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Investigation of Real Power Flow Control of AI Based MC-UPFC in FACTS Controllers

Journal of Energy and Power Engineering 2020年第4期14卷 111-130页

作者： Boopalan Chandran saravanan vasudevan Raghavendiran TA Anna University Chennai 600025India Arunai Engineering College Tiruvannamalai 606603India Sri venakateswara Engineering College for Women Tirupathi 517507India

The power consumption is rapidly increased due to ASD(Adjustable Speed Drives)and automation in industries and large consumption of electricity in domestic regions increased the concern of the power *** quality of the power received in the distribution system is altered because of the losses in the transmission *** losses in the transmission system are mitigated using the FACTS(Flexible AC Transmission System)controller,among these controllers UPFC(Unified Power Flow Controller)plays a vital role in controlling the shunt and series reactive powers in the bus of the power *** conventional topology of the UPFC consists of AC-DC converter and energy stored in the DC link and DC-AC converter injected a voltage in series to the bus which is to be *** a new topology based on matrix converter can replace the dual converters and perform the required *** construction of 2-bus,7-bus and IEEE-14-bus power system is designed and ***-UPFC(Matrix Converter Based Unified Power Flow Controller)is designed and *** MC-UPFC is the rich topology in the FACTS which is capable of controlling both the transmission parameters simultaneously with the switching technique of direct power control by the smooth sliding control which gives less ripple in the injecting control parameters such as control voltage(Vc)and voltage angle(α).By implementing MC-UPFC the real and reactive power can be controlled simultaneously and *** control techniques were designed based on the PID(Proportional Integral Derivative)with sliding surface power control,FLC(Fuzzy Logic Controller)and ANN(Artificial Neural Network)and the performances of Vc andαof the controllers are *** the sliding surface and relevant control switching state of the MC can be controlled by the FLC which gives the robust and autonomous decision made in the selection of the appropriate switching state for the effective real power control in the power syst

关键词： Matrix converter unified power flow controller fuzzy logic controller

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A solution to unit commitment problem using invasive weed optimization algorithm

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Frontiers in Energy 2013年第4期7卷 487-494页

作者： B. saravanan E. R. vasudevan D. P. KOTHARI School of Electrical Engineering Vellore Institute of Technology University Vellore 632014 India JB Group of Educational Institutions Hyderabad 500 034 India

Unit commitment （UC） is one of the most important aspect of power generation in the world today. Though, there is no method to find the exact optimized solution, there exists several meta-heuristic algorithms to determine the close to exact solution. This paper proposes a novel solution to effectively determine UC and generation cost using the technique of invasive weed optimization （IWO）. The existing technique distributes the load demand among all the generating units. The method proposed here utilizes the output of UC obtained by using the Lagrangian relaxation （LR） method and calculates the required generation from only the plants that are ON discarding the OFF generator units and thereby giving a faster and more accurate response. Moreover, the results show the comparison between the LR-particle swarm optimization （PSO） and LR-IWO, and prove that the cost of generation for a 4 unit, 8 hour schedule is much less in the case of IWO when compared to PSO.

关键词： Lagrangian relaxation (LR) invasive weed optimization (IWO) economic dispatch optimization fuel cost seed fitness

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