Optimization Study of Carbon Emissions in Wind Power Integrated Systems Based on Optimal Dispatch Algorithm
By:
References
- Abid A., Malik T. N., Ashraf M. M. Combined Emission Economic Dispatch of Power System in Presence of Solar and Wind Using Flower Pollination Algorithm.
Mehran Univ. Res. J. En. 2019:38(3):581–598.https://doi.org/10.22581/muet1982.1903.05">https://doi.org/10.22581/muet1982.1903.05 - Obaro A.,
et al . Energy Dispatch of Decentralized Hybrid Power System.Int. J. Renew. Energy R. 2018:8(4):2131–2145. - Zhao B. C.,
et al . System-level performance optimization of molten-salt packed-bed thermal energy storage for concentrating solar power.Appl. Energ. 2018:226:225–239.https://doi.org/10.1016/j.apenergy.2018.05.081">https://doi.org/10.1016/j.apenergy.2018.05.081 - Kim S. K., Lee K. B. Robust Offset-Free Speed Tracking Controller of Permanent Magnet Synchronous Generator for Wind Power Generation Applications.
Electronics 2018:7(4):48.https://doi.org/10.3390/electronics7040048">https://doi.org/10.3390/electronics7040048 - Hoseinzadeh B.,
et al . Emergency wind power plant re-dispatching against transmission system cascading failures using reverse tracking of line power flow.IET Gener. Transm. Dis. 2020:14(16):3241–3249.https://doi.org/10.1049/iet-gtd.2019.1950">https://doi.org/10.1049/iet-gtd.2019.1950 - Ghaljehei M.,
et al . Stochastic SCUC considering compressed air energy storage and wind power generation: A techno-economic approach with static voltage stability analysis.Int. J. Elec. Power 2018:100:489–507.https://doi.org/10.1016/j.ijepes.2018.02.046">https://doi.org/10.1016/j.ijepes.2018.02.046 - Rao D. S. N. M., Kumar N. Optimal load dispatch solution of power system using enhanced harmony search algorithm.
Eur. J. Elec. Eng. 2018:20(4):469–483.https://doi.org/10.3166/EJEE.20.469-483">https://doi.org/10.3166/EJEE.20.469-483 - Tejaswini K. N., Rao G. K. Consensus Based Economic Dispatch including System Power Losses.
Int. J. Eng. Technol. 2018:7(1):178–181.https://doi.org/10.14419/ijet.v7i1.8.11545">https://doi.org/10.14419/ijet.v7i1.8.11545 - Zhang J. J.,
et al . Parallel Dispatch: A New Paradigm of Electrical Power System Dispatch.IEEE/CAA J. Automatic. 2018:5(1):311–319.https://doi.org/10.1109/JAS.2017.7510778">https://doi.org/10.1109/JAS.2017.7510778 - Zhang H., Shen J., Wang G. Day-ahead stochastic optimal dispatch of LCC-HVDC interconnected power system considering flexibility improvement measures of sending system.
Int. J. Elec. Power 2022:138:107937.https://doi.org/10.1016/j.ijepes.2021.107937">https://doi.org/10.1016/j.ijepes.2021.107937 - Yuan J., Cheng K., Qu K. Optimal dispatching of high-speed railway power system based on hybrid energy storage system.
Energy Rep. 2022:8(13):433–442.https://doi.org/10.1016/j.egyr.2022.08.039">https://doi.org/10.1016/j.egyr.2022.08.039 - Si Y.,
et al . Game Approach to HDR-TS-PV Hybrid Power System Dispatching.Appl. Sci. 2021:11(3):1–22.https://doi.org/10.3390/app11030914">https://doi.org/10.3390/app11030914 - Sahoo A.,
et al . Chaotic Butterfly Optimization Algorithm Applied to Multi-objective Economic and Emission Dispatch in Modern Power System.Rec. Adv. Comput. Sci. Commun. 2022:15(2):170–185.https://doi.org/10.2174/2666255813999200818140528">https://doi.org/10.2174/2666255813999200818140528 - Dey S. K., Dash D. P., Basu M. Multi-Objective Economic Environmental Dispatch of Variable Hydro-Wind-Thermal Power System.
Int. J. Appl. Metaheur. 2021:12(2):16–35.https://doi.org/10.4018/IJAMC.2021040102">https://doi.org/10.4018/IJAMC.2021040102 - Feng J.,
et al . Flexible optimal scheduling of power system based on renewable energy and electric vehicles.Energy Rep. 2022:8(S1):1414–1422.https://doi.org/10.1016/j.egyr.2021.11.065">https://doi.org/10.1016/j.egyr.2021.11.065 - Thorat L., Skjetne R., Osen O. L. Genset scheduling in a redundant electric power system for an offshore vessel using mixed integer linear programming.
J. Offshore Mech. Arct. 2021:143(6):1–10.https://doi.org/10.1115/1.4050643">https://doi.org/10.1115/1.4050643 - Bhadoria A., Marwaha S. Moth flame optimizer-based solution approach for unit commitment and generation scheduling problem of electric power system.
J. Comput. Des. Eng. 2020:7(5):668–683.https://doi.org/10.1093/jcde/qwaa050">https://doi.org/10.1093/jcde/qwaa050 - Gupta P. P.,
et al . Optimal electric vehicles charging scheduling for energy and reserve markets considering wind uncertainty and generator contingency.Int. J. Energ. Res. 2022:46(4):4516–4539.https://doi.org/10.1002/er.7446">https://doi.org/10.1002/er.7446 - Eladl A. A., Eldesouky A. A. Optimal economic dispatch for multi heat-electric energy source power system.
Int. J. Elec. Power 2019:110:21–35.https://doi.org/10.1016/j.ijepes.2019.02.040">https://doi.org/10.1016/j.ijepes.2019.02.040 - Athab F. A., Saeed W. Economic power dispatch for an interconnected power system based on reliability indices.
Indones. J. Electr. Eng. Comput. Sci. 2020:20(2):777–787.https://doi.org/10.11591/ijeecs.v20.i2.pp777-787">https://doi.org/10.11591/ijeecs.v20.i2.pp777-787 - Shen N., Zhao Y., Deng R. A review of carbon trading based on an evolutionary perspective.
Int. J. Clim. Chang. Str. 2020:12(5):739–756. - Lu J., Sun X. Carbon regulations, production capacity, and low-carbon technology level for new products with incomplete demand information.
J. Clean. Prod. 2020:282(1):1–19.https://doi.org/10.1016/j.jclepro.2020.124551">https://doi.org/10.1016/j.jclepro.2020.124551 - Chen X., Wang J., Hu D. Study on the effect of rent-seeking on carbon emission trading market performance under free carbon emission allowances.
Syst. Eng.-Theor. Pract. 2018:38(1):93–101.https://doi.org/10.12011/1000-6788(2018)01-0093-09">https://doi.org/10.12011/1000-6788(2018)01-0093-09 - Rautray R., Balabantaray R. C. An evolutionary framework for multi document summarization using Cuckoo search approach: MDSCSA.
Appl. Comput. Inform. 2018:14(2):134–144.https://doi.org/10.1016/j.aci.2017.05.003">https://doi.org/10.1016/j.aci.2017.05.003 - Choi J. Y.,
et al . Prediction of Dynamic Stability Using Mapped Chebyshev Pseudospectral Method.Int. J. Aerosp. Eng. 2018:2018(2):2508153.1–2508153.14.https://doi.org/10.1155/2018/2508153">https://doi.org/10.1155/2018/2508153 - Ting T. O., Rao M. V. C., Loo C. K. A novel approach for unit commitment problem via an effective hybrid particle swarm optimization.
IEEE T. Power Syst. 2006:21(1):411–418.https://doi.org/10.1109/TPWRS.2005.860907">https://doi.org/10.1109/TPWRS.2005.860907 - Amiri A.,
et al . Adaptive Shewhart Control Charts Under Fuzzy Parameters with Tuned Particle Swarm Optimization Algorithm.J. Ind. Integr. Manag. 2023:08(02):241–276.https://doi.org/10.1142/S2424862221500226">https://doi.org/10.1142/S2424862221500226
Language: English
Page range: 107 - 119
Submitted on: Oct 8, 2023
Accepted on: Dec 27, 2023
Published on: Mar 2, 2024
Published by: Riga Technical University
In partnership with: Paradigm Publishing Services
Publication frequency: 2 times per year
Keywords:
Related subjects:
© 2024 Xiaohui Zhu, Lisan Zhao, published by Riga Technical University
This work is licensed under the Creative Commons Attribution 4.0 License.