Integrated energy hubs; Demand response; Cooperative methods
Abstract :
[en] Energy hub systems integrate various energy sources and interconnect different energy
carriers in order to enhance the flexibility of the system. In this paper, a cooperative
framework is proposed in which a network of energy hubs collaborate together and share
their resources in order to reduce their costs. Each hub has several sources including CHP,
boiler, renewable sources, electrical chiller, and absorption chiller. Moreover, energy
storages are considered for electrical, heating, and cooling systems in order to increase the
flexibility of energy hubs. Unlike the methods based on Nash-equilibrium points, which find
the equilibrium point and have no guarantee for optimality of the solution, the employed
cooperative method finds the optimal solution for the problem. We utilize the Shapley value
to allocate the overall gain of the hub’s coalition based on the contribution and efficiency of
the energy hubs. The proposed method is modeled as a mixed integer linear programming
problem, and the cost of network energy hubs are decreased in the cooperative operation,
which shows the efficiency of this model. The results show 18.89, 10.23, and 8.72%
improvement for hub1, hub2, and hub3, respectively, by using the fair revenue mechanism.
Research center :
“Interdisciplinary Centre for Security, Reliability and Trust (SnT) > FINATRAX - Digital Financial Services and Cross-organizational Digital Transformations”
Disciplines :
Computer science Management information systems
Author, co-author :
Bahmani, Ramin ; University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > FINATRAX
Karimi, Hamid; School of Electrical Engineering, Center of Excellence for Power System Automation and Operation, Iran University of Science and Technology (IUST), Iran.
Jadid, Shahram; School of Electrical Engineering, Center of Excellence for Power System Automation and Operation, Iran University of Science and Technology (IUST), Iran.
External co-authors :
yes
Language :
English
Title :
Cooperative energy management of multi-energy hub systems considering demand response programs and ice storage
Alternative titles :
[en] Cooperative energy management of multi-energy hub systems considering demand response programs and ice storage
Publication date :
April 2021
Journal title :
International Journal of Electrical Power and Energy Systems
ISSN :
0142-0615
eISSN :
1879-3517
Publisher :
Elsevier, Amsterdam, Netherlands
Peer reviewed :
Peer Reviewed verified by ORBi
Focus Area :
Security, Reliability and Trust
Development Goals :
9. Industry, innovation and infrastructure
Funding text :
The authors gratefully acknowledge the financial support of the Kopernikus-project “SynErgie” by the Federal Ministry of Education and Research BMBF and the project supervision by the project management organization Projekttra ̈ger Jülich (PtJ) (Grant number 03SFK3G1).
Parisio, A., Del Vecchio, C., Vaccaro, A., A robust optimization approach to energy hub management. Int J Electr Power Energy Syst 42:1 (2012), 98–104.
Luo, X., Liu, J., Liu, X., Energy scheduling for a three-level integrated energy system based on energy hub models: a hierarchical Stackelberg game approach. Sustain Cities Soc, 52, 2019, 101814.
Khoshjahan, M., Moeini-Aghtaie, M., Fotuhi-Firuzabad, M., Dehghanian, P., Mazaheri, H., Advanced bidding strategy for participation of energy storage systems in joint energy and flexible ramping product market. IET Gener Transm Distrib, 2020, 1–10.
Zhao, T., Pan, X., Yao, S., Ju, C., Li, L., Strategic bidding of hybrid AC/DC microgrid embedded energy hubs: a two-stage chance constrained stochastic programming approach. IEEE Trans Sustain Energy 11:1 (2020), 116–125.
Wang X, Liu Y, Liu C, Liu J. Coordinating energy management for multiple energy hubs: From a transaction perspective. Int J Electr Power Energy Syst 2020;121. p. 106060.
Fan, S., Li, Z., Wang, J., Piao, L., Ai, Q., Cooperative economic scheduling for multiple energy hubs: a bargaining game theoretic perspective. IEEE Access 6 (2018), 27777–27789.
Heidari, A., Mortazavi, S.S., Bansal, R.C., Stochastic effects of ice storage on improvement of an energy hub optimal operation including demand response and renewable energies. Appl Energy, 261(September 2020), 2019, 114393.
Vahid-Pakdel, M.J., Nojavan, S., Mohammadi-ivatloo, B., Zare, K., Stochastic optimization of energy hub operation with consideration of thermal energy market and demand response. Energy Convers Manage 145 (2017), 117–128.
Bostan, A., Nazar, M.S., Shafie-khah, M., Catalão, J.P.S., Optimal scheduling of distribution systems considering multiple downward energy hubs and demand response programs. Energy, 190, 2020.
Liu T, Zhang D, Wang S, Wu T. Standardized modelling and economic optimization of multi-carrier energy systems considering energy storage and demand response. Energy Convers Manage 2019;182:126–142.
Ghanbari, A., Karimi, H., Jadid, S., Optimal planning and operation of multi-carrier networked microgrids considering multi-energy hubs in distribution networks. Energy, 204, 2020, 117936.
Gholizadeh N, Gharehpetian GB, Abedi M, Nafisi H, Marzband M. An innovative energy management framework for cooperative operation management of electricity and natural gas demands. Energy Convers Manage 200;2019:112069.
Salehi, J., Namvar, A., Gazijahani, F.S., Scenario-based co-optimization of neighboring multi carrier smart buildings under demand response exchange. J Clean Prod 235 (2019), 1483–1498.
Sobhani, S.O., Sheykhha, S., Madlener, R., An integrated two-level demand-side management game applied to smart energy hubs with storage. Energy, 206, 2020, 118017.
Salimi, M., Ghasemi, H., Adelpour, M., Vaez-ZAdeh, S., Optimal planning of energy hubs in interconnected energy systems: a case study for natural gas and electricity. IET Gener Transm Distrib 9:8 (2015), 695–707.
Sheikhi A, Bahrami S, Ranjbar AM. An autonomous demand response program for electricity and natural gas networks in smart energy hubs. Energy 2015:1–10.
Bahrami S, Member S, Sheikhi A, Member S. From demand response in smart grid toward integrated demand response in smart energy hub; 2015. p. 1–9.
Bahrami, S., Toulabi, M., Ranjbar, S., Moeini-Aghtaie, M., Ranjbar, A.M., A decentralized energy management framework for energy hubs in dynamic pricing markets. IEEE Trans Smart Grid 9:6 (2018), 6780–6792.
Sheikhi, A., Rayati, M., Bahrami, S., Ranjbar, A.M., Integrated demand side management game in smart energy hubs. IEEE Trans Smart Grid 6:2 (2015), 675–683.
Li, Y., Li, Z., Wen, F., Shahidehpour, M., Privacy-preserving optimal dispatch for an integrated power distribution and natural gas system in networked energy hubs. IEEE Trans Sustain Energy 10:4 (2018), 2028–2038.
Nima Nasiri, Yazdankhah Ahmad Sadeghi, Mirzaei Mohammad Amin, Loni Abdolah, Mohammadi-Ivatloo Behnam, Zare Kazem, Marzband Mousa. A bi-level market-clearing for coordinated regional-local multi-carrier systems in presence of energy storage technologies. Sustain Cities Soc 2020;63:102439.
Mirzapour-Kamanaj, A., Majidi, M., Zare, K., Kazemzadeh, R., Optimal strategic coordination of distribution networks and interconnected energy hubs: a linear multi-follower bi-level optimization model. Int J Electr Power Energy Syst, 119, 2020, 105925.
Ma, T., Wu, J., Hao, L., Energy flow modeling and optimal operation analysis of the micro energy grid based on energy hub. Energy Convers Manage 133 (2017), 292–306.
Rakipour, D., Barati, H., Probabilistic optimization in operation of energy hub with participation of renewable energy resources and demand response. Energy 173 (2019), 384–399.
Lu, X., Liu, Z., Ma, L., Wang, L., Zhou, K., Feng, N., A robust optimization approach for optimal load dispatch of community energy hub. Appl Energy, 259, 2020, 114195.
Cao, Y., Wang, Q., Du, J., Nojavan, S., Jermsittiparsert, K., Ghadimi, N., Optimal operation of CCHP and renewable generation-based energy hub considering environmental perspective: an epsilon constraint and fuzzy methods. Sustain Energy Grids Networks, 20, 2019, 100274.
Vahid Pakdel, M.J., Sohrabi, F., Mohammadi-Ivatloo, B., Multi-objective optimization of energy and water management in networked hubs considering transactive energy. J Clean Prod, 266, 2020, 121936.
Gholizadeh N, Vahid-Pakdel MJ, Mohammadi-ivatloo B. Enhancement of demand supply's security using power to gas technology in networked energy hubs. Int J Electr Power Energy Syst 109;2019:83–94.
Liu, T., Zhang, D., Wu, T., Standardised modelling and optimisation of a system of interconnected energy hubs considering multiple energies—electricity, gas, heating, and cooling. Energy Convers Manage, 205(November 2020), 2019, 112410.
Faigle, U., Kern, W., The Shapley value for cooperative games under precedence constraints. Int J Game Theory 21:3 (1992), 249–266.
Gao, J., Yang, X., Liu, D., Uncertain Shapley value of coalitional game with application to supply chain alliance. Appl Soft Comput J 56 (2017), 551–556.