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Increasing penetration of distributed energy resources in the distribution network (DN) is threatening safe operation of the DN, which necessitates setup of the ancillary service market in the DN. In the ancillary service market, distribution system operator (DSO) is responsible for safety of the DN by procuring available capacities of aggregators. Unlike existing studies, this paper proposes a novel market mechanism composed of two parts: choice rule and payment rule. The proposed choice rule simultaneously considers social welfare and fairness, encouraging risk-averse aggregators to participate in the ancillary service market. It is then formulated as a linear programming problem, and a distributed solution using the multi-cut Benders decomposition is presented. Moreover, successful implementation of the choice rule depends on each aggregator’s truthful adoption of private parameters. Therefore, a payment rule is also designed, which is proved to possess two properties: incentive compatibility and individual rationality. Simulation results demonstrate effectiveness of the proposed choice rule on improving fairness and verify properties of the payment rule.
S. Dalhues, Y. Zhou, O. Pohl, F. Rewald, F. Erlemeyer, D. Schmid, J. Zwartscholten, Z. Hagemann, C. Wagner, D. M. Gonzalez, H. Liu, M. M. Zhang, J. Y. Liu, C. Rehtanz, Y. Li, and Y. J. Cao, “Research and practice of flexibility in distribution systems: a review,” CSEE Journal of Power and Energy Systems, vol. 5, no. 3, pp. 285–294, Sep. 2019.
Z. K. Yi, Y. L. Xu, J. G. Zhou, W. C. Wu, and H. B. Sun, “Bi-level programming for optimal operation of an active distribution network with multiple virtual power plants,” IEEE Transactions on Sustainable Energy, vol. 11, no. 4, pp. 2855–2869, Oct. 2020.
Q. R. Sun, Z. Wu, W. Gu, T. Zhu, L. Zhong, and T. Gao, “Flexible expansion planning of distribution system integrating multiple renewable energy sources: an approximate dynamic programming approach,” Energy, vol. 226, pp. 120367, Jul. 2021.
S. Y. Zhou, Z. J. Hu, W. Gu, M. Jiang, and X. P. Zhang, “Artificial intelligence based smart energy community management: a reinforcement learning approach,” CSEE Journal of Power and Energy Systems, vol. 5, no. 1, pp. 1–10, Mar. 2019.
H. R. Bokkisam, S. Singh, R. M. Acharya, and M. P. Selvan, “Blockchain-based peer-to-peer transactive energy system for community microgrid with demand response management,” CSEE Journal of Power and Energy Systems, vol. 8, no. 1, pp. 198–211, Jan. 2022.
T. Morstyn, A. Teytelboym, and M. D. McCulloch, “Designing decentralized markets for distribution system flexibility,” IEEE Transactions on Power Systems, vol. 34, no. 3, pp. 2128–2139, May 2019.
K. Zhang, S. Troitzsch, S. Hanif, and T. Hamacher, “Coordinated market design for peer-to-peer energy trade and ancillary services in distribution grids,” IEEE Transactions on Smart Grid, vol. 11, no. 4, pp. 2929–2941, Jul. 2020.
Y. Jin, Z. Y. Wang, C. W. Jiang, and Y. Zhang, “Dispatch and bidding strategy of active distribution network in energy and ancillary services market,” Journal of Modern Power Systems and Clean Energy, vol. 3, no. 4, pp. 565–572, Dec. 2015.
P. Faria, J. Spínola, and Z. Vale, “Methods for aggregation and remuneration of distributed energy resources,” Applied Sciences, vol. 8, no. 8, pp. 1283, Aug. 2018.
B. Olek and M. Wierzbowski, “Local energy balancing and ancillary services in low-voltage networks with distributed generation, energy storage, and active loads,” IEEE Transactions on Industrial Electronics, vol. 62, no. 4, pp. 2499–2508, Apr. 2015.
G. Fusco and M. Russo, “A decentralized approach for voltage control by multiple distributed energy resources,” IEEE Transactions on Smart Grid, vol. 12, no. 4, pp. 3115–3127, Jul. 2021.
A. C. Rueda-Medina and A. Padilha-Feltrin, “Distributed generators as providers of reactive power support—a market approach,” IEEE Transactions on Power Systems, vol. 28, no. 1, pp. 490–502, Feb. 2013.
Y. Shoham and K. Leyton-Brown, Multiagent Systems: Algorithmic, Game-Theoretic, and Logical Foundations, New York: Cambridge University Press, 2008.
A. K. Zarabie, S. Das, and M. N. Faqiry, “Fairness-regularized DLMP-based bilevel transactive energy mechanism in distribution systems,” IEEE Transactions on Smart Grid, vol. 10, no. 6, pp. 6029–6040, Nov. 2019.
G. Tsaousoglou, J. S. Giraldo, P. Pinson, and N. G. Paterakis, “Mechanism design for fair and efficient DSO flexibility markets,” IEEE Transactions on Smart Grid, vol. 12, no. 3, pp. 2249–2260, May 2021.
J. Rawls, A Theory of Justice, Cambridge: Harvard University Press, 1999.
H. Kim, J. Lee, S. Bahrami, and V. W. S. Wong, “Direct energy trading of microgrids in distribution energy market,” IEEE Transactions on Power Systems, vol. 35, no. 1, pp. 639–651, Jan. 2020.
S. C. Cui, Y. W. Wang, Y. Shi, and J. W. Xiao, “A new and fair peer-to-peer energy sharing framework for energy buildings,” IEEE Transactions on Smart Grid, vol. 11, no. 5, pp. 3817–3826, Sep. 2020.
S. Hanif, K. Zhang, C. M. Hackl, M. Barati, H. B. Gooi, and T. Hamacher, “Decomposition and equilibrium achieving distribution locational marginal prices using trust-region method,” IEEE Transactions on Smart Grid, vol. 10, no. 3, pp. 3269–3281, May 2019.
Z. F. Yang, H. W. Zhong, A. Bose, T. X. Zheng, Q. Xia, and C. Q. Kang, “A linearized OPF model with reactive power and voltage magnitude: a pathway to improve the MW-only DC OPF,” IEEE Transactions on Power Systems, vol. 33, no. 2, pp. 1734–1745, Mar. 2018.
W. Wei, F. Liu, and S. W. Mei, “Nash bargain and complementarity approach based environmental/economic dispatch,” IEEE Transactions on Power Systems, vol. 30, no. 3, pp. 1548–1549, May 2015.
F. Q. You and I. E. Grossmann, “Multicut benders decomposition algorithm for process supply chain planning under uncertainty,” Annals of Operations Research, vol. 210, no. 1, pp. 191–211, Nov. 2013.
H. M. Khodr, F. G. Olsina, P. M. De Oliveira-De Jesus, and J. M. Yusta, “Maximum savings approach for location and sizing of capacitors in distribution systems,” Electric Power Systems Research, vol. 78, no. 7, pp. 1192–1203, Jul. 2008.
R. D. Zimmerman, C. E. Murillo-Sánchez, and R. J. Thomas, “MATPOWER: steady-state operations, planning, and analysis tools for power systems research and education,” IEEE Transactions on Power Systems, vol. 26, no. 1, pp. 12–19, Feb. 2011.
This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
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