Network reconfiguration in distribution system is realized by changing the status of sectionalizing switches, and is usually done for the purpose of loss reduction. Loss reduction can result in substantial benefits for a utility. Other benefits from loss reduction include increased system capacity, and possible deferment or elimination of capital expenditures for system improvements and expansion. There is also improved voltage regulation as a result of reducing feeder voltage drop. Research work included by this paper focuses on using branch exchange method to minimize losses and solve the problems over different radial configuration. Solution’s algorithm for loss minimization has been developed based on two stages of solution methodology. The first stage determines maximum loss-reduction loop by comparing the size of circles for every loop. In a distribution system, a loop is associated by a tie-line and hence there are several loops in the system. To obtain the maximum loss- reduction loop, size of modified zero loss-change circles are compared, and the loop within the largest circle is identified for maximum loss-reduction. The second stage determines the switching operation to be executed in that loop to reach a minimum loss network configuration by comparing the size of the loop circle for each branch-exchange. The smallest circle is to be identified for the best solution; the size of the loop circle is reduced when the losses are minimized. The performance of the proposed branch exchange method is tested on 16-bus distribution systems.
In this paper, explicit model predictive controller is applied to an inverted pendulum apparatus. Explicit solutions to constrained linear model predictive controller can be computed by solving multi-parametric quadratic programs. The solution is a piecewise affine function, which can be evaluated at each sample to obtain the optimal control law. The on-line computation effort is restricted to a table-lookup. This admits implementation on low cost hardware at high sampling frequencies in real-time systems with high reliability and low software complexity. This is useful for systems with limited power and CPU resources.