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Journal articles on the topic 'Unit commitment/Economic dispatch'

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Published: 4 June 2021

Last updated: 13 February 2022

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1

Mohamed-Nor, Khalid, and Abdul Halim Abdul Rashid. "Efficient economic dispatch algorithm for thermal unit commitment." IEE Proceedings C Generation, Transmission and Distribution 138, no. 3 (1991): 213. http://dx.doi.org/10.1049/ip-c.1991.0025.

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2

Ouyang, Z., and S. M. Shahidehpour. "Heuristic multi-area unit commitment with economic dispatch." IEE Proceedings C Generation, Transmission and Distribution 138, no. 3 (1991): 242. http://dx.doi.org/10.1049/ip-c.1991.0030.

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3

Chen, C. L., and S. L. Che. "Short-term unit commitment with simplified economic dispatch." Electric Power Systems Research 21, no. 2 (1991): 115–20. http://dx.doi.org/10.1016/0378-7796(91)90025-i.

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4

Anyaka, Boniface O., J. Felix Manirakiza, Kenneth C. Chike, and Prince A. Okoro. "Optimal unit commitment of a power plant using particle swarm optimization approach." International Journal of Electrical and Computer Engineering (IJECE) 10, no. 2 (2020): 1135. http://dx.doi.org/10.11591/ijece.v10i2.pp1135-1141.

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Economic load dispatch among generating units is very important for any power plant. In this work, the economic load dispatch was made at Egbin Thermal Power plant supplying a total load of 600MW using six generating units. In carrying out this study, transmission losses were assumed to be included into the load supplied. Also three different combinations in the form of 6, 5 and 4 units commitment were considered. In each case, the total load was optimally dispatched between committed generating units using Particle Swarm Optimization (PSO). Similarly, the generation cost for each generating u

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5

Walsh, M. P., and M. J. O'Malley. "Augmented Hopfield network for unit commitment and economic dispatch." IEEE Transactions on Power Systems 12, no. 4 (1997): 1765–74. http://dx.doi.org/10.1109/59.627889.

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6

Cho, Youngchae, Takayuki Ishizaki, Nacim Ramdani, and Jun-ichi Imura. "Economic Dispatch Cost Reduction in Box-based Robust Unit Commitment." IFAC-PapersOnLine 53, no. 2 (2020): 13248–53. http://dx.doi.org/10.1016/j.ifacol.2020.12.153.

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7

Xie, Min, Yuxin Du, Peijun Cheng, Wei Wei, and Mingbo Liu. "A Cross-Entropy-Based Hybrid Membrane Computing Method for Power System Unit Commitment Problems." Energies 12, no. 3 (2019): 486. http://dx.doi.org/10.3390/en12030486.

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The cross-entropy based hybrid membrane computing method is proposed in this paper to solve the power system unit commitment problem. The traditional unit commitment problem can be usually decomposed into a bi-level optimization problem including unit start-stop scheduling problem and dynamic economic dispatch problem. In this paper, the genetic algorithm-based P system is proposed to schedule the unit start-stop plan, and the biomimetic membrane computing method combined with the cross-entropy is proposed to solve the dynamic economic dispatch problem with a unit start-stop plan given. The si

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8

Khunkitti, Sirote, Neville R. Watson, Rongrit Chatthaworn, Suttichai Premrudeepreechacharn, and Apirat Siritaratiwat. "An Improved DA-PSO Optimization Approach for Unit Commitment Problem." Energies 12, no. 12 (2019): 2335. http://dx.doi.org/10.3390/en12122335.

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Solving the Unit Commitment problem is an important step in optimally dispatching the available generation and involves two stages—deciding which generators to commit, and then deciding their power output (economic dispatch). The Unit Commitment problem is a mixed-integer combinational optimization problem that traditional optimization techniques struggle to solve, and metaheuristic techniques are better suited. Dragonfly algorithm (DA) and particle swarm optimization (PSO) are two such metaheuristic techniques, and recently a hybrid (DA-PSO), to make use of the best features of both, has been

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9

Prashar, Sushil, Vikram Kumar Kamboj, and Kultaar Deep Singh. "A Cost Effective Solution to Security Constrained Unit Commitment and Dispatch Problem using Hybrid Search Algorithm." E3S Web of Conferences 184 (2020): 01071. http://dx.doi.org/10.1051/e3sconf/202018401071.

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The Security constraints unit commitment (SCUC) is a powerful scheduling technique used in power markets for daily planning. SCUC is a framework that combines two common algorithms in the electricity industry: Unit Commitment (UC) and Economic Dispatch (ED), while adding a new dimension – Security. Load demand is changing continuously due to variation of load of industrial, residential and commercial sectors. Thus, it is very important to decide which generating unit should be kept on and how much power should be dispatched so that time varying load demand can be meet on Hourly basis and there

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10

Wang, C., and S. M. Shahidehpour. "Effects of ramp-rate limits on unit commitment and economic dispatch." IEEE Transactions on Power Systems 8, no. 3 (1993): 1341–50. http://dx.doi.org/10.1109/59.260859.

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11

HABACHI, Rachid, Achraf Touil, Abdellah Boulal, Abdelkabir Charkaoui, and Abdelwahed Echchatbi. "Solving economic dispatch and unit commitment problem in smart grid system using eagle strategy based crow search algorithm." Indonesian Journal of Electrical Engineering and Computer Science 14, no. 3 (2019): 1087. http://dx.doi.org/10.11591/ijeecs.v14.i3.pp1087-1096.

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<p><span lang="EN-US">The economic dispatch problem of power plays a very important role in the exploitation of electro-energy systems to judiciously distribute power generated by all plants. The Unit commitment problem (UCP) is mainly finding the minimum cost schedule to a set of generators by turning each one either on or off over a given time horizon to meet the demand load and satisfy different operational constraints. This research article integrates the crow search algorithm as a local optimizer of Eagle strategy to solve economic dispatch and unit commitment problem in smart

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12

Hassan, Zeinab G., M. Ezzat, and Almoataz Y. Abdelaziz. "Solving unit commitment and economic load dispatch problems using modern optimization algorithms." International Journal of Engineering, Science and Technology 9, no. 4 (2017): 10. http://dx.doi.org/10.4314/ijest.v9i4.2.

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13

Kasangaki, V. B. A., H. M. Sendaula, and S. K. Biswas. "Stochastic Hopfield artificial neural network for unit commitment and economic power dispatch." Electric Power Systems Research 42, no. 3 (1997): 215–23. http://dx.doi.org/10.1016/s0378-7796(96)01210-2.

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14

OLIVEIRA, P., S. MCKEE, and C. COLES. "Lagrangian relaxation and its application to the unit-commitment-economic-dispatch problem." IMA Journal of Management Mathematics 4, no. 3 (1992): 261–72. http://dx.doi.org/10.1093/imaman/4.3.261.

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15

Ponciroli, Roberto, Nicolas E. Stauff, Jackson Ramsey, Francesco Ganda, and Richard B. Vilim. "An Improved Genetic Algorithm Approach to the Unit Commitment/Economic Dispatch Problem." IEEE Transactions on Power Systems 35, no. 5 (2020): 4005–13. http://dx.doi.org/10.1109/tpwrs.2020.2986710.

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16

Tehzeeb-ul-Hassan, H., and Ayaz Ahmad. "Profit based unit commitment and economic dispatch of IPPs with new technique." International Journal of Electrical Power & Energy Systems 44, no. 1 (2013): 880–88. http://dx.doi.org/10.1016/j.ijepes.2012.08.039.

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17

Kamboj, Vikram Kumar, and S. K. Bath. "Scope of Biogeography Based Optimization for Economic Load Dispatch and Multi-Objective Unit Commitment Problem." International Journal of Energy Optimization and Engineering 3, no. 4 (2014): 34–54. http://dx.doi.org/10.4018/ijeoe.2014100103.

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Biogeography Based Optimization (BBO) algorithm is a population-based algorithm based on biogeography concept, which uses the idea of the migration strategy of animals or other spices for solving optimization problems. Biogeography Based Optimization algorithm has a simple procedure to find the optimal solution for the non-smooth and non-convex problems through the steps of migration and mutation. This research paper presents the solution to Economic Load Dispatch Problem for IEEE 3, 4, 6 and 10-unit generating model using Biogeography Based Optimization algorithm. It also presents the mathema

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18

Habachi, Rachid, Achraf Touil, Abdellah Boulal, Abdelkabir Charkaoui, and Abdelwahed Echchatbi. "Comparative study of metaheuristics methods applied to smart grid network in Morocco." International Journal of Power Electronics and Drive Systems (IJPEDS) 11, no. 1 (2020): 487. http://dx.doi.org/10.11591/ijpeds.v11.i1.pp487-495.

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The economic dispatch problem of power plays a very important role in the exploitation of electro-energy systems to judiciously distribute power generated by all plants. The Unit commitment problem (UCP) is mainly finding the minimum cost schedule to a set of generators by turning each one either on or off over a given time horizon to meet the demand load and satisfy different operational constraints, This research article integrates the crow search algorithm (CSA) as a local optimizer of Eagle strategy (ES) to solve economic dispatch and unit commitment problem in smart grid system of two ele

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19

Nguyen, Khai Phuc, Dieu Ngoc Vo, and Tu Phan Vu. "AUGMENTED LAGRANGE HOPFIELD NEURAL NETWORK BASED METHOD FOR UNIT COMMITMENT." Science and Technology Development Journal 15, no. 2 (2012): 39–49. http://dx.doi.org/10.32508/stdj.v15i2.1789.

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This paper proposed an enhanced merit order (EMO) and augmented Lagrange Hopfield neural network (ALHN) for solving unit commitment problem. This problem is solved on 2 stages. At first, with the heuristic search EMO method we plan the unit scheduling. And then, we use ALHN, a continuous Hopfield neural network combines with augmented Lagrange relaxation, to solve the economic dispatch problem. The proposed method is tested on systems with 10 units, 17 units and up to 100 units. The obtained results is compared to conventional priority list (PL-ALHN) and other methods in literature. Test resul

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20

Abdulaziz Alshareef, Abdulaziz Alshareef. "https://www.kau.edu.sa/Files/320/Researches/61836_32803.pdf." journal of King Abdulaziz University Engineering Sciences 23, no. 1 (2012): 21–37. http://dx.doi.org/10.4197/eng.23-1.2.

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Unit commitment (UC) in power systems typically involves properly scheduling the on/off states as well as the real power outputs (economic dispatch) of all resources (generators/units) in the system. In addition to fulfill a large number of system constraints, the UC meets forecasted load demand calculated in advance, plus the spinning reserve requirement at each time interval, such that the total cost (mainly fuel cost) is minimum. In this paper particle swarm optimization (PSO) is applied to minimize cost, emission or costemission of the Unit Commitment problem. For unit commitment both cost

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21

Ankaliki, Shekhappa G., A. D. Kulkarni, and Sujata I. Katti. "Particle Swarm Optimization (PSO) Technique for Unit Commitment and Economic Dispatch Problem Solution." i-manager's Journal on Information Technology 2, no. 2 (2013): 8–16. http://dx.doi.org/10.26634/jit.2.2.2284.

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22

Zhang, Yachao, Kaipei Liu, Xiaobing Liao, Liang Qin, and Xueli An. "Stochastic dynamic economic emission dispatch with unit commitment problem considering wind power integration." International Transactions on Electrical Energy Systems 28, no. 1 (2017): e2472. http://dx.doi.org/10.1002/etep.2472.

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23

Wang, C., and S. M. Shahidehpour. "Ramp-rate limits in unit commitment and economic dispatch incorporating rotor fatigue effect." IEEE Transactions on Power Systems 9, no. 3 (1994): 1539–45. http://dx.doi.org/10.1109/59.336106.

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24

Tuffaha, Mutaz, and Jan Tommy Gravdahl. "Discrete state-space model to solve the unit commitment and economic dispatch problems." Energy Systems 8, no. 3 (2016): 525–47. http://dx.doi.org/10.1007/s12667-016-0212-x.

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25

SIDDIQUE, Nazmul, and Hojjat ADELI. "APPLICATIONS OF GRAVITATIONAL SEARCH ALGORITHM IN ENGINEERING." JOURNAL OF CIVIL ENGINEERING AND MANAGEMENT 22, no. 8 (2016): 981–90. http://dx.doi.org/10.3846/13923730.2016.1232306.

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Gravitational search algorithm (GSA) is a nature-inspired conceptual framework with roots in gravitational kinematics, a branch of physics that models the motion of masses moving under the influence of gravity. In a recent article the authors reviewed the principles of GSA. This article presents a review of applications of GSA in engineering including combinatorial optimization problems, economic load dispatch problem, economic and emission dispatch problem, optimal power flow problem, optimal reactive power dispatch problem, energy management system problem, clustering and classification prob

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26

Botterud, Audun, Zhi Zhou, Jianhui Wang, et al. "Demand Dispatch and Probabilistic Wind Power Forecasting in Unit Commitment and Economic Dispatch: A Case Study of Illinois." IEEE Transactions on Sustainable Energy 4, no. 1 (2013): 250–61. http://dx.doi.org/10.1109/tste.2012.2215631.

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27

Pluta, Marcin, Artur Wyrwa, Wojciech Suwała, Janusz Zyśk, Maciej Raczyński, and Stanisław Tokarski. "A Generalized Unit Commitment and Economic Dispatch Approach for Analysing the Polish Power System under High Renewable Penetration." Energies 13, no. 8 (2020): 1952. http://dx.doi.org/10.3390/en13081952.

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The achievement of carbon neutrality requires a deep transformation of the Polish power sector. This paper analyses the impact of increased electricity generation from wind and solar technologies envisaged in the newest version of the Energy Policy of Poland until 2040 on the operation of dispatchable generators in 2030. The analysis was carried out using the Model of Economic Dispatch and Unit commitment for System Analysis (MEDUSA) model, which solves a mixed integer problem related to unit commitment and economic dispatch in electrical power production. At first, the model was validated bas

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28

Surekha, P., N. Archana, and S. Sumathi. "An Integrated GA-ABC Optimization Technique to Solve Unit Commitment and Economic Dispatch Problems." Asian Journal of Scientific Research 5, no. 3 (2012): 93–107. http://dx.doi.org/10.3923/ajsr.2012.93.107.

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29

SUROSO, HADI, and ONTOSENO PENANGSANG. "AN OPTIMISATION APPROACH TOWARD ONBOARD ENERGY MANAGEMENT SYSTEMS: MODELLING AND SIMULATION OF SUPPLY SIDE." Jurnal Teknik Industri 11, no. 1 (2012): 1. http://dx.doi.org/10.22219/jtiumm.vol11.no1.1-5.

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Optimization in the operation of electric power system is an important task for both inland and onboard. The objective is to minimize operating cost index. Taking advantage of thescheme that onboard operator has the authority not only in the supply side but also in the demandside, an optimization approach toward onboard energy management systems based onintegrated model for supply and demand side is being developed. The model utilizes unit commitmentand economic dispatch in the supply side and load management based on multipleattribute decision-making in the demand side. As a part of the whole

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30

Nepal, Nahakul, and Rajesh Karki. "Quantifying Power System Operational Reliability." Applied Sciences 9, no. 14 (2019): 2777. http://dx.doi.org/10.3390/app9142777.

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Rising uncertainty in power systems due to ongoing system and operational changes has led to increasing risks in operating a system in a reliable and economic manner. There are growing reliability concerns with the widely used methods, such as the N-1 criterion, to determine operating reserve requirement during unit commitment, and the economic load dispatch method to allocate regulating margin to respond to disturbances. These deterministic methods do not consider the uncertainty or stochastic nature of power systems and are often inadequate to maintain the required operating reliability of m

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31

Psarros, Georgios, and Stavros Papathanassiou. "Comparative Assessment of Priority Listing and Mixed Integer Linear Programming Unit Commitment Methods for Non-Interconnected Island Systems." Energies 12, no. 4 (2019): 657. http://dx.doi.org/10.3390/en12040657.

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The generation management concept for non-interconnected island (NII) systems is traditionally based on simple, semi-empirical operating rules dating back to the era before the massive deployment of renewable energy sources (RES), which do not achieve maximum RES penetration, optimal dispatch of thermal units and satisfaction of system security criteria. Nowadays, more advanced unit commitment (UC) and economic-dispatch (ED) approaches based on optimization techniques are gradually introduced to safeguard system operation against severe disturbances, to prioritize RES participation and to opti

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32

Sreejith, Sekharan, and Sishaj P. Simon. "Security Constrained Unit Commitment Incorporating Interline Power Flow Controller." Periodica Polytechnica Electrical Engineering and Computer Science 61, no. 1 (2017): 22. http://dx.doi.org/10.3311/ppee.9460.

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Security-constrained unit commitment (SCUC) problem is solved using Artificial Bee Colony (ABC) algorithm incorporating Interline Power Flow Controller (IPFC). The objective of the SCUC problem is to obtain the minimum operating cost simultaneously maintaining the system security. The SCUC problem involves unit commitment as the main problem and security-constrained Economic Dispatch (SCED) as the sub problem. The solution of the SCUC problem is also investigated during contingency with a single line outage. Binary coded artificial bee colony (BABC) is used for solving the UC problem (master p

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33

Xia, Qing, Y. H. Song, Boming Zhang, Chongqing Kang, and Niande Xiang. "Effective decomposition and co-ordination algorithms for unit commitment and economic dispatch with security constraints." Electric Power Systems Research 53, no. 1 (2000): 39–45. http://dx.doi.org/10.1016/s0378-7796(99)00035-8.

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34

ZHANG, Yachao, Kaipei LIU, Xiaobing LIAO, Liang QIN, and Xueli AN. "A probabilistic scenario-based framework for solving stochastic dynamic economic emission dispatch with unit commitment." TURKISH JOURNAL OF ELECTRICAL ENGINEERING & COMPUTER SCIENCES 25 (2017): 4805–17. http://dx.doi.org/10.3906/elk-1705-92.

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35

Cho, Youngchae, Takayuki Ishizaki, Nacim Ramdani, and Jun-ichi Imura. "Box-Based Temporal Decomposition of Multi-Period Economic Dispatch for Two-Stage Robust Unit Commitment." IEEE Transactions on Power Systems 34, no. 4 (2019): 3109–18. http://dx.doi.org/10.1109/tpwrs.2019.2896349.

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36

Guo, Sangang. "Novel methods for Solving Economic Dispatch of Security-Constrained Unit Commitment Based on Linear Programming." IOP Conference Series: Materials Science and Engineering 231 (September 2017): 012066. http://dx.doi.org/10.1088/1757-899x/231/1/012066.

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37

Kumar, S. Senthil, and V. Palanisamy. "A dynamic programming based fast computation Hopfield neural network for unit commitment and economic dispatch." Electric Power Systems Research 77, no. 8 (2007): 917–25. http://dx.doi.org/10.1016/j.epsr.2006.08.005.

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38

Alvarez, Gonzalo E. "Solving the Unit Commitment and Economic Dispatch Problems by Applying a Novel Weighted Decomposition Method." Computers & Chemical Engineering 150 (July 2021): 107337. http://dx.doi.org/10.1016/j.compchemeng.2021.107337.

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39

C, Christopher Columbus, and Sishaj P. Simon. "Parallel hybrid enhanced inherited GA based scuc in a distributed cluster." Artificial Intelligence Research 1, no. 1 (2012): 96. http://dx.doi.org/10.5430/air.v1n1p96.

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In the deregulated electricity market, secure operation is an enduring concern of the independent system operator (ISO). For a secure and economical hourly generation schedule of the day ahead market, ISO executes the security constrained unit commitment (SCUC) problem. In this paper, a new formulation of SCUC problem, considering more practical constraints are presented. The proposed SCUC formulation includes constraints, such as hourly power demand, system reserves, ramp up/down limits, minimum ON/OFF duration limits. Unlike the traditional SCUC techniques the proposed method solves the Secu

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40

Moreno, Ricardo, Johan Obando, and Gabriel Gonzalez. "An integrated OPF dispatching model with wind power and demand response for day-ahead markets." International Journal of Electrical and Computer Engineering (IJECE) 9, no. 4 (2019): 2794. http://dx.doi.org/10.11591/ijece.v9i4.pp2794-2802.

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In the day-ahead dispatching of network-constrained electricity markets, renewable energy and distributed resources are dispatched together with conventional generation. The uncertainty and volatility associated to renewable resources represents a new paradigm to be faced for power system operation. Moreover, in various electricity markets there are mechanisms to allow the demand participation through demand response (DR) strategies. Under operational and economic restrictions, the operator each day, or even in intra-day markets, dispatchs an optimal power flow to find a feasible state of oper

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41

Shao, Jian, Bu Han Zhang, Wei Si Deng, Kai Min Zhang, Bing Jie Jin, and Teng Yu Ge. "A Stochastic Programming Method for Unit Commitment of Wind Integrated Power System." Advanced Materials Research 732-733 (August 2013): 1390–95. http://dx.doi.org/10.4028/www.scientific.net/amr.732-733.1390.

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This paper presents a stochastic programming method that can assess the impact of wind generation uncertainties on unit comment (UC) problem. To model the uncertainty of wind genration, scenarios of wind speed are generated based on the known probability interval of forecasted wind speed and a scenario reduction technique limits the number of scenarios. The UC problem is modeled as a stochastic programming problem based on chance-constrained programming, and is decomposed into two embedded optimization sub-problems: the unit on/off status schedule problem and the load economic dispatch problem

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42

Chandrasekaran, K., and Sishaj P. Simon. "Wind-Thermal Integrated Power System Scheduling Problem Using Cuckoo Search Algorithm." International Journal of Operations Research and Information Systems 5, no. 3 (2014): 81–109. http://dx.doi.org/10.4018/ijoris.2014070104.

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A new nature inspired metaheuristic algorithm known as the cuckoo search algorithm (CSA) is presented in this paper, to solve the unit commitment problem (UCP) for hybrid power system. The utilization of wind energy sources is increasing throughout the world. It is therefore important to develop the protocol for the integration of wind generation system with conventional thermal unit generation system. High wind penetration can lead to high-risk level in power system reliability. In order to maintain the system reliability, wind power dispatch is usually restricted and energy storage is consid

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43

Shanti Swarup, K., and P. V. Simi. "Neural computation using discrete and continuous Hopfield networks for power system economic dispatch and unit commitment." Neurocomputing 70, no. 1-3 (2006): 119–29. http://dx.doi.org/10.1016/j.neucom.2006.05.002.

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44

Kotapuri, Mercy Rosalina, and Rajesh Kumar Samala. "Fuzzy Logic Controlled Based Ant-Lion Optimization Hybridization for Economic Power Dispatch." Journal Européen des Systèmes Automatisés 53, no. 5 (2020): 725–31. http://dx.doi.org/10.18280/jesa.530515.

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The demand on the power system rising more rapidly is causing to increase the power system size and capacity. There is a need of interconnection of various generating stations to meet the increased load demand. Economical unit commitment is necessary for plant operation with the advancement in power system integration. The Economical Power Dispatch (EPD) is to find the most favourable combination of generating systems output powers which reduce the fuel cost by satisfying all system constraints. This research involves the fuzzy logic controller (FLC) has been hybridized with Ant-Lion Optimizat

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45

He, Nan, Zhong Fu Tan, Shu Xiang Wang, and Yang Hou. "Study on CO₂ Emission Constraint Based on New Energy Materials for Generation Permits Trade." Advanced Materials Research 577 (October 2012): 22–26. http://dx.doi.org/10.4028/www.scientific.net/amr.577.22.

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Generation permits trade plays a key role in the economic generation dispatch. The application of new energy materials has a positive influence on the generation fuel mix, which offers cleaner power option for generation permits trade. An optimization model on generation permits trade is established to promote the development of renewable energy and the lowest generation cost of a certain unit commitment. Power demand, ramp-up limit, real power of a unit, new energy materials, and a certain emission limit are applied as the constraints of the model. The process of generation permits trade is a

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46

Mbae, Ariel Mutegi, and Nnamdi I. Nwulu. "Day-ahead load forecasting using improved grey Verhulst model." Journal of Engineering, Design and Technology 18, no. 5 (2020): 1335–48. http://dx.doi.org/10.1108/jedt-12-2019-0337.

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Purpose In the daily energy dispatch process in a power system, accurate short-term electricity load forecasting is a very important tool used by spot market players. It is a critical requirement for optimal generator unit commitment, economic dispatch, system security and stability assessment, contingency and ancillary services management, reserve setting, demand side management, system maintenance and financial planning in power systems. The purpose of this study is to present an improved grey Verhulst electricity load forecasting model. Design/methodology/approach To test the effectiveness

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47

Lin, Hongji, Chongyu Wang, Fushuan Wen, et al. "Risk-Limiting Real-Time Economic Dispatch in a Power System with Flexibility Resources." Energies 12, no. 16 (2019): 3133. http://dx.doi.org/10.3390/en12163133.

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The integration of numerous intermittent renewable energy sources (IRESs) poses challenges to the power supply-demand balance due to the inherent intermittent and uncertain power outputs of IRESs, which requires higher operational flexibility of the power system. The deployment of flexible ramping products (FRPs) provides a new alternative to accommodate the high penetration of IRESs. Given this background, a bi-level risk-limiting real-time unit commitment/real-time economic dispatch model considering FRPs provided by different flexibility resources is proposed. In the proposed model, the obj

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48

Azizipanah-Abarghooee, Rasoul, Faranak Golestaneh, Hoay Beng Gooi, Jeremy Lin, Farhad Bavafa, and Vladimir Terzija. "Corrective economic dispatch and operational cycles for probabilistic unit commitment with demand response and high wind power." Applied Energy 182 (November 2016): 634–51. http://dx.doi.org/10.1016/j.apenergy.2016.07.117.

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49

Yalcinoz, T. "An Educational Software Package for Power Systems Analysis and Operation." International Journal of Electrical Engineering & Education 42, no. 4 (2005): 369–82. http://dx.doi.org/10.7227/ijeee.42.4.7.

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This paper presents a software package developed in Matlab for teaching power systems analysis and operation. The software package is used to support and enhance power engineering education at both undergraduate and postgraduate levels. The application programs in this package include fault analysis, load flow analysis, transient stability, economic dispatch, unit commitment and load forecasting. All modules of the package are independent of each other. The students or researchers can make copies of the software to study and can modify any module of the package.

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Nemati, Mohsen, Martin Braun, and Stefan Tenbohlen. "Optimization of unit commitment and economic dispatch in microgrids based on genetic algorithm and mixed integer linear programming." Applied Energy 210 (January 2018): 944–63. http://dx.doi.org/10.1016/j.apenergy.2017.07.007.

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