Stability Analysis and Efficiency Improvement of a Multi-converter System Using Multi-objective Decision Making

Multi-converter system is mainly used in advanced automotive systems.Different converters and inverters are taking part in automotive systems to provide different voltage levels in a multi-converter system.It involves constant voltage load(CVL),constant power load(CPL)and other loads.The CPL in such systems offers negative impedance characteristic and it creates a destabilizing effect on the main converter.The effect of destabilization can be reduced by increasing the CVL or inserting parasitic components.Attempts have been made by authors to improve the stability by using parasitics of different components such as switch,diode and inductor.Influence of insertion of parasitics including the series equivalent resistance of the filter capacitor and variation in CVL on the performance of main converter is mathematically analyzed and conflicting behavior between system stability and efficiency is observed.The optimum solution between these two functions is obtained by using multi-objective decision making(MODM)by varying parasitics of different components and CVL.An attempt has been made to demonstrate the effect of CVL load and the parasitics on the stability and efficiency of the main converter,experimentally.

Attuned design of demand response program and M-FACTS for relieving congestion in a restructured market environment

This paper addresses the attuned use of multi- converter flexible alternative current transmission systems （M-FACTS） devices and demand response （DR） to perform congestion management （CM） in the deregulated environment. The strong control capability of the M- FACTS offers a great potential in solving many of the problems facing electric utilities. Besides, DR is a novel procedure that can be an effective tool for reduction of congestion. A market clearing procedure is conducted based on maximizing social welfare （SW） and congestion as network constraint is paid by using concurrently the DR and M-FACTS. A multi-objective problem （MOP） based on the sum of the payments received by the generators for changing their output, the total payment received by DR participants to reduce their load and M-FACTS cost is systematized. For the solution of this problem a nonlinear time-varying evolution （NTVE） based multi-objective particle swarm optimization （MOPSO） style is formed. Fuzzy decision-making （FDM） and technique for order preference by similarity to ideal solution （TOPSIS） approaches are employed for finding the best compromise solution from the set of Pareto-solutions obtained through multi-objective particle swarm optimization-nonlinear time-varying evolution （MOPSO-NTVE）. In a real power system, Azarbaijan regional power system of Iran, comparative analysis of the results obtained from the application of the DR ＆ unified power flow controller （UPFC） and the DR ＆ M-FACTS are presented.