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Journal articles on the topic 'Expansion of power generation'

Author: Grafiati

Published: 4 June 2021

Last updated: 3 February 2022

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1

Shu, Jun, Lei Wu, Lizi Zhang, and Bing Han. "Spatial Power Network Expansion Planning Considering Generation Expansion." IEEE Transactions on Power Systems 30, no. 4 (July 2015): 1815–24. http://dx.doi.org/10.1109/tpwrs.2014.2358237.

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2

Basu, Mousumi. "Electric Power and Heat Generation Expansion Planning." Electric Power Components and Systems 48, no. 4-5 (March 15, 2020): 501–11. http://dx.doi.org/10.1080/15325008.2020.1793840.

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3

Sharan, Ishan, and R. Balasubramanian. "Generation Expansion Planning with High Penetration of Wind Power." International Journal of Emerging Electric Power Systems 17, no. 4 (August 1, 2016): 401–23. http://dx.doi.org/10.1515/ijeeps-2015-0186.

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Abstract Worldwide thrust is being provided in generation of electricity from wind. Planning for the developmental needs of wind based power has to be consistent with the objective and basic framework of overall resource planning. The operational issues associated with the integration of wind power must be addressed at the planning stage. Lack of co-ordinated planning of wind turbine generators, conventional generating units and expansion of the transmission system may lead to curtailment of wind power due to transmission inadequacy or operational constraints. This paper presents a generation expansion planning model taking into account fuel transportation and power transmission constraints, while addressing the operational issues associated with the high penetration of wind power. For analyzing the operational issues, security constrained unit commitment algorithm is embedded in the integrated generation and transmission expansion planning model. The integrated generation and transmission expansion planning problem has been formulated as a mixed integer linear problem involving both binary and continuous variables in GAMS. The model has been applied to the expansion planning of a real system to illustrate the proposed approach.

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4

Kim, Sunoh, and Jin Hur. "Probabilistic Approaches to the Security Analysis of Smart Grid with High Wind Penetration: The Case of Jeju Island’s Power Grids." Energies 13, no. 21 (November 4, 2020): 5785. http://dx.doi.org/10.3390/en13215785.

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As the importance of renewable generating resources has grown around the world, South Korea is also trying to expand the proportion of renewable generating resources in the power generation sector. Among the various renewable energy sources, wind generating resources are emerging as a key alternative to conventional power generations in the electricity sector in Korea accounted for 17.7 GW of total capacity by 2030. As wind generating resources are gradually replacing traditional generating resources, the system security and reliability are negatively affected because of the variability, due to intermittent outputs. Therefore, existing power grids will need to be correctly re-measured to cover the large scale of renewable energy, including wind generation. To expand the grid, we must understand the characteristics of renewable energy and the impact of its adoption in the grid. In this paper, we analyze various characteristics of wind power generation, and then we propose a probabilistic power output modeling method to consider the uncertainty of wind power generation. For the probabilistic approach, Monte-Carlo simulation is used in the modeling method. The modeled wind power outputs can help planning for the reinforcement and expansion of power systems to expand the capacity for large-scale renewable energy in the future. To verify the proposed method, some case studies were performed using empirical data, and probabilistic power flow calculation was performed by integrating large-scale wind power generation to the Jeju Island power system. The probabilistic method proposed in this paper can efficiently plan power system expansion and play a key strategy of evaluating the security of the power system through the results of stochastic power flow calculation.

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5

Kaymaz, Pinar, Jorge Valenzuela, and Chan S. Park. "Transmission Congestion and Competition on Power Generation Expansion." IEEE Transactions on Power Systems 22, no. 1 (February 2007): 156–63. http://dx.doi.org/10.1109/tpwrs.2006.887960.

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6

Tejada-Arango, Diego A., German Morales-Espana, Sonja Wogrin, and Efraim Centeno. "Power-Based Generation Expansion Planning for Flexibility Requirements." IEEE Transactions on Power Systems 35, no. 3 (May 2020): 2012–23. http://dx.doi.org/10.1109/tpwrs.2019.2940286.

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7

Kamalinia, S., and M. Shahidehpour. "Generation expansion planning in wind-thermal power systems." IET Generation, Transmission & Distribution 4, no. 8 (2010): 940. http://dx.doi.org/10.1049/iet-gtd.2009.0695.

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8

Quaddus, M. A., and T. N. Goh. "Electric power generation expansion: Planning with multiple objectives." Applied Energy 19, no. 4 (January 1985): 301–19. http://dx.doi.org/10.1016/0306-2619(85)90004-2.

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9

Aghaei, Jamshid, Mohammad Amin Akbari, Alireza Roosta, and Amir Baharvandi. "Multiobjective generation expansion planning considering power system adequacy." Electric Power Systems Research 102 (September 2013): 8–19. http://dx.doi.org/10.1016/j.epsr.2013.04.001.

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10

., G. Srinivasulu. "GLOBAL ISSUE BASED POWER GENERATION EXPANSION PLANNING FOR A POWER SYSTEM." International Journal of Research in Engineering and Technology 01, no. 01 (January 25, 2012): 7–12. http://dx.doi.org/10.15623/ijret.2012.0101002.

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11

Podkovalnikov, Sergei, and Lyudmila Chudinova. "Renewables Expansion in Northeast Asian Power Grid." E3S Web of Conferences 209 (2020): 04003. http://dx.doi.org/10.1051/e3sconf/202020904003.

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The paper considers effectiveness of a penetration of renewables into potential Northeast Asia power system interconnection. Renewables are currently in the mainstream of expansion of energy sector in the world and in Northeast Asia, particularly. Formation of NEA power interconnection will increase utilization of variable and poorly predictable renewable generation. Economic incentive for penetration of renewables, like CO2 emission tax, is studied. The study revealed that quite significant tax is needed to be imposed to induce non-fossil fuel generation capacities, including renewable ones, to be added to power systems.

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12

Karaki, Sami H., Farid B. Chaaban, Nicholas Al-Nakhl, and Khalil A. Tarhini. "Power generation expansion planning with environmental consideration for Lebanon." International Journal of Electrical Power & Energy Systems 24, no. 8 (October 2002): 611–19. http://dx.doi.org/10.1016/s0142-0615(01)00075-8.

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13

Fakehi, Amir Hossein, Somayeh Ahmadi, Mohammad Bagher Ghofrani, and Yadollah Saboohi. "A multi-regional model for power generation expansion planning." International Journal of Energy and Statistics 03, no. 01 (March 2015): 1550004. http://dx.doi.org/10.1142/s2335680415500040.

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14

Sevilgen, Süleyman Hakan, Hasan Hüseyin Erdem, Burhanettin Cetin, Ali Volkan Akkaya, and Ahmet Dagˇdaş. "Effect of economic parameters on power generation expansion planning." Energy Conversion and Management 46, no. 11-12 (July 2005): 1780–89. http://dx.doi.org/10.1016/j.enconman.2004.09.006.

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15

Wu, Shengyu, and Xufeng Song. "A Framework to Include Wind-Thermal Bundled Power Transmission Pattern in Multi-region Generation Expansion Planning Model." Journal of Clean Energy Technologies 5, no. 2 (2017): 159–62. http://dx.doi.org/10.18178/jocet.2017.5.2.362.

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16

Rouhani, Ahmad, Seyyed Hadi Hosseini, and Mahdi Raoofat. "Composite generation and transmission expansion planning considering distributed generation." International Journal of Electrical Power & Energy Systems 62 (November 2014): 792–805. http://dx.doi.org/10.1016/j.ijepes.2014.05.041.

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17

Oh, Inha, Wang-Jin Yoo, and Kihwan Kim. "Economic Effects of Renewable Energy Expansion Policy: Computable General Equilibrium Analysis for Korea." International Journal of Environmental Research and Public Health 17, no. 13 (July 2, 2020): 4762. http://dx.doi.org/10.3390/ijerph17134762.

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This study examines the effects of renewable energy expansion policy on the Korean economy and industries using the computable general equilibrium model, which divides the power generation sector into detailed generation technologies and sources. The scenarios are set to observe the cases where the share of solar photovoltaic and wind power generation reaches 7%. The effects are examined according to differing circumstances, such as when greenhouse gas (GHG) emissions are regulated, and the funding source for renewable expansion varies. The results show that renewable expansion policies have negative effects on GDP. However, the magnitude of the GDP decline becomes smaller when GHG emissions are regulated. The expansion of renewable energy induces the growth of upstream industries which supply components for renewable generation modules. Regarding employment, the renewable expansion policy can increase the demand for labor. However, the direction and the extent of the effect vary depending on the funding source. When overlapping regulations, such as the emission trading scheme and renewable energy expansion policies, exist in the power generation sector, the renewable energy expansion policy could provide incentives for GHG emission-intensive power sources.

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18

Bagdadee, Amam Hossain, and Li Zhang. "Electrical power crisis solution by the developing renewable energy based power generation expansion." Energy Reports 6 (February 2020): 480–90. http://dx.doi.org/10.1016/j.egyr.2019.11.106.

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19

Mavalizadeh, Hani, Abdollah Ahmadi, Foad Haidari Gandoman, Pierluigi Siano, and Heidar Ali Shayanfar. "Multiobjective Robust Power System Expansion Planning Considering Generation Units Retirement." IEEE Systems Journal 12, no. 3 (September 2018): 2664–75. http://dx.doi.org/10.1109/jsyst.2017.2672694.

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20

Meza, Jose L. Ceciliano, Mehmet Bayram Yildirim, and Abu S. M. Masud. "A Model for the Multiperiod Multiobjective Power Generation Expansion Problem." IEEE Transactions on Power Systems 22, no. 2 (May 2007): 871–78. http://dx.doi.org/10.1109/tpwrs.2007.895178.

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21

Canas-Carreton, Miguel, and Miguel Carrion. "Generation Capacity Expansion Considering Reserve Provision by Wind Power Units." IEEE Transactions on Power Systems 35, no. 6 (November 2020): 4564–73. http://dx.doi.org/10.1109/tpwrs.2020.2994173.

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22

Zou, Jikai, Shabbir Ahmed, and Xu Andy Sun. "Partially Adaptive Stochastic Optimization for Electric Power Generation Expansion Planning." INFORMS Journal on Computing 30, no. 2 (May 2018): 388–401. http://dx.doi.org/10.1287/ijoc.2017.0782.

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23

Javadi, Mohammad Sadegh. "Sustainable generation and transmission expansion planning in competitive power markets." Indian Journal of Science and Technology 5, no. 2 (February 20, 2012): 1–7. http://dx.doi.org/10.17485/ijst/2012/v5i2.3.

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24

Yildirim, Mehmet, Kadir Erkan, and Semra Ozturk. "Power generation expansion planning with adaptive simulated annealing genetic algorithm." International Journal of Energy Research 30, no. 14 (2006): 1188–99. http://dx.doi.org/10.1002/er.1214.

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25

Yuan, Bo, Jin Zong, and Shengyu Wu. "Capacity expansion model of wind power generation based on ELCC." IOP Conference Series: Earth and Environmental Science 121 (February 2018): 042020. http://dx.doi.org/10.1088/1755-1315/121/4/042020.

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26

de Paula, A. N., E. J. de Oliveira, L. W. Oliveira, and C. A. Moraes. "Reliability-constrained dynamic transmission expansion planning considering wind power generation." Electrical Engineering 102, no. 4 (July 3, 2020): 2583–93. http://dx.doi.org/10.1007/s00202-020-01054-y.

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27

Aliyu, Abubakar Sadiq, Ahmad Termizi Ramli, and Muneer Aziz Saleh. "Nigeria electricity crisis: Power generation capacity expansion and environmental ramifications." Energy 61 (November 2013): 354–67. http://dx.doi.org/10.1016/j.energy.2013.09.011.

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28

Dong, Zhen, Zhongguo Li, Zhongchao Liang, Yiqiao Xu, and Zhengtao Ding. "Distributed neural network enhanced power generation strategy of large-scale wind power plant for power expansion." Applied Energy 303 (December 2021): 117622. http://dx.doi.org/10.1016/j.apenergy.2021.117622.

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29

Deossa, P., K. De Vos, G. Deconinck, and J. Espinosa. "Generation Expansion Models including Technical Constraints and Demand Uncertainty." Journal of Applied Mathematics 2017 (2017): 1–11. http://dx.doi.org/10.1155/2017/3424129.

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This article presents a Generation Expansion Model of the power system taking into account the operational constraints and the uncertainty of long-term electricity demand projections. The model is based on a discretization of the load duration curve and explicitly considers that power plant ramping capabilities must meet demand variations. A model predictive control method is used to improve the long-term planning decisions while considering the uncertainty of demand projections. The model presented in this paper allows integrating technical constraints and uncertainty in the simulations, improving the accuracy of the results, while maintaining feasible computational time. Results are tested over three scenarios based on load data of an energy retailer in Colombia.

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30

Mahyuddin, Astuty. "MULTI-OBJECTIVE OPTIMIZATION OF POWER GENERATION EXPANSION IN WEST AND SOUTH SULAWESI POWER SYSTEM." Patria Artha Technological Journal 1, no. 1 (April 8, 2017): 1–8. http://dx.doi.org/10.33857/patj.v1i1.31.

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31

Abass, Samir, and Eman Massoud. "A fuzzy approach to the generation expansion planning problem in a multi-objective environment." Nuclear Technology and Radiation Protection 22, no. 1 (2007): 67–72. http://dx.doi.org/10.2298/ntrp0701067a.

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In many power system problems, the use of optimization techniques has proved inductive to reducing the costs and losses of the system. A fuzzy multi-objective decision is used for solving power system problems. One of the most important issues in the field of power system engineering is the generation expansion planning problem. In this paper, we use the concepts of membership functions to define a fuzzy decision model for generating an optimal solution for this problem. Solutions obtained by the fuzzy decision theory are always efficient and constitute the best compromise. .

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32

Borzea, Claudia, Iulian Vlăducă, Dan Ionescu, Valentin Petrescu, Filip Niculescu, Cristian Nechifor, Gabriel Vătăşelu, and Mihai Hanek. "Compressed Air Energy Storage Installation for Renewable Energy Generation." E3S Web of Conferences 112 (2019): 02010. http://dx.doi.org/10.1051/e3sconf/201911202010.

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Compressed Air Energy Storage (CAES) installations are used for storing electrical power, under the form of potential energy from compressed air. The heat generated during compression can be stored to improve the efficiency of compression-expansion cycle. The solution presented consists of a 100 kW screw compressor driven by a 110 kW asynchronous three-phase motor. The compressor supplies air into vessels which store it until a high electrical energy demand arises. At that time, the compressed air is released into a 132 kW screw expander whose shaft spins a 132 kW asynchronous generator, producing electric power and supplying it into the electrical grid. Before expansion, the air must be preheated in order to avoid the freezing of expansion equipment. If the heat generated during compression is used for air preheating before expansion, the process is adiabatic. A demonstrative model of the installation is currently being developed, with the expander part being completed so far. The maximum power to be produced was calculated to be around 100 kW. During expander commissioning tests with air supply from a 250 kW high pressure compressor, a maximum generated power of 49.7 kW was attained, expected to be higher when releasing air from the reservoirs.

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33

Kumar, Maneesh, and Raminder Kaur. "An Analytical Approach For Transmission Expansion Planning with Generation Variations." Transactions on Environment and Electrical Engineering 2, no. 2 (September 8, 2017): 72. http://dx.doi.org/10.22149/teee.v2i2.111.

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Planning for expanding a power system under different scenarios is one of the major challenge for power engineers hence, it is very important and essential to implement a well-balanced and feasible system over a time horizon under suitable assumptions and available constraints. Transmission expansion planning is one of this task. Here it is important to develop a suitable planning structure. In this paper some analytical approaches have been implemented for specific load condition with variations in generation.

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34

Yoo, Bok-Jong, Chan-Bae Park, and Ju Lee. "Comparative Study to Predict Power Generation using Meteorological Information for Expansion of Photovoltaic Power Generation System for Railway Infrastructure." Journal of the Korean Society for Railway 20, no. 4 (August 31, 2017): 474–81. http://dx.doi.org/10.7782/jksr.2017.20.4.474.

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35

Al Hasibi, Rahmat Adiprasetya, Sasongko Pramono Hadi, and Sarjiya Sarjiya. "Integrated and Simultaneous Model of Power Expansion Planning with Distributed Generation." International Review of Electrical Engineering (IREE) 13, no. 2 (April 30, 2018): 116. http://dx.doi.org/10.15866/iree.v13i2.14748.

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36

Luz, Thiago, Pedro Moura, and Aníbal de Almeida. "Multi-objective power generation expansion planning with high penetration of renewables." Renewable and Sustainable Energy Reviews 81 (January 2018): 2637–43. http://dx.doi.org/10.1016/j.rser.2017.06.069.

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37

Chen, Siyuan, Pei Liu, and Zheng Li. "Multi-regional power generation expansion planning with air pollutants emission constraints." Renewable and Sustainable Energy Reviews 112 (September 2019): 382–94. http://dx.doi.org/10.1016/j.rser.2019.05.062.

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38

Aïd, René, Liangchen Li, and Michael Ludkovski. "Capacity expansion games with application to competition in power generation investments." Journal of Economic Dynamics and Control 84 (November 2017): 1–31. http://dx.doi.org/10.1016/j.jedc.2017.08.002.

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39

Han, Shifen. "An Improved Chaos Quantum Immune Algorithm for Power Generation Expansion Planning." Journal of Physics: Conference Series 1624 (October 2020): 042025. http://dx.doi.org/10.1088/1742-6596/1624/4/042025.

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40

Clímaco, João, C. Henggeler Antunes, A. Gomes Martins, and A. Traça Almeida. "A multiple objective linear programming model for power generation expansion planning." International Journal of Energy Research 19, no. 5 (July 1995): 419–32. http://dx.doi.org/10.1002/er.4440190507.

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41

Gampala, Kiran, Linet Özdamar, and Shaligram Pokharel. "Investment Model for Power Generation and Transmission Network Expansion in Turkey." Journal of Energy Engineering 131, no. 2 (August 2005): 118–38. http://dx.doi.org/10.1061/(asce)0733-9402(2005)131:2(118).

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42

Moghaddas Tafreshi, S. M., A. Saliminia Lahiji, J. Aghaei, and A. Rabiee. "Reliable generation expansion planning in pool market considering power system security." Energy Conversion and Management 54, no. 1 (February 2012): 162–68. http://dx.doi.org/10.1016/j.enconman.2011.10.008.

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43

de Paula, Arthur N., Edimar J. de Oliveira, Leonardo W. de Oliveira, and Leonardo M. Honório. "Robust Static Transmission Expansion Planning Considering Contingency and Wind Power Generation." Journal of Control, Automation and Electrical Systems 31, no. 2 (January 3, 2020): 461–70. http://dx.doi.org/10.1007/s40313-019-00556-w.

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44

Feng, Yonghan, and Sarah M. Ryan. "Scenario construction and reduction applied to stochastic power generation expansion planning." Computers & Operations Research 40, no. 1 (January 2013): 9–23. http://dx.doi.org/10.1016/j.cor.2012.05.005.

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45

Pineda, Salvador, and Juan M. Morales. "Capacity expansion of stochastic power generation under two-stage electricity markets." Computers & Operations Research 70 (June 2016): 101–14. http://dx.doi.org/10.1016/j.cor.2015.12.007.

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46

Wang, Hanyun, Tao Wang, Xinyi Wang, Bing Li, and Congmin Ye. "A Stochastic Rolling Horizon-Based Approach for Power Generation Expansion Planning." Mathematical Problems in Engineering 2021 (June 29, 2021): 1–11. http://dx.doi.org/10.1155/2021/6635829.

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Variable renewable energy sources introduce significant amounts of short-term uncertainty that should be considered when making investment decisions. In this work, we present a method for representing stochastic power system operation in day-ahead and real-time electricity markets within a capacity expansion model. We use Benders’ cuts and a stochastic rolling-horizon dispatch to represent operational costs in the capacity expansion problem (CEP) and investigate different formulations for the cuts. We test the model on a two-bus case study with wind power, energy storage, and a constrained transmission line. The case study shows that cuts created from the day-ahead problem gives the lowest expected total cost for the stochastic CEP. The stochastic CEP results in 3% lower expected total cost compared to the deterministic CEP capacities evaluated under uncertain operation. The number of required stochastic iterations is efficiently reduced by introducing a deterministic lower bound, while extending the horizon of the operational problem by persistence forecasting leads to reduced operational costs.

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47

Dalabeeh, Ali S., Anwar Almofleh, Abdallah R. Alzyoud, and Hindi T. Ayman. "Economical and Reliable Expansion Alternative of Composite Power System under Restructuring." International Journal of Electrical and Computer Engineering (IJECE) 8, no. 6 (December 1, 2018): 4790. http://dx.doi.org/10.11591/ijece.v8i6.pp4790-4799.

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The paper intends to select the most economical and reliable expansion alternative of a composite power system to meet the expected future load growth. In order to reduce time computational quantity, a heuristic algorithm is adopted for composite power system reliability evaluation is proposed. The proposed algorithm is based on Monte-Carlo simulation method. The reliability indices are estimated for system base case and for the case of adding peaking generation units. The least cost reserve margin for the addition of five 20MW generating units sequentially is determined. Using the proposed algorithm an increment comparison approach used to illustrate the effect of the added units on the interruption and on the annual net gain costs. A flow chart introduced to explain the basic methodology to have an adequate assessment of a power system using Monte Carlo Simulation. The IEEE RTS (24-bus, 38-line) and The Jordanian Electrical Power System (46-bus and 92-line) were examined to illustrate how to make decisions in power system planning and expansions.

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48

Conde-López, Luis, Guillermo Gutiérrez-Alcaraz, and S. N. Singh. "Generating adequacy analysis of Mexico’s national interconnected power system." International Journal of Energy Sector Management 10, no. 4 (November 7, 2016): 561–75. http://dx.doi.org/10.1108/ijesm-11-2014-0003.

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Purpose Long-term reliability analysis of generation capacity based on the forecasted load demand helps to identify the optimal generation expansion plan of the system. This paper analyzes the generation adequacy of Mexico’s National Interconnected Power System (MNIPS) using loss of load expectation (LOLE) and loss of energy expectation (LOEE) indices. Design/methodology/approach These indices are calculated through an analytical (recursive) method and are then compared with values recommended by the North American Electric Reliability Council (NERC). Weekly indices are computed to analyze the load curtailment options that may occur in some periods. Findings Forecasted values, including load and generation capacity considering maintenance schedules, additions of new generating units and permanently shut down units in accordance with the long-term expanding-system plan have been considered. The load forecast uncertainty is also included. Originality/value This is original work.

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49

Pourahmadi, Farzaneh, Jalal Kazempour, Christos Ordoudis, Pierre Pinson, and Seyed Hamid Hosseini. "Distributionally Robust Chance-Constrained Generation Expansion Planning." IEEE Transactions on Power Systems 35, no. 4 (July 2020): 2888–903. http://dx.doi.org/10.1109/tpwrs.2019.2958850.

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50

Ahmed, N. U., and Q. Ahsan. "A dynamic model for generation expansion planning." Electric Power Systems Research 9, no. 1 (June 1985): 79–86. http://dx.doi.org/10.1016/0378-7796(85)90057-4.

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