. C., Ntakou, E., Hogan, W. W., Chakrabortty, A., & Schoene, J. (2016) · Proceedings of the IEEE · doi:10.1109/jproc.2016.2520758 · Cited by 188
Second-Order Cone Programming for Optimal Power Flow in VSC-Type AC-DC Grids
Baradar, M., Hesamzadeh, M. R., & Ghandhari, M. (2013) · IEEE Transactions on Power Systems · doi:10.1109/tpwrs.2013.2271871 · Cited by 183
Geometry of Power Flows and Optimization in Distribution Networks
Lavaei, J., Tse, D. N. C., & Zhang, B. (2013) · IEEE Transactions on Power Systems · doi:10.1109/tpwrs.2013.2282086 · Cited by 180
Physics of power networks makes hard optimization problems easy to solve
Sojoudi, S., & Lavaei, J. (2012) · IEEE Power Engineering Society General Meeting · doi:10.1109/pesgm.2012.6345272 · Cited by 164
Safayet, A., Fajri, P., & Husain, I. (2017) · IEEE Transactions on Industry Applications · doi:10.1109/tia.2017.2741925 · Cited by 164
Pricing data center demand response
Liu, Z., Liu, I., Low, S. H., & Wierman, A. (2014) · ACM SIGMETRICS International Conference on Measurement and Modeling of Computer Systems (SIGMETRICS) · doi:10.1145/2591971.2592004 · Cited by 162
Self-citationLiu, H., & Wu, W. (2020) · IEEE Transactions on Smart Grid · doi:10.1109/tsg.2020.3041620 · Cited by 171
Exact convex relaxation of OPF for radial networks using branch flow model
Li, N., Chen, L., & Low, S. H. (2012) · IEEE International Conference on Smart Grid Communications (SmartGridComm) · doi:10.1109/smartgridcomm.2012.6485951 · Cited by 154
Self-citationEquivalent Relaxations of Optimal Power Flow
Bose, S., Low, S. H., Teeraratkul, T., & Hassibi, B. (2014) · IEEE Transactions on Automatic Control · doi:10.1109/tac.2014.2357112 · Cited by 152
Self-citationOptimal Power Flow in Direct Current Networks
Gan, L., & Low, S. H. (2014) · IEEE Transactions on Power Systems · doi:10.1109/tpwrs.2014.2313514 · Cited by 146
Self-citationAn Online Gradient Algorithm for Optimal Power Flow on Radial Networks
Gan, L., & Low, S. H. (2016) · IEEE Journal on Selected Areas in Communications · doi:10.1109/jsac.2016.2525598 · Cited by 142
Self-citationQuadratically Constrained Quadratic Programs on Acyclic Graphs With Application to Power Flow
Bose, S., Gayme, D. F., Chandy, K. M., & Low, S. H. (2015) · IEEE Transactions on Control of Network Systems · doi:10.1109/tcns.2015.2401172 · Cited by 126
Self-citationDistribution System Reconfiguration Under Uncertain Load and Renewable Generation
Haghighat, H., & Zeng, B. (2015) · IEEE Transactions on Power Systems · doi:10.1109/tpwrs.2015.2481508 · Cited by 129
Linear Decision Rules for Control of Reactive Power by Distributed Photovoltaic Generators
Jabr, R. A. (2017) · IEEE Transactions on Power Systems · doi:10.1109/tpwrs.2017.2734694 · Cited by 127
NESTA, The NICTA Energy System Test Case ArchivePreprint
Coffrin, C., Gordon, D., & Scott, P. (2014) · arXiv (Cornell University) · doi:10.48550/arxiv.1411.0359 · Cited by 127
Toward Distributed Energy Services: Decentralizing Optimal Power Flow With Machine Learning
Dobbe, R., Sondermeijer, O., Fridovich-Keil, D., Arnold, D., Callaway, D., & Tomlin, C. (2020) · IEEE Transactions on Smart Grid · doi:10.1109/tsg.2019.2935711 · Cited by 120
Inverter-Less Hybrid Voltage/Var Control for Distribution Circuits With Photovoltaic Generators
Wang, Z., Chen, H., Wang, J., & Begovic, M. M. (2014) · IEEE Transactions on Smart Grid · doi:10.1109/tsg.2014.2324569 · Cited by 121
Active distribution network expansion planning integrating dispersed energy storage systems
Xing, H., Cheng, H., Zhang, Y., & Zeng, P. (2015) · IET Generation Transmission & Distribution · doi:10.1049/iet-gtd.2015.0411 · Cited by 120
Robust Volt/VAr Control With Photovoltaics
Jabr, R. A. (2019) · IEEE Transactions on Power Systems · doi:10.1109/tpwrs.2018.2890767 · Cited by 118
Nick, M., Cherkaoui, R., Boudec, J. L., & Paolone, M. (2017) · IEEE Transactions on Automatic Control · doi:10.1109/tac.2017.2722100 · Cited by 114
Coffrin, C., Hijazi, H., & Hentenryck, P. V. (2016) · IEEE Transactions on Power Systems · doi:10.1109/tpwrs.2016.2634586 · Cited by 103
Feeder Reconfiguration in Distribution Networks Based on Convex Relaxation of OPF
Peng, Q., Tang, Y., & Low, S. H. (2014) · IEEE Transactions on Power Systems · doi:10.1109/tpwrs.2014.2356513 · Cited by 103
Self-citationAC OPF for Smart Distribution Networks: An Efficient and Robust Quadratic Approach
Franco, J. F., Ochoa, L. F., & Romero, R. A. (2017) · IEEE Transactions on Smart Grid · doi:10.1109/tsg.2017.2665559 · Cited by 100
Pricing data center demand response
Liu, Z., Liu, I., Low, S. H., & Wierman, A. (2014) · ACM SIGMETRICS Performance Evaluation Review · doi:10.1145/2637364.2592004 · Cited by 98
Self-citationA survey on conic relaxations of optimal power flow problem
Zohrizadeh, F., Josz, C., Jin, M., Madani, R., Lavaei, J., & Sojoudi, S. (2020) · European Journal of Operational Research · doi:10.1016/j.ejor.2020.01.034 · Cited by 97
Distributed algorithm for optimal power flow on a radial network
Peng, Q., & Low, S. H. (2014) · IEEE Conference on Decision and Control (CDC) · doi:10.1109/cdc.2014.7039376 · Cited by 96
Self-citationOptimal power flow over tree networks
Bose, S., Gayme, D. F., Low, S. H., & Chandy, K. M. (2011) · Allerton Conference on Communication, Control, and Computing · doi:10.1109/allerton.2011.6120323 · Cited by 91
Self-citationBranch flow model: Relaxations and convexification
Farivar, M., & Low, S. H. (2012) · IEEE Conference on Decision and Control (CDC) · doi:10.1109/cdc.2012.6425870 · Cited by 89
Self-citationReverse and Forward Engineering of Local Voltage Control in Distribution Networks
Zhou, X., Farivar, M., Liu, Z., Chen, L., & Low, S. H. (2020) · IEEE Transactions on Automatic Control · doi:10.1109/tac.2020.2994184 · Cited by 86
Self-citationModel-Free Optimal Control of VAR Resources in Distribution Systems: An Extremum Seeking Approach
Arnold, D., Negrete-Pincetic, M., Sankur, M., Auslander, D. M., & Callaway, D. S. (2015) · IEEE Transactions on Power Systems · doi:10.1109/tpwrs.2015.2502554 · Cited by 85
Arnold, D., Sankur, M., Dobbe, R., Brady, K., Callaway, D. S., & von Meier, A. (2016) · IEEE Power Engineering Society General Meeting · doi:10.1109/pesgm.2016.7741261 · Cited by 79
Sarantakos, I., Peker, M., Zografou-Barredo, N.-M., Deakin, M., Patsios, C., Sayfutdinov, T., Taylor, P., & Greenwood, D. (2022) · IEEE Transactions on Smart Grid · doi:10.1109/tsg.2022.3145709 · Cited by 78
Minimum loss operation of distribution networks with photovoltaic generation
Jabr, R. (2014) · IET Renewable Power Generation · doi:10.1049/iet-rpg.2012.0213 · Cited by 75
On the exactness of convex relaxation for optimal power flow in tree networks
Gan, L., Li, N., Topcu, U., & Low, S. H. (2012) · IEEE Conference on Decision and Control (CDC) · doi:10.1109/cdc.2012.6426045 · Cited by 76
Self-citationConic AC transmission system planning
Taylor, J. A., & Hover, F. S. (2012) · IEEE Transactions on Power Systems · doi:10.1109/tpwrs.2012.2214490 · Cited by 72
Voltage regulation in distribution grids: A survey
Srivastava, P., Haider, R., Nair, V. J., Venkataramanan, V., Annaswamy, A. M., & Srivastava, A. K. (2023) · Annual Reviews in Control · doi:10.1016/j.arcontrol.2023.03.008 · Cited by 71
Local voltage control in distribution systems: An incremental control algorithm
Farivar, M., Zho, X., & Chen, L. (2015) · IEEE International Conference on Smart Grid Communications (SmartGridComm) · doi:10.1109/smartgridcomm.2015.7436388 · Cited by 70
Self-citationBobo, L., Venzke, A., & Chatzivasileiadis, S. (2020) · International Journal of Electrical Power & Energy Systems · doi:10.1016/j.ijepes.2020.106625 · Cited by 69
Christakou, K., Tomozei, D.-C., Boudec, J. L., & Paolone, M. (2016) · Electric Power Systems Research · doi:10.1016/j.epsr.2016.07.030 · Cited by 69
Kabir, F., Yu, N., Gao, Y., & Wang, W. (2023) · Applied Energy · doi:10.1016/j.apenergy.2022.120629 · Cited by 73
Strengthening Convex Relaxations with Bound Tightening for Power Network Optimization
Coffrin, C., Hijazi, H., & Hentenryck, P. V. (2015) · Lecture notes in computer science · doi:10.1007/978-3-319-23219-5_4 · Cited by 66
Optimal Placement of Energy Storage in Distribution Networks
Tang, Y., & Low, S. H. (2017) · IEEE Transactions on Smart Grid · doi:10.1109/tsg.2017.2711921 · Cited by 63
Self-citationAlzahrani, A. M., Zohdy, M. A., & Yan, B. Y. (2020) · Electric Power Systems Research · doi:10.1016/j.epsr.2020.106877 · Cited by 65
Graph Multi-Agent Reinforcement Learning for Inverter-Based Active Voltage Control
Mu, C., Liu, Z., Yan, J., Jia, H., & Zhang, X. (2023) · IEEE Transactions on Smart Grid · doi:10.1109/tsg.2023.3298807 · Cited by 63
Ergodic Energy Management Leveraging Resource Variability in Distribution Grids
Wang, G., Kekatos, V., Conejo, A. J., & Giannakis, G. B. (2016) · IEEE Transactions on Power Systems · doi:10.1109/tpwrs.2016.2524679 · Cited by 60
Distribution System Restructuring: Distribution LMP via Unbalanced ACOPF
Liu, Y., Li, J., & Wu, L. (2017) · IEEE Transactions on Smart Grid · doi:10.1109/tsg.2016.2647692 · Cited by 60
Dispatching Stochastic Heterogeneous Resources Accounting for Grid and Battery Losses
Stai, E., Reyes-Chamorro, L., Sossan, F., Boudec, J. L., & Paolone, M. (2017) · IEEE Transactions on Smart Grid · doi:10.1109/tsg.2017.2715162 · Cited by 60
Data-Driven Optimal Voltage Regulation Using Input Convex Neural Networks
Chen, Y., Shi, Y., & Zhang, B. (2020) · Electric Power Systems Research · doi:10.1016/j.epsr.2020.106741 · Cited by 92
Sarantakos, I., Zografou-Barredo, N.-M., Huo, D., & Greenwood, D. (2021) · IEEE Transactions on Power Systems · doi:10.1109/tpwrs.2021.3071088 · Cited by 59
Advanced optimization methods for power systems
Panciatici, P., Campi, M. C., Garatti, S., Low, S. H., Molzahn, D. K., Sun, A., & Wehenkel, L. A. (2014) · Power Systems Computation Conference · doi:10.1109/pscc.2014.7038504 · Cited by 58
Self-citationDecentralized Reactive Power Compensation Using Nash Bargaining Solution
Nguyen, H. K., Mohsenian‐Rad, H., Khodaei, A., & Han, Z. (2015) · IEEE Transactions on Smart Grid · doi:10.1109/tsg.2015.2500729 · Cited by 58
Optimal Multi-Period Dispatch of Distributed Energy Resources in Unbalanced Distribution Feeders
Nazir, N., Racherla, P. N., & Almassalkhi, M. R. (2020) · IEEE Transactions on Power Systems · doi:10.1109/tpwrs.2019.2963249 · Cited by 59
Ghasemi, M. A., & Parniani, M. (2016) · Electric Power Systems Research · doi:10.1016/j.epsr.2015.12.030 · Cited by 56
Multistage Multiobjective Volt/VAR Control for Smart Grid-Enabled CVR With Solar PV Penetration
Singh, S. P., Pamshetti, V. B., Thakur, A. K., & Singh, S. P. (2020) · IEEE Systems Journal · doi:10.1109/jsyst.2020.2992985 · Cited by 56
Dao, T. V., Chaitusaney, S., & Nguyen, H. T. N. (2016) · IEEE Transactions on Smart Grid · doi:10.1109/tsg.2016.2536782 · Cited by 55
Fundamental Review of the OPF Problem: Challenges, Solutions, and State-of-the-Art Algorithms
Yang, Z., Zhong, H., Xia, Q. L., & Kang, C. (2017) · Journal of Energy Engineering · doi:10.1061/(asce)ey.1943-7897.0000510 · Cited by 53
Liu, X., Cramer, A. M., & Liao, Y. (2015) · Electric Power Systems Research · doi:10.1016/j.epsr.2015.06.003 · Cited by 50
Optimum energy resource scheduling in a microgrid using a distributed algorithm framework
Rokni, S. G. M., Radmehr, M., & Zakariazadeh, A. (2017) · Sustainable Cities and Society · doi:10.1016/j.scs.2017.11.016 · Cited by 49
Optimal distribution systems reconfiguration for radial and meshed grids
Hijazi, H., & Thiébaux, S. (2015) · International Journal of Electrical Power & Energy Systems · doi:10.1016/j.ijepes.2015.02.026 · Cited by 48
Bansal, S., Zeilinger, M. N., & Tomlin, C. J. (2014) · IEEE Conference on Decision and Control (CDC) · doi:10.1109/cdc.2014.7040312 · Cited by 48
Appearance of multiple stable load flow solutions under power flow reversal conditions
Nguyen, H. D., & Turitsyn, K. S. (2014) · IEEE Power Engineering Society General Meeting · doi:10.1109/pesgm.2014.6938797 · Cited by 47
Distributed Multi-Period Optimal Power Flow for Demand Response in Microgrids
Scott, P., & Thiébaux, S. (2015) · ACM International Conference on Future Energy Systems (e-Energy) · doi:10.1145/2768510.2768534 · Cited by 45
Liu, Y., Guo, L., Lu, C., Chai, Y., Gao, S., & Xu, B. (2019) · IEEE Access · doi:10.1109/access.2019.2912004 · Cited by 44
Nowak, S., Wang, L., & Metcalfe, M. S. (2020) · International Journal of Electrical Power & Energy Systems · doi:10.1016/j.ijepes.2020.105858 · Cited by 44
Chowdhury, M. M.-U.-T., & Kamalasadan, S. (2021) · IEEE Transactions on Industry Applications · doi:10.1109/tia.2021.3107825 · Cited by 44
Energy saving estimation in distribution network with smart grid‐enabled CVR and solar PV inverter
Singh, S. P., & Singh, S. P. (2017) · IET Generation Transmission & Distribution · doi:10.1049/iet-gtd.2017.0973 · Cited by 43
Convex relaxation of optimal power flow: A tutorial
Low, S. H. (2013) · IREP Symposium on Bulk Power System Dynamics and Control (IREP) · doi:10.1109/irep.2013.6629391 · Cited by 41
Self-citationNetwork flow and copper plate relaxations for AC transmission systems
Coffrin, C., Hijazi, H., & Hentenryck, P. V. (2016) · Power Systems Computation Conference · doi:10.1109/pscc.2016.7540869 · Cited by 40
A Linearized Power Flow Model for Optimization in Unbalanced Distribution SystemsPreprint
Sankur, M., Dobbe, R., Stewart, E., Callaway, D. S., & Arnold, D. (2016) · arXiv (Cornell University) · doi:10.48550/arxiv.1606.04492 · Cited by 38
Metadata
- Authors
- Farivar, M., Clarke, C. R., Low, S. H., & Chandy, K. M.
- Affiliations
- California Institute of Technology (US)
- Edison International (United States) (US)
- Venue
- 2011 IEEE International Conference on Smart Grid Communications (SmartGridComm)
- Publisher
- IEEE
- Published
- 2011-10
- Pages
- 457-462
- OpenAlex
- W1978282571
- Cited by
- 331
- References
- 13
- Citations by year
- 2026: 5 · 2025: 14 · 2024: 13 · 2023: 12 · 2022: 14 · 2021: 22 · 2020: 35 · 2019: 26 · 2018: 24 · 2017: 36 · 2016: 28 · 2015: 30 · 2014: 39 · 2013: 20 · 2012: 12
- FWCI
- 31.25
- Type
- conference paper
- Language
- en
- Open access
- green
- zenodo.org
- Licence
- public-domain
- Locations
- IEEE International Conference on Smart Grid Communications (SmartGridComm) (publishedVersion)
- CaltechAUTHORS (California Institute of Technology) (submittedVersion)
- Zenodo (CERN European Organization for Nuclear Research) (submittedVersion, public-domain)
- Topics
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Optimal Power Flow Distribution
- Physical Sciences › Engineering › Control and Systems Engineering › Microgrid Control and Optimization
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Power Quality and Harmonics
- Keywords
- volt/var control, inverter control, distribution systems, renewable generation integration, convex relaxation, radial distribution systems, power quality, IEEE 1547, non-convex optimization
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review