This paper presents a distribution planning on a geographical network, using improved K-means clustering algorithm and is compared with the conventional Euclidean distance based K-means clustering algorithm. The distribution planning includes optimal placement of substation, minimization of expansion cost, optimization of network parameters such as network topology, routing of single/multiple feeders, and reduction in network power losses. The improved K-means clustering is an iterative weighting factor based optimization algorithm which locates the substation optimally and improves the voltage drop at each node. For feeder routing shortest path based algorithm is proposed and the modified load flow method is used to calculate the active and reactive power losses in the network. Simulation is performed on 54 nodes based geographical network with load points and the results obtained show significant power loss minimization as compared to the conventional K-means clustering algorithm.

This paper presents a marketing mechanism based on the Pay-As-Bid (PAB) method for reactive power ancillary services in the deregulated electricity market. Security, reliability and the location is major concern for Independent System Operator (ISO). So a modified Optimal Power Flow (OPF) optimization method is proposed in this paper to provide the system security. Firstly, the reactive power solution is obtained by solving a modified OPF model which maximizes system loadability subject to transmission security constraints imposed by thermal limits, voltage limits and stability limits. This modified OPF model is used for ensuring systemsecurity as well as for contingency analysis. Secondly, the Expected Payment Function (EPF) of generators is used to develop a bidding framework while Total Payment Function (TPF) based OPF is used to clear the PAB market. For the simulation and analysis purposes, a 24 bus RTS network is used in normal condition as well as in worst contingency state. The system security is preserved even in the worst contingency state. 

This paper presents a distribution network reconfiguration based on bacterial foraging optimization algorithm (BFOA) along with backward-forward sweep (BFS) load flow method and geographical information system (GIS). Distribution network reconfiguration (DNR) is a complex, non-linear, combinatorial, and non-differentiable constrained optimization process aimed at finding the radial structure that minimized network power loss while satisfying all operating constraints. BFOA is used to obtain the optimal switching configuration which results in a minimum loss, BFS is used to optimize the deviation in node voltages, and GIS is used for planning and easy analysis purposes. Simulation is performed on the 33-bus system and results are compared with the other approaches. The obtained results show that the proposed approach is better in terms of efficiency and having good convergence criteria.

Inverted Pendulum is a well established benchmark problem that produces many challenges to a control engineer. It is a nonlinear, unstable, non minimumphase and under actuated system.Itrequires a controller which canadapt in different disturbance conditions and work appreciably well when compared to conventional controllers. In this paper Interval type-2 Fuzzy logic controllerfor inverted pendulum isdesigned.The objective of the proposed control technique is to develop the stability position of the pendulum. The optimal membership functions and the interference system are developed using IT2FLS. Using the IT2FLS, the position of the inverted pendulum is maintained towards the reference position. The proposed control techniqueis implemented in MATLAB/Simulink working platform and the control performances are evaluated. Then, the performance of proposed controller is evaluated and compared with the PI controller, Fuzzy controller andABC- FLC.

In this paper, a hybrid control technique is proposed for managing the variation of angle and velocity of the inverted pendulum. The proposed hybrid technique is the combination of ABC algorithm and interval type-2 Fuzzy Logic System (IT2FLS). The objective of the proposed hybrid control technique is to achieve the stability position of the pendulum. Here, the ABC algorithm is used to optimize the change of angle and change of velocity of the pendulum. With the optimized value, the optimal membership functions and the interference system are developed using IT2FLS. Using the ABC based IT2FLS, the position of the inverted pendulum is maintained towards the reference position. The proposed hybrid control technique is implemented in MATLAB/Simulink working platform and the control performances are evaluated.