AI approach to optimal var control with fuzzy reactive loads

Journal Article · Wed Feb 01 04:00:00 EST 1995 · IEEE Transactions on Power Systems

DOI:https://doi.org/10.1109/59.373931· OSTI ID:49194

Abdul-Rahman, K H; Shahidehpour, S M ^[1]; Daneshdoost, M ^[2]

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1. Illinois Inst. of Tech., Chicago, IL (United States). Dept. of Electrical and Computer Engineering
2. Southern Illinois Univ., Carbondale, IL (United States). Dept. of Electrical and Computer Engineering

This paper presents an artificial intelligence (AI) approach to the optimal reactive power (var) control problem. The method incorporates the reactive load uncertainty in optimizing the overall system performance. The artificial neural network (ANN) enhanced by fuzzy sets is used to determine the memberships of control variables corresponding to the given load values. A power flow solution will determine the corresponding state of the system. Since the resulting system state may not be feasible in real-time, a heuristic method based on the application of sensitivities in expert system is employed to refine the solution with minimum adjustments of control variables. Test cases and numerical results demonstrate the applicability of the proposed approach. Simplicity, processing speed and ability to model load uncertainties make this approach a viable option for on-line var control.

• OSTI ID: 49194
• Report Number(s): CONF-940110--
• Journal Information: IEEE Transactions on Power Systems, Journal Name: IEEE Transactions on Power Systems Journal Issue: 1 Vol. 10; ISSN 0885-8950; ISSN ITPSEG
• Country of Publication: United States
• Language: English

Related Subjects

24 POWER TRANSMISSION AND DISTRIBUTION
ARTIFICIAL INTELLIGENCE
COMPUTERIZED SIMULATION
EXPERT SYSTEMS
FUZZY LOGIC
POWER SYSTEMS