A Review on Wind and Solar type DG Placement in Power Distribution Networks to Enhance the Systems Stability
Keywords:
Distributed generation, Distribution system adequacy assessment, Reliability, Solar energy, Wind energyAbstract
In the previous paper they propose a distributed generator (DG) placement methodology based on newly defined term reactive power load ability. The effectiveness of the proposed planning is carried out over a distribution test system representative of the Kumamoto area in Japan. The proposed approach can reduce the power loss of the system, which in turn, reduces the size of compensating devices. In this paper, we proposed conventional and renewable distributed generation (DG) on the reliability of future distribution systems, even when the connection may not be simply radial. The variability of the power output of renewable DGs, such as wind and solar is included. The stochastic nature of the renewable resources and their influence on the reliability of the system are modeled and studied by computing the adequacy transition rate. An integrated Markov model that incorporates the DG adequacy transition rate, DG mechanical failure, and starting and switching probability is proposed and utilized to give accurate results for the DG reliability assessment. The main focus is conventional generation, solar, and wind DG units. The technique used appears to be applicable to any renewable energy source.
References
2. Mithulananthan N, Oo T, Phu LV. Distributed generator placement in power distribution system using genetic algorithm to reduce losses. Thammasat International Journal of Science and Technology 2004; 9: 55–62.
3. Roy NK, Hossain MJ, Pota HR. Effects of load modeling in power distribution system with distributed wind generation. Proc. Australasian Universities Power Engineering (AUPEC 2011), 2011, Brisbane, Australia.
4. Borges C, Falcao D. Impact of distributed generation allocation and sizing on reliability, losses and voltage profile. Power Tec Conference Proceedings, 2003 IEEE Bologna 2003; 2: 1-5.
5. Acharya N, Mahat P, Mithulananthan N. An analytical approach for DG allocation in primary distribution network. InternationalJournal of Electrical Power & Energy Systems 2006; 28(10): 669– 678.
6. LÖf PA, Hill DJ, Arnborg S et al. On the analysis of longterm voltage stability. International Journal of Electrical Power & Energy Systems 1993; 15(4): 229-237.
7. Acharya N, Mahat P, Mithulananthan N. Distributed generation placement to maximize the loadability of a distribution system. International Journal of Electrical Engineering Education 2006; 43(2): 107-118.
8. Canizares CA, ACZ de Souza, Quintana VH. Comparison of performance indices for detection of proximity to voltage collapse. IEEE Trans. of Power Systems 1996; 11(3): 1441-1450.
9. Celli G, Pilo F. Optimal distributed generation allocation in MV distribution networks. IEEE Power Engineering Society International Conference on Power Industry Computer Applications, 2001, pp. 81–86. 10. Guo Y, Lin Y, Sun M. The impact of integrating distributed generation on the losses in the smart grid. Proc. IEEE Power and Energy Society General Meeting, Detroit, USA, 24-29 July 2011.
11. Tautiva C, Cadena A, Rodriguez F. Optimal placement of distributed generation on distribution networks. Proc. Universities Power Engineering Conference (UPEC), 2009.
12. Parizad A, Khazali AH, Kalantar M. Siting and sizing of distributed generation through harmony search algorithm for improve voltage profile and reducuction of THD and losses. Proc. 23rd Canadian Conference on Electrical and Computer Engineering(CCECE), 2010.
13. Roy NK, Pota HR, Hossain MJ et al. An effective VAR planning to improve dynamic voltage profile of distribution networks with distributed wind generation. IEEE Power and EnergySociety General Meeting, 2012, San Diego, USA. (Accepted) 14. Mithulananthan N, Salama MMA, Cañizares CAet al. Distribution system voltage regulation and var compensation for different static load models. IJEEE 2000; 37(4): 384–395.
15. Taylor CW, Power System Voltage Stability, New York:
McGraw-Hill, 1994.
16. Kessel P, Glavitsch H. Estimating the voltage stability of a power system. IEEE Trans. on Power Delivery 1986; 1: 346-354.
17. Aziz T, Saha TK, Mithulananthan N. Identification of the weakest bus in a distribution system with load uncertainties using reactive power margin. Proc. Australasian Universities PowerEngineering (AUPEC 2010), 2010, Christchurch, New Zealand.
18. Freitas W, Vieira J, Morelato A et al. Influence of excitation system control modes on the allowable penetration level of distributed synchronous generators. IEEE Trans. on Energy Conversion 2005; 20(2): 474–480.
19. Li S, Tomsovic K, Hiyama T. Load following functions using distributed energy resources. Proc. IEEE Power Engineering Society Summer Meeting, 2000, Seattle, Washington, USA.
20. Kueck J, Kirby B, Rizy T et al. Reactive power from distributed energy. The Electricity Journal 2006; 19(10): 27-38.
Published
Issue
Section
Copyright (c) 2019 Journal of Advanced Research in Modeling and Simulation
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
We, the undersigned, give an undertaking to the following effect with regard to our article entitled
“_______________________________________________________________________________________________________________________________________________________________________________
________________________________________________________________________________” submitted for publication in (Journal title)________________________________________________ _______________________________________________________Vol.________, Year _________:-
1. The article mentioned above has not been published or submitted to or accepted for publication in any form, in any other journal.
2. We also vouchsafe that the authorship of this article will not be contested by anyone whose name(s) is/are not listed by us here.
3. I/We declare that I/We contributed significantly towards the research study i.e., (a) conception, design and/or analysis and interpretation of data and to (b) drafting the article or revising it critically for important intellectual content and on (c) final approval of the version to be published.
4. I/We hereby acknowledge ADRs conflict of interest policy requirement to scrupulously avoid direct and indirect conflicts of interest and, accordingly, hereby agree to promptly inform the editor or editor's designee of any business, commercial, or other proprietary support, relationships, or interests that I/We may have which relate directly or indirectly to the subject of the work.
5. I/We also agree to the authorship of the article in the following sequence:-
Authors' Names (in sequence) Signature of Authors
1. _____________________________________ _____________________________________
2. _____________________________________ _____________________________________
3. _____________________________________ _____________________________________
4. _____________________________________ _____________________________________
5. _____________________________________ _____________________________________
6. _____________________________________ _____________________________________
7. _____________________________________ _____________________________________
8. _____________________________________ _____________________________________
Important
(I). All the authors are required to sign independently in this form in the sequence given above. In case an author has left the institution/ country and whose whereabouts are not known, the senior author may sign on his/ her behalf taking the responsibility.
(ii). No addition/ deletion/ or any change in the sequence of the authorship will be permissible at a later stage, without valid reasons and permission of the Editor.
(iii). If the authorship is contested at any stage, the article will be either returned or will not be
processed for publication till the issue is solved.
