Investigating a Ranking of Loads in Avoiding Potential Power System Outages

• Autorzy: Fahrioglu M. , Nwulu N.I.

Warianty tytułu

PL

Opracowanie rankingu odbiorników pod względem odporności na potencjalne problemy w systemie energetycznym

• Języki publikacji: EN

Abstrakty

EN

In this work, we consider the impact or sensitivity of loads to likely power system contingencies that would require the adoption of dem and management programs and we establish a frame work for determining the most critical loads and ranking them. Moreover we develop a novel weighted average approach that can be modified to specific power system needs and determine the most effective load for a number of likely contingencies. The methodologies developed in this work are tested on a wide range of sample power system test cases with successful results

PL

W artykule przedstawiono wyniki prac dotyczących badania wpływu oraz wrażliwości odbiorników na możliwe awarie w systemie energetyczny, ingerujące w zarządzanie dystrybucją mocy. Opracowany został system segregacji i oceny najbardziej wrażliwych odbiorników.

Słowa kluczowe

EN

Power System Outages; Demand Management Programs; electric loads; sensitivity analysis

PL

analiza wrażliwości; zarządzanie poborem energii w sieci; blackout; awaria sieci; odbiorniki elektryczne

• Wydawca: Wydawnictwo SIGMA-NOT
• Czasopismo: Przegląd Elektrotechniczny
• Rocznik: 2012
• Tom: R. 88, nr 11a
• Strony: 239--242
• Opis fizyczny: Bibliogr. 12 poz., tab., rys.

Twórcy

autor

Fahrioglu M.

autor

Nwulu N.I.

• Dept. of Electrical & Electronics Engineering, Middle East Technical University, NCC,

Bibliografia

• [1] Gelings C. W., The concept of demand side management for electric utilities, Proc. Of the IEEE., 73 (1985), No.10, 1468-1470.
• [2] Saffre F., Gedge R., Demand Side management for the smart grid, IEEE/IFIP Network Operations and management symposium, April 2010
• [3] Nwulu N.I., Fahrioglu M. A Neural Network Model for Optimal Demand Management Contract Design // 10th International Conference on Environmental & Electrical Engineering (EEEIC2011), 8-11, May 2011, Rome, Italy
• [4] Nwulu N.I., Fahrioglu M. Power System Demand Management Contract Design: A Comparison between Game Theory and Artificial Neural Networks, International Review of Modelling and Simulations, 4 (2011), No. 1, 106-112
• [5] Fahrioglu M., Lasseter R.H., Alvarado F. L., Yong T. Suplementing Demand Management Programs with Distributed Genertion Options, Electric Power System Research, 84 (2012), No.1, 195-200.
• [6] Liu M., Gross G., Role of distribution factors in congestion revenue rights application, IEEE Transactions on Power Systems, 19 (2004), No. 2, 802-810
• [7] Zimmerman R.D., Murillo-Sanchez C.E., Thomas R.J. MATPOWER Steady-state operations, planning and analysis tools for power systems research and education, IEEE Transactions on Power Systems. 26 (2011), No.1, 12-19.
• [8] Greene S., Dobson I., Alvarado F. L., Sensitivity of the loading margin to voltage collapse with respect to arbitrary parameters., IEEE Transactions on Power Systems. 12 (1997), No. 1, 262-272.
• [9] Alvarado F. L., Obtaining Efficient Prices: Nodal Pricing and PTDFs., EEI Transmission Pricing School, July 2001.
• [10] Momoh J., Xia Y., Boswell G., Locational Marginal Pricing for real and reactive power., IEEE PES General Meeting, 2008. P. 1-8
• [11] Nwulu N.I., Fahrioglu M., A Soft Computing Approach to Projecting Locational Marginal Price., Neural Computing and Applications. 2012. DOI 10.1007/s00521-012-0875-8.
• [12] Zhang J., Dobson I., Alvarado F. L., Quantifying transmission reliability margin, Intl. Journal of Electric Energy and Power Systems. 26 (2004), No. 9, 697-702.