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A Stochastic Programming Approach for Energy Hubs Integrated with Renewable Energy Sources Based on Life Cycle Cost


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DOI: https://doi.org/10.15866/irecon.v8i3.18852

Abstract


This study presents a stochastic programming approach to plan the energy hub integrated with renewable energy sources. Energy hub offers significant advantages in energy services such as enhancement of the efficiency, reduction of the emissions and costs, increase of the flexibility and reliability of the system but it has side effects due to the uncertainty of renewable energy sources, energy demands, and prices. Hence, the model with the objective function, which minimizes the expected life cycle cost, simultaneously considers many different technologies of renewable energy sources with the intermittent generation power and uncertainty of energy demands and prices. The uncertainty of parameters is modeled by probability density function then scenarios are generated by scenario matrix from all states of the parameters. The scenario reduction technique is applied to reduce the computational burden. Finally, the proposed model is simulated by GAMS/BONMIN for a test energy hub to illustrate the feasibility and effectiveness compared to the previous approaches.
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Keywords


Energy Hub; Life Cycle Cost; Stochastic Programming; Renewable Energy Sources; Uncertainty

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References


P. Mancarella. MES (multi-energy systems): An overview of concepts and evaluation models. Energy 2014; 65: 1-17.
https://doi.org/10.1016/j.energy.2013.10.041

M.Mohammadi, Y.Noorollahi, B.Mohammadi-ivatloob, H.Yousefia. Energy hub: From a model to a concept – A review. Renewable and Sustainable Energy Reviews 2017; 80: 1512–1527.
https://doi.org/10.1016/j.rser.2017.07.030

X.Dong, C.Quan and T.Jiang. Optimal Planning of Integrated Energy Systems Based on Coupled CCHP. Energies 2018; 11(2621): 1-27
https://doi.org/10.3390/en11102621

S.Pazouki, M.Haghifamb. Optimal planning and scheduling of energy hub in presence of wind, storage and demand response under uncertainty. Electrical Power and Energy Systems 2016; 80: 219–239.
https://doi.org/10.1016/j.ijepes.2016.01.044

A.Dolatabadi, B.Mohammadi-ivatloo, M.Abapour, and S.Tohidi. Optimal Stochastic Design of Wind Integrated Energy Hub. IEEE Transaction on Industrial Informatics 2017; 13(5): 2379-2388
https://doi.org/10.1109/tii.2017.2664101

K.S. Sambaiah. A Review on Optimal Allocation and Sizing Techniques for DG in Distribution Systems. International Journal of Renewable Energy Research 2018; 8(3): 1236-1256.

B.Singh, J.Sharma. A review on distributed generation planning. Renewable and Sustainable Energy Reviews 2017; 76: 529–544.
https://doi.org/10.1016/j.rser.2017.03.034

W. L. Theo, J. S. Lim, W. S. Ho, H. Hashimb, C. T. Lee. Review of distributed generation (DG) system planning and optimisation techniques: Comparison of numerical and mathematical modelling methods. Renewable and Sustainable Energy Reviews 2017; 67: 531–573
https://doi.org/10.1016/j.rser.2016.09.063

F. Nadeem, S. M. Suhail Hussain, P. K. Tiwari and A. K. Goswami, T. S. Ustun. Comparative Review of Energy Storage Systems, Their Roles and Impacts on Future Power Systems. IEEE Access 2018; 7: 4555-4585.
https://doi.org/10.1109/access.2018.2888497

T. Kousksou, P. Bruel, A. Jamil, T. E. Rhafiki, Y.Zeraouli. Energy storage: Applications and challenges. Solar Energy Materials & Solar Cells 2014; 120: 59-80.
https://doi.org/10.1016/j.solmat.2013.08.015

J. A. Momoh, S. S. Reddy. Review of Optimization Techniques for Renewable Energy Resources. IEEE Symposium on Power Electronics and Machines for Wind and Water Applications, 24-26 July 2014, USA.
https://doi.org/10.1109/pemwa.2014.6912225

Z. Abdmouleh, A. Gastli, L. Ben-Brahim, M. Haouari, N. A. Al-Emadi. Review of optimization techniques applied for the integration of distributed generation from renewable energy sources. Renewable Energy 2017; 113: 266-280.
https://doi.org/10.1016/j.renene.2017.05.087

K. Amiri, T. Niknam. Optimal Planning of a Multi-carrier Energy Hub Using the Modified Bird Mating Optimizer. Iranian Journal of Science and Technology, Transactions of Electrical Engineering 2019; 43 (1): 517-526.
https://doi.org/10.1007/s40998-018-0138-5

V. Amir, S. Jadid, M. Ehsan. Optimal Planning of a Multi-Carrier Microgrid (MCMG) Considering Demand-Side Management. International Journal of Renewable Energy Research 2018; 8 (1): 238-249.
https://doi.org/10.3390/en10122109

A. Dolatabadi, B. Mohammadi-Ivatloo. Stochastic risk-constrained scheduling of smart energy hub in the presence of wind power and demand response. Applied Thermal Engineering 2017; 123: 40–49.
https://doi.org/10.1016/j.applthermaleng.2017.05.069

M. Jadidbonab, A. Dolatabadi, B. Mohammadi-Ivatloo, M. Abapour, S. Asadi. Risk-constrained Energy Management of PV Integrated Smart Energy Hub in the Presence of Demand Response Program and Compressed Air Energy Storage. IET Renewable Power Generation 2019; 13 (6):998-1008.
https://doi.org/10.1049/iet-rpg.2018.6018

C. Chena, H. Suna, X. Shena, Y. Guoa, Q. Guoa, T. Xiab. Two-stage robust planning-operation co-optimization of energy hub considering precise energy storage economic model. Applied Energy 2019; 252; 1-14.
https://doi.org/10.1016/j.apenergy.2019.113372

S. Deng, Q. Wu, Z. Jing, L. Wu, F. Wei and X. Zhou. Optimal Capacity Configuration for Energy Hubs Considering Part-Load Characteristics of Generation Units. Energies 2017; 10(1966): 1-19.
https://doi.org/10.3390/en10121966

M. Ristimäki, A. Säynäjoki, J. Heinonen, S. Junnila. Combining life cycle costing and life cycle assessment for an analysis of a new residential district energy system design. Energy 2013; 63: 168-179.
https://doi.org/10.1016/j.energy.2013.10.030

F. Chen, S. Huang, J. Ding, B. Gao, Y. Xie and X. Wang. Fast Reliability Assessing Method for Distribution Network with Distributed Renewable Energy Generation. IOP Conf. Series: Earth and Environmental Science 111 2018, p. 1-9.
https://doi.org/10.1088/1755-1315/111/1/012036

V. V. Thang, and Thanhtung Ha. Optimal siting and sizing of renewable sources in distribution system planning based on life cycle cost and considering uncertainties. AIMS Energy 2019; 7(2): 211–226.
https://doi.org/10.3934/energy.2019.2.211

Z. Zhou, J. Zhang, P. Liu, Z. Li, M. C. Georgiadis, E. N. Pistikopoulos. A two-stage stochastic programming model for the optimal design of distributed energy systems. Applied Energy 2013; 103: 135–144
https://doi.org/10.1016/j.apenergy.2012.09.019

D. Xu, Z. Chen, L. Yang. Scenario tree generation approaches using K-means and LP moment matching methods. Journal of Computational and Applied Mathematics 2012; 236:4561–4579
https://doi.org/10.1016/j.cam.2012.05.020

Z. Chen, Z. Yan. Scenario tree reduction methods through clustering nodes. Computers and Chemical Engineering 2018; 109: 96–111.
https://doi.org/10.1016/j.compchemeng.2017.10.017

Rosenthal RE (2010) GAMS-a user’s guide. GAMS Development Corporation, Washington. [Online].
Available: http://www.gams.com/

A. Ehsan, M. Cheng, and Q. Yang. Scenario-based Planning of Active Distribution Systems Under Uncertainties of Renewable Generation and Electricity Demand. CSEE Journal of Power and Energy Systems 2019; 5(1): 56-62.
https://doi.org/10.17775/cseejpes.2018.00460

Y. Cao, W. Wei, J. Wang, S. Mei, M. Shafie-khah, J. P. S.Catalao. Capacity Planning of Energy Hub in Multi-carrier Energy Networks: A Data-driven Robust Stochastic Programming Approach. IEEE Transactions on Sustainable Energy 2019; Early Access: 1-12.
https://doi.org/10.1109/tste.2018.2878230

A. A. Bayod-Rújula, Y. Yuan, A. Martínez-Gracia, J. Wang, J. Uche and H. Chen. Modelling and Simulation of a Building Energy Hub. Proceedings 2018; 2(1431): 1-6.
https://doi.org/10.3390/proceedings2231431

Hassoune, A., Khafallah, M., Mesbahi, A., Benaaouinate, L., ouragba, T., Control Strategies of a Smart Topology of EVs Charging Station Based Grid Tied RES-Battery, (2018) International Review of Electrical Engineering (IREE), 13 (5), pp. 385-396.
https://doi.org/10.15866/iree.v13i5.15520

Rozić, I., Imamović, B., Pavličević, J., Gubina, A., Halilčević, S., The Energy Sustainability of the Small Agricultural Farms Isolated of Electric Power Grid, (2018) International Review of Electrical Engineering (IREE), 13 (3), pp. 229-236.
https://doi.org/10.15866/iree.v13i3.14413

Menniti, D., Sorrentino, N., Pinnarelli, A., Brusco, G., Barone, G., Motta, M., Burgio, A., A Laboratory-Scale Prototype of a Smart User Network with DBS Control, (2017) International Review of Electrical Engineering (IREE), 12 (6), pp. 485-497.
https://doi.org/10.15866/iree.v12i6.12706
Afandi, A., Wibawa, A., Padmantara, S., Fujita, G., Triyana, W., Sulistyorini, Y., Miyauchi, H., Tutkun, N., EL-Shimy Mahmoud, M., Gao, X., Designed Operating Approach of Economic Dispatch for Java Bali Power Grid Areas Considered Wind Energy and Pollutant Emission Optimized Using Thunderstorm Algorithm Based on Forward Cloud Charge Mechanism, (2018) International Review of Electrical Engineering (IREE), 13 (1), pp. 59-68.
https://doi.org/10.15866/iree.v13i1.14687


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