Shuai Yan, Mingchun Hou, Lei Luo, Dali Xiao, Bingyuan Tan, Xiong Xiao, and Wenguang Wu


  1. [1] C. Jin, W. Li, J. Shen, P. Li, L. Liu, and K. Wen, Activefrequency response based on model predictive control for bulkpower system, IEEE Transactions on Power Systems, 34(4),2019, 3002–3013.
  2. [2] P. Hu, X. Ai, and Z. Yang, Day-ahead optimal schedulingfor cluster building with integrated energy system consideringpower sharing, Electric Power Automation Equipment, 39(8),2019, 239–245.
  3. [3] A. Morteza, M. Sadipour, R.S. Fard, S. Taheri, and A. Ahmadi,A dagging-based deep learning framework for transmissionline flexibility assessment, IET Renewable Power Generation,17(5), 2023, 1092–1105.
  4. [4] B. Zhou, J. Zou, C.Y. Chung, H. Wang, N. Liu, N. Voropai,and D. Xu, Multi-microgrid energy management systems:Architecture, communication, and scheduling strategies,Journal of Modern Power Systems and Clean Energy, 9(3),2021, 463–476.
  5. [5] J. Wang, H. Zhong, Y. Yu, J. Wang, and Q. Xia, Incentivemechanism for cooperative energy sharing, Proc. of 2018 IEEEPower & Energy Society General Meeting, Portland, OR, 2018,1–5.
  6. [6] X. Song, Y. Lu, L. Shen, and X. Shi, Will China’s buildingsector participate in emission trading system? Insights frommodelling an owner’s optimal carbon reduction strategies,Energy Policy, 118, 2018, 232–244.
  7. [7] N. Ghadimi, M. Sedaghat, K.K Azar, and K.K Azar, Aninnovative technique for optimization and sensitivity analysisof a PV/DG/BESS based on converged Henry gas solubilityoptimizer: A case study, IET Generation, Transmission andDistribution, 4330–4339, Feb. 2023.
  8. [8] Y. Zhang, X. Dai, and X. Han, Renewable energy integrationcapacity assessment in regional power grid based on anenhanced sequential production simulation, The Journal ofEngineering, 2017(13), 2017, 1065–1070.
  9. [9] K. Rahmani, F. Kavousifard, and A. Abbasi, Considerationeffect of wind farms on the network reconfiguration in thedistribution systems in an uncertain environment, Journalof Experimental & Theoretical Artificial Intelligence, 29(5),2017:1–15.
  10. [10] M. Ilbeigi, A. Morteza, and R. Ehsani, An infrastructure-less emergency communication system: A blockchain-basedframework, Journal of Computing in Civil Engineering, 36(2),2022, 36.
  11. [11] S. Abbasi, A, Kavousi-Fard, A. Abbasi, and S. Tabatabaie,Optimal probabilistic reconfiguration of smart distribu-tion grids considering penetration of plug-in hybrid elec-tric vehicles, Journal of Intelligent & Fuzzy Systems:7Applications in Engineering and Technology, 29(5), 2015,1847–1855.
  12. [12] M. Ghiasi, T. Niknam, Z. Wangand, M. Mehrandezh, M.Dehghani, and N. Ghadimi, A comprehensive review of cyber-attacks and defense mechanisms for improving security in smartgrid energy systems: Past, present and future, IET Generation,Electric Power Systems Research, 215(Part A), 2023,108975.
  13. [13] Z. Chen, J. Yang, and K. Jin, Control strategy of time-shiftfacility agriculture load and photovoltaic local consumptionbased on energy blockchain, Electric Power AutomationEquipment, 41(2), 2021, 47–55.
  14. [14] X. Zhang, Y. Zhang, X. Ji, X. Han, M. Yang, andB. Xu, Synergetic optimized scheduling of transmissionand distribution network with electricity-gas-heat integratedenergy system, Power System Technology, 46(11), 2022,4256–4270.
  15. [15] X. L¨u, T. Liu, X. Liu, C. He, L. Nan, and H. Zeng, Low-carbon economic dispatch of multi-energy park consideringhigh proportion of renewable energy, Journal of Shanghai JiaoTong University, 55(12), 2021, 1586–1597.
  16. [16] A. Morteza, M. Ilbeigi, and J. Schwed, A Blockchaininformation management framework for construction safety,Proc. ASCE International Conf. on Computing in CivilEngineering 2021, Orlando, FL, May 2022.
  17. [17] S. Shargh, B.K. Ghazani, B. Mohammadi-Ivatloo, H. Seyedi,and M. Abapour, Probabilistic multi-objective optimal powerflow considering correlated wind power and load uncertainties,Renewable Energy, 94, 2016, 10–21.

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