PL EN


Preferencje help
Widoczny [Schowaj] Abstrakt
Liczba wyników
Tytuł artykułu

Reactive power based fair calculation approach for multiobjective load dispatch problem

Treść / Zawartość
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
This paper proposes a fair calculation approach for the cost and emission of generators. Generators also have reactive power requirements along with the active power demand to meet up the total power demand. In this paper, firstly the reactive power is calculated considering the random active power operating points on the capability curve of a generator then the cost for reactive power generation as well as emission are calculated. In order to develop the mathematical function for the reactive power cost and reactive power emission, a curve-fitting technique is applied, which gives the generalised reactive power cost and reactive power emission functions. At the end, the problem is formulated as a multiobjective problem, considering conflicting objectives such as combined activereactive economic dispatch and combined active-reactive emission dispatch. The problem is converted from the multiobjective load dispatch problem (MOLDP) into a scalar problem, using the weighting method and the best compromised solution has been calculated using the particle swarm optimization (PSO) technique. A fuzzy cardinal method has been applied to choose the best solution. In order to demonstrate the efficiency of developed functions the proposed method is applied on a 3 generator unit system and a 10 generator unit system, the results obtained show its validity and effectiveness.
Rocznik
Strony
719--735
Opis fizyczny
Bibliogr. 26 poz., rys., tab., wz.
Twórcy
  • I.K. Gujral Punjab Technical University Jalandhar – Kapurthala Highway, VPO – Ibban, India
  • I.K. Gujral Punjab Technical University Jalandhar – Kapurthala Highway, VPO – Ibban, India
autor
  • Wainganga College of Engineering and Management Wardha Road, Gumgaon, Nagpur, India
Bibliografia
  • [1] Miller R.H., Malinnowski J.H., Power System Operation, McGraw-Hill, Inc. (1994).
  • [2] Kothari D.P., Dhillon J.S., Power System Optimization, Second Edition, PHI learning private limited (2011).
  • [3] Singh H.P., Brar Y.S., Kothari D.P., Multiobjective load dispatch using particle swarm optimization, Proceeding of 8th IEEE conference on Industrial Electronics and Application (ICIEA2013), Melbourne, VIC, Australia, pp. 272–277 (2013).
  • [4] Walter D.C., Sheble G.B., Genetic algorithm solution of economic dispatch with valve point loading, IEEE Trans. Power Syst., vol. 8, no. 3, pp. 1325–1332 (1993).
  • [5] Yang H.T., Yang P.C., Huang C.L., Evolutionary programming based economic dispatch for units with non-smooth fuel cost functions, IEEE Trans. Power Syst., vol. 11, no. 1, pp. 112–118 (1996).
  • [6] Abido M.A., Environmental/economic power dispatch using multiobjective evolutionary algorithm, IEEE Trans. Power Syst., vol. 18, no. 4, pp. 1529–1537 (2003).
  • [7] Brar Y.S., Dhillon J.S., Kothari D.P., Multi-objective load dispatch by fuzzy logic based searching weightage pattern, Electr. Power Syst. Res., vol. 63, pp. 149–60 (2002).
  • [8] Brar Y.S., Dhillon J.S., Kothari D.P., Fuzzy satisfying multi-objective generation scheduling based on simplex weightage pattern search, Electric Power and Energy System, vol. 27, pp. 518–527 (2005).
  • [9] Storn R., Price K.V., Differential evolution – a simple and efficient heuristic for global optimization over continuous spaces, Int. Journal of Global Optimization, vol. 11, pp. 341–359 (1997).
  • [10] Coelho L.S., Mariani V.C., Combining of chaotic differential evolution and quadratic programming for economic dispatch optimization with valve-point effect, IEEE Transactions on Power Systems, vol. 21, no. 2, pp. 989–996 (2006).
  • [11] Basu M., Economic environmental dispatch using multi-objective differential evolution, Applied Soft Computing, vol. 11, pp. 2845–2853 (2011).
  • [12] Chen G., Combined economic emission dispatch using SFLA, International Conference on Information Engineering and Computer Science (ICIECS), Wuhan, China, Dec. 19–20, pp. 1–4 (2009).
  • [13] Eusuff M.M., Lansey K., Pasha F., Shuffled frog-leaping algorithm: A memetic meta-heuristic for discrete optimization, Engineering Optimization, vol. 38, pp. 129–54 (2006).
  • [14] Darabian M., Mohseni-Bonab S.M., Mohammadi-Ivatloo B., Improvement of power system stability by optimal SVC controller design using shuffled frog-leaping algorithm, IETE Journal of Research, vol. 61, no. 2, pp. 160–169 (2015).
  • [15] Muchayi M., A summary of algorithm in reactive power pricing, Electr. Power Energy Syst., vol. 21, pp. 119–125 (1999).
  • [16] Dona V.M., Paredes A.N., Reactive power pricing in competitive electric markets using the transmission losses function, Power Tech Conference, Portugal, pp. 1–6 (2001).
  • [17] Chu W., Chen B., Allocating the costs of reactive power purchased in an ancillary services market by modified Y-bus matrix method, IEEE Trans. Power Syst., vol. 9, pp. 174–180 (2004).
  • [18] Xie K., Calculation and decomposition of spot price using interior point nonlinear optimization methods, Electr. Power Energy Syst., vol. 26, pp. 379–388 (2004).
  • [19] Hasanpour S., Ghaziand R., Javidi M.H., A new approach for cost allocation and reactive power pricing in a deregulated environment, Elect. Eng., vol. 91, no. 1, pp. 27–34 (2009).
  • [20] Shamani M., Ahmadi H., Ramezani M., Probabilistic framework of cooperative disperse generation resources scheme for producing required reactive power through simultaneous active and reactive power markets, CIRED-Open Access Proceedings Journal (2017).
  • [21] Saxena N.K., Kumar A., Dynamic Reactive Power Compensation and Cost Analysis for Isolated Hybrid Power System, Electric Power Components and Systems, vol. 45, no. 18, pp. 2034–2049 (2018).
  • [22] Danalakshmi D., Kannan S., Gnanadass R., Generator reactive power pricing for practical utility system using power flow tracing method, International Journal of Engineering and Technology, vol. 7, no. 1.8, pp. 20–25 (2018).
  • [23] Samini A., Kazemi A., Coordinated Volt/Var Control in Distribution Systems with Distributed Generations Based on Joint Active and Reactive Powers Dispatch, Appl. Science, vol. 6, no. 4 (2016).
  • [24] Eberhart R.C., Kennedy J., A new optimizer using particle swarm theory, Proceedings of the 6th. International Symposium on Micro Machine and Human Science, Nagoya, Japan, pp. 39–43 (1995).
  • [25] Singh H.P., Brar Y.S., Kothari D.P., Combined active and reactive power dispatch using particle swarm optimization, Proceedings of informing science and IT education conference (insite), Wollongong, NSW, Australia, pp. 295–304 (2014).
  • [26] Aribia H.B., Derbel N., Abdallah H.H., The active–reactive complete dispatch of an electrical network, International Journal of Electrical Power and Energy Systems, vol. 44, no. 1, pp. 236–248 (2013).
Uwagi
Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2019).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-32c68301-5d6a-40b0-9622-d8691ee302da
JavaScript jest wyłączony w Twojej przeglądarce internetowej. Włącz go, a następnie odśwież stronę, aby móc w pełni z niej korzystać.