Open Access Open Access  Restricted Access Subscription or Fee Access

Multi-Objective Optimization of Integrated Power System Expansion Planning with Renewable Energy-Based Distributed Generation


(*) Corresponding author


Authors' affiliations


DOI: https://doi.org/10.15866/iree.v14i1.16082

Abstract


Multi-objective-based power system expansion planning considering distributed generation is presented in this study. An integrated model of electrical power system expansion planning with renewable energy-based distributed generation is proposed. Two objective functions, cost and the emission objective function, are implemented in the proposed model. The cost function comprises investment cost and operation cost. The investment cost covers the cost of the new generation unit, the new distributed generation unit, and the investment for the new transmission circuit. The operation cost covers the operation cost of the installed and new generation unit and the operation cost of the installed and new distributed generation unit. Two emission gasses, CO2 and NOx, are considered in the proposed model. These two gasses are expressed in the same unit as Global Warming Potential.  The developed model is implemented into the IEEE 14 bus system. Lexicographic optimization combined with the epsilon constraint technique is used to solve the multi-objective problem. A Pareto optimal solution is generated by this method. Then, the fuzzy decision-making process is implemented to select the best solution from the Pareto set. The simulation results show that the distributed generation significantly reduces the overall cost of power system expansion planning. With a 30% DG penetration level, overall planning costs can be reduced by 12.62% compared to without DG penetration with an equal weighting factor for each objective function. Details of the capacity expansion of the generation unit, distributed generation unit, and transmission line are presented in this study.
Copyright © 2019 Praise Worthy Prize - All rights reserved.

Keywords


Multi-Objective; Generation Expansion; Transmission Expansion; Integrated Planning; Distributed Generation; Lexicographic Optimization; Epsilon Constraint

Full Text:

PDF


References


I. Sharan and R. Balasubramanian, Integrated generation and transmission expansion planning including power and fuel transportation constraints, Energy Policy, vol. 43, 2012, pp. 275–284.
https://doi.org/10.1016/j.enpol.2012.01.004

A. Khodaei, M. Shahidehpour, L. Wu, and Z. Li, Coordination of Short-Term Operation Constraints in Multi-Area Expansion Planning, IEEE Transactions on Power Systems, vol. 27, no. 4, Nov. 2012, pp. 2242–2250.
https://doi.org/10.1109/tpwrs.2012.2192507

Rios, M., Moreno Garzon, A., Integrated Generation and Transmission Planning with Intermittent Renewable Energy Sources in High-Level Hydroelectric Generation Systems, (2015) International Review of Electrical Engineering (IREE), 10 (3), pp. 404-413.
https://doi.org/10.15866/iree.v10i3.5983

CPardo, C., Rios, M., Inclusion of HVDC-Wind Generation in the Transmission Expansion Planning, (2017) International Review on Modelling and Simulations (IREMOS), 10 (2), pp. 103-111.
https://doi.org/10.15866/iremos.v10i2.11548

S. Surendra and D. Thukaram, Identification of prospective locations for generation expansion with least augmentation of network, Generation, Transmission Distribution, IET, vol. 7, no. 1, 2013, pp. 37–45.
https://doi.org/10.1049/iet-gtd.2012.0211

F. Luo, J. Zhao, J. Qiu, S. Member, and J. Foster, Assessing the Transmission Expansion Cost With Distributed Generation : An Australian Case Study, IEEE Transactions on Smart GRID, vol. 5, no. 4, 2014, pp. 1892–1904.
https://doi.org/10.1109/tsg.2014.2314451

J. H. Zhao, J. Foster, Z. Y. Dong, and K. P. Wong, Flexible transmission network planning considering distributed generation impacts, IEEE Transactions on Power Systems, vol. 26, no. 3, 2011, pp. 1434–1443.
https://doi.org/10.1109/tpwrs.2010.2089994

F. Careri, C. Genesi, P. Marannino, M. Montagna, S. Rossi, and I. Siviero, Generation expansion planning in the age of green economy, IEEE Transactions on Power Systems, vol. 26, no. 4, 2011, pp. 2214–2223.
https://doi.org/10.1109/tpwrs.2011.2107753

G. A. Bakirtzis, P. N. Biskas, and V. Chatziathanasiou, Generation expansion planning by MILP considering mid-term scheduling decisions, Electric Power Systems Research, vol. 86, 2012, pp. 98–112.
https://doi.org/10.1016/j.epsr.2011.12.008

C. Yuan et al., New Problem Formulation of Emission Constrained Generation Mix, IEEE Transactions on Power Systems, vol. 28, no. 4, 2013, pp. 4064–4071.
https://doi.org/10.1109/tpwrs.2013.2263230

K. Rajesh, A. Bhuvanesh, S. Kannan, and C. Thangaraj, Least cost generation expansion planning with solar power plant using Differential Evolution algorithm, Renewable Energy, vol. 85, 2016, pp. 677–686.
https://doi.org/10.1016/j.renene.2015.07.026

K. Rajesh, K. Karthikeyan, S. Kannan, and C. Thangaraj, Generation expansion planning based on solar plants with storage, Renewable and Sustainable Energy Reviews, vol. 57, 2016, pp. 953–964.
https://doi.org/10.1016/j.rser.2015.12.126

S. Tanatvanit, B. Limmeechokchai, and R. M. Shrestha, CO 2 mitigation and power generation implications of clean supply- side and demand-side technologies in Thailand, Energy Policy, vol. 32, 2004, pp. 83–90.
https://doi.org/10.1016/s0301-4215(02)00260-4

A. S. Malik, Impact on power planning due to demand-side management ( DSM ) in commercial and government sectors with rebound effect — A case study of central grid of Oman, Energy, vol. 32, 2007, pp. 2157–2166.
https://doi.org/10.1016/j.energy.2007.05.004

M. Paulus and F. Borggrefe, The potential of demand-side management in energy-intensive industries for electricity markets in Germanym Applied Energy, vol. 88, no. 2, 2011, pp. 432–441.
https://doi.org/10.1016/j.apenergy.2010.03.017

A. Pina, C. Silva, and P. Ferrão, The impact of demand side management strategies in the penetration of renewable electricity, Energy, vol. 41, no. 1, 2012, pp. 128–137.
https://doi.org/10.1016/j.energy.2011.06.013

A. H. Seddighi and A. Ahmadi-Javid, Integrated multiperiod power generation and transmission expansion planning with sustainability aspects in a stochastic environment, Energy, vol. 86, 2015, pp. 9–18.
https://doi.org/10.1016/j.energy.2015.02.047

A. Heidari, H. Mavalizadeh, and A. Ahmadi, Probabilistic multi-objective generation and transmission expansion planning problem using normal boundary intersection, IET Generation, Transmission & Distribution, vol. 9, no. 6, Apr. 2015, pp. 560–570.
https://doi.org/10.1049/iet-gtd.2014.0278

O. J. Guerra, D. A. Tejada, and G. V Reklaitis, An optimization framework for the integrated planning of generation and transmission expansion in interconnected power systems, Applied Energy, vol. 170, 2016, pp. 1–21.
https://doi.org/10.1016/j.apenergy.2016.02.014

A. Rouhani, S. H. Hosseini, and M. Raoofat, Composite generation and transmission expansion planning considering distributed generation, International Journal of Electrical Power & Energy Systems, vol. 62, 2014, pp. 792–805.
https://doi.org/10.1016/j.ijepes.2014.05.041

Al Hasibi, R., Hadi, S., Sarjiya, S., Integrated and Simultaneous Model of Power Expansion Planning with Distributed Generation, (2018) International Review of Electrical Engineering (IREE), 13 (2), pp. 116-127
https://doi.org/10.15866/iree.v13i2.14748

H. Tekiner, D. W. Coit, and F. A. Felder, Multi-period multi-objective electricity generation expansion planning problem with Monte-Carlo simulation, Electric Power Systems Research, vol. 80, no. 12, 2010, pp. 1394–1405.
https://doi.org/10.1016/j.epsr.2010.05.007

K. Promjiraprawat and B. Limmeechokchai, Multi-Objective and Multi-Criteria Optimization for Power Generation Expansion Planning with CO2 Mitigation in Thailand, Songklanakarin Journal of Sicence and Technology, vol. 35, no. 3, 2013, pp. 349–359.

A. Bagheri, V. Vahidinasab, and K. Mehran, A novel multiobjective generation and transmission investment framework for implementing 100% renewable energy sources, IET Generation, Transmission & Distribution, vol. 12, no. 2, 2018, pp. 455–465.
https://doi.org/10.1049/iet-gtd.2017.0976

G. Myhre et al., Anthropogenic and Natural Radiative Forcing, in Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, T. F. Stocker, D. Qin, G.-K. Plattner, M. Tignor, S. K. Allen, J. Boschung, A. Nauels, Y. Xia, V. Bex, and P. M. Midgley, Eds. , Cambridge, United Kingdom and New York, NY, USA: Cambridge University Press, 2013, pp. 659–740.
https://doi.org/10.1017/cbo9781107415324.018

J. Aghaei, N. Amjady, and H. A. Shayanfar, Multi-objective electricity market clearing considering dynamic security by lexicographic optimization and augmented epsilon constraint method, Applied Soft Computing Journal, vol. 11, no. 4, 2011, pp. 3846–3858.
https://doi.org/10.1016/j.asoc.2011.02.022

G. Mavrotas, Effective implementation of the ε-constraint method in Multi-Objective Mathematical Programming problems, Applied Mathematics and Computation, vol. 213, no. 2, 2009, pp. 455–465.
https://doi.org/10.1016/j.amc.2009.03.037

Reyes-Jordan, L., Rios, M., Load Shedding in Power Systems Based on a Fuzzy Logic Decision and Sensibility of Stability Prediction and Fast Voltage Indices, (2016) International Review of Electrical Engineering (IREE), 11 (5), pp. 496-505.
https://doi.org/10.15866/iree.v11i5.10137

P. Pujihatma, S. Pramono, and T. Agung, “Combined heat and power – multi-objective optimization with an associated petroleum and wet gas utilization constraint” Journal of Natural Gas Science and Engineering, vol. 54, no. February, 2018, pp. 25–36.
https://doi.org/10.1016/j.jngse.2018.03.025

NREL, Cost and Performance data for Power Generation Technologies, 2012.


Refbacks

  • There are currently no refbacks.


Please send any question about this web site to info@praiseworthyprize.com
Copyright © 2005-2024 Praise Worthy Prize