This paper proposes multi-constrained binary integer linear programming (MBILP) method for optimal installation of phasor measurement units in IEEE networks considering Fast Load Voltage Stability Index (FLVSI), branch weight and redundancy constraints to minimize the cost of installation and to accomplish complete network observability. The weak buses of IEEE network are sorted based on their severity through the proposed strategy. A new FLVSI is programmed along with branch weight and redundancy constraints in MBILP to place PMUs in network. As installation cost of PMU for different buses varies with the number of branches or number of channels connected, PMUs should be allotted at bus with minimum cost. Redundancy of bus is computed to measure redundancy of bus network. Priority of PMU placement is considered at weak bus with proposed FLVSI in such a way that the cost is minimized and redundancy is adequate considering both branch weight and redundancy constraints. Ranking is proposed for PMU placement to find weak load bus in network along with the consideration of branch weight and redundancy. Zero injection (ZI) constraint modeling is recommended to minimize allocations further in system without losing observability. Contingency constraints for single-line or PMU loss are considered for allocation of PMUs. The proposed method is compared with ZI and without ZI modeling under general and line-outage or PMU loss cases to show efficacy of method. To estimate observability performance of complete network, a Complete Network Bus Observability Index is suggested. IEEE 14-, 24-, 30-and 57-bus networks are programmed with MATLAB software and compared with standard approaches to validate their efficacy.

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A conquest for Science and also Technology and also the ever-growing planet of innovation trigger numerous innovations. Currently India demandingly picking to beat non-renewable fuel sources sparsity issues along with Renewable Energy Sources (RES). Renewable Energy Sources needs intricate innovations for the usage. Renewable resource resources and also modern technologies possess prospective to supply options to the enduring electricity troubles being actually experienced due to the establishing nations. The renewable resource resources like wind power, solar power, geothermal power, electricity, biomass electricity and also energy tissue innovation may be made use of to get over electricity lack in India. To overcome the power demand for such a fast-growing economic climate, India will certainly need an ensured source of 3- 4 times extra power than the overall power consumed today. This work reviews different control techniques and proposes a new control technique Optimal Recurrent Neural Networks (ORNN) based Controller to mitigate the power quality (PQ) disturbances of power system. In the proposed approach, optimal weight selection is employed for enhancing the learning procedure of RNN (ORNN). Here, ORNN technique is utilized for selecting the ideal control signal of grid inverter through optimal adjustments of the control variables in the power system. The proposed strategy creates the ideal control of the grid inverter which tries to enhance the power quality of a power system and manage the line voltage by providing reactive power compensation. This paper reviews several papers with different control strategies applied to the grid connected inverter.