The DOI matches its Crossref record; the references it cites are not checked yet.
TSO and DSO with large‐scale distributed energy resources: A security constrained unit commitment coordinated solution
Open accessAbstract
Modern power system requires optimally coordinated operation between transmission and distribution systems due to large-scale integration of distributed energy resources (DERs). Commonly, transmission system operator (TSO) solves its own cost optimization problem and evaluates required targets for each distribution system operator (DSO). Thus, TSO problem becomes more complex and highly scaled with increase in number of connected distribution systems, which requires more computational time and resources. Therefore, this paper proposed a method to reduce computational burden on TSO and solve coordinated security constrained unit commitment (C-SCUC) problem by involving a coordinator in upper level hierarchy. Coordinator is required to solve system-wide problem to adjust targets for transmission system (TS) and all distribution systems (DS). Besides, TSO and DSO only need to solve their own cost optimization problems. In this paper, we have proposed analytical target cascading (ATC) along with hybridized particle swarm optimization with differential evolution (PSO-DE) for solving increased complexity of the coordinated problem. ATC provides coordination between transmission and distribution sections of power system while hybrid PSO-DE provides better accuracy of optimization in ATC layers. For evaluation of efficacy of proposed method, this paper has taken IEEE 118-bus system as TS and IEEE 33-bus system as DS. Results has depicted that proposed method could help TSO in reducing computational resources and improving computational time.
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 check wasn’t confident either way, so it gives no verdict — never disputed.
In the citing paper
“Due to EV's inconsistent charging behaviors, the grid has unexpected operation risks [5] and the distribution networks security is undermined even more.”
From A Review: The Impact of High Penetration of EVs on Distribution Network and Its Management Strategy (2025) · cites this paper as [5]
Experimental — accuracy not yet measuredThe check wasn’t confident either way, so it gives no verdict — never disputed.
In the citing paper
“Due to EV's inconsistent charging behaviors, the grid has unexpected operation risks [5]”
From A Review: The Impact of High Penetration of EVs on Distribution Network and Its Management Strategy (2025) · cites this paper as [5]
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
The citation lists haven’t been fetched yet
References 38 · Cited by 42
Research works printed but not linked: 40
- JainH RahimiK TbailehA BroadwaterRP Akshay KumarJ DilekM.Integrated transmission & distribution system modeling and analysis: need & advantages. Paper presented at: 2016 IEEE Power and Energy Society General Meeting (PESGM); 17‐21 July 2016 2016. · DOI
- 10.1109/MPE.2015.2423211 · DOI
- 10.1109/TPWRS.2014.2307863 · DOI
- DvijothamK.Systems of quadratic equations: efficient solution algorithms and conditions for solvability. Paper presented at: 2015 53rd Annual Allerton Conference on Communication Control and Computing (Allerton); 29 Sept.‐2 Oct. 2015 2015. · DOI
- YasudaT DahanX HuangY‐J TakagiT SakuraiK.MQ challenge: hardness evaluation of solving multivariate quadratic problems. IACR Cryptology ePrint Archive2015;2015:275.
- 10.1109/TSTE.2015.2500571 · DOI
- Chung K, 2011, Multi‐area generation scheduling algorithm with regionally distributed optimal power flow using alternating direction method, Int J Electr Power Energy Syst, 33, 1527, 10.1016/j.ijepes.2010.11.013 · DOI
- 10.1016/j.compchemeng.2018.09.019 · DOI
- 10.1109/TSG.2016.2571848 · DOI
- 10.1049/iet-gtd.2016.0616 · DOI
- 10.1016/j.energy.2018.07.088 · DOI
- 10.1109/TSG.2016.2614904 · DOI
- 10.1007/s00158-005-0579-0 · DOI
- 10.2514/1.15326 · DOI
- 10.1109/TPWRS.2018.2885805 · DOI
- 10.1109/TSG.2016.2580578 · DOI
- 10.1002/etep.2107 · DOI
- 10.1109/TPWRS.2014.2360063 · DOI
- MiguelH SalmanM MichaelS GonçaloC Rodrigo DeL.Optimal sizing and placement of distributed generation: MILP vs PSO comparison in a real microgrid application. Paper presented at: Intelligent System Applications to Power Systems (ISAP) Conference; 2017/09// 2017.
- 10.1016/j.ijepes.2012.11.002 · DOI
- 10.1016/j.ijepes.2012.01.005 · DOI
- 10.1016/j.applthermaleng.2018.11.122 · DOI
- KhamsawangS WannakarnP JiriwibhakornS.Hybrid PSO‐DE for solving the economic dispatch problem with generator constraints. Paper presented at: 2010 the 2nd international conference on computer and automation engineering (ICCAE)2010. · DOI
- 10.1142/S1793005711001986 · DOI
- KargarianA FuY LiuP WangC.A system of systems engineering approach for unit commitment in multi‐area power markets. Paper presented at: 2014 IEEE PES General Meeting|Conference & Exposition; 27‐31 July 2014 2014. · DOI
- 10.1002/etep.2164 · DOI
- 10.1109/TPWRS.2017.2787645 · DOI
- 10.1016/j.energy.2018.04.021 · DOI
- LiL ChuX BoQ GaoL ShaoX.Analytical target cascading based on physical programming. Conference Proceedings ‐ IEEE International Conference on Systems Man and Cybernetics2010:3060‐3067.
- DorMohammadiS Rais‐rohaniM.Analytical target cascading framework using the exponential method of multipliers. Paper presented at: 12th AIAA Aviation Technology Integration and Operations (ATIO) Conference and 14th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference2012. · DOI
- YangS WangW LinQ ChenJ.A novel PSO‐DE co‐evolutionary algorithm based on decomposition framework. Paper presented at: International Conference on Smart Computing and Communication2016. · DOI
- 10.1109/ACCESS.2018.2864188 · DOI
- 10.1109/TEVC.2011.2112662 · DOI
- 10.2514/2.2025 · DOI
- 10.1109/TPWRS.2010.2051168 · DOI
- UllmannMRD PimentelKF MeloLAD CruzGD VinhalC.Comparison of PSO variants applied to large scale optimization problems. Paper presented at: 2017 IEEE Latin American Conference on Computational Intelligence (LA‐CCI); 8‐10 Nov. 2017 2017. · DOI
- 10.1016/j.neucom.2013.03.075 · DOI
- BraginM DvorkinY DarvishiA.Toward coordinated transmission and distribution operations. Paper presented at: 2018 IEEE Power & Energy Society General Meeting (PESGM)2018. · DOI
- 10.1016/j.solener.2018.05.003 · DOI
- 10.1109/TPWRS.2014.2360851 · DOI
Metadata
- Authors
- Nawaz, A., Wang, H., Wu, Q., & Kumar Ochani, M.
- Affiliations
- Shandong University (CN)
- Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of EducationShandong University Jingshi Road #17923 Jinan 250000 China
- Corresponding author
- Wang, Hongtao
- Venue
- International Transactions on Electrical Energy Systems
- Publisher
- Wiley
- Published
- 2019-11-27
- Volume
- 30
- Issue
- 3
- ISSN
- 2050-7038 (ISSN-L)
- OpenAlex
- W2990990632
- Cited by
- 42
- References
- 38
- Citations by year
- 2026: 7 · 2025: 4 · 2024: 4 · 2023: 2 · 2022: 9 · 2021: 13 · 2020: 3
- FWCI
- 2.25
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- International Transactions on Electrical Energy Systems (publishedVersion)
- Technical University of Denmark, DTU Orbit (Technical University of Denmark, DTU) (submittedVersion)
- Topics
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Electric Power System Optimization
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Optimal Power Flow Distribution
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Integrated Energy Systems Optimization
- Keywords
- transmission-distribution coordination, security-constrained unit commitment, distributed energy resources, analytical target cascading, hybrid particle swarm optimization, differential evolution, transmission system operators, distribution system operators, computational burden reduction, hierarchical 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
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: TSO and DSO with large‐scale distributed energy resources: A security constrained unit commitment coordinated solution. https://app.cochat.ai/papers/10.1002/2050-7038.12233
- The paper
- Nawaz, A., Wang, H., Wu, Q., & Kumar Ochani, M. (2020). TSO and DSO with large‐scale distributed energy resources: A security constrained unit commitment coordinated solution. International Transactions on Electrical Energy Systems. https://doi.org/10.1002/2050-7038.12233
