constrained optimization

With day by day increase in electrical energy demand and uneven distribution of sources in nature, there is a need of Integration of power plants. This integration needs a proper scheduling of all connected generating units in accordance with the variation in load demand. An optimum sharing of load is necessary to minimize the generation cost. Emission is also an important issue in a generation. An attempt is also made in this paper to analyze emission dispatch with the Economic Dispatch optimization. Environmental effects tend to involve renewable sources based power generation. Wind and Solar are most popular and highly abundant among all renewable sources. But, the fluctuations of these sources complicate the load dispatch optimization. Also, the conventional thermal generators itself affected by certain constraints and non linearity such as valve-point loading effect. A proper planning should involve consideration of all this issue, which requires advance soft computing technique. Previous approaches need proper tuning of their specific parameters, to remove this ambiguity, a new Jaya Algorithm technique is introduced in this paper.

This paper presents a new approach to unit commitment (UC) problems using a particle swarm optimization (PSO) technique. The mid term UC problem has a cost function with equality and inequality constraints that make the problem of finding the global optimum difficult by using any mathematical approach. In this paper, a modified PSO (MPSO) mechanism is suggested to deal with the equality and inequality constraints in the UC problems. The proposed MPSO is applied to a 10-unit test system and the results of the MPSO are compared with the results of conventional numerical methods such as mixed integer nonlinear programming (MINLP).

A polynomial trajectory is a time-traveled distance function used to describe trajectory of the robot. Optimal high-degree polynomial trajectories considering initial and the final velocity conditions besides the acceleration constraints are desired. In this paper, a trajectory optimization problem aiming travel maximum distance for a robot that follows an arc based path is formulated. Along the path, the robot requires observing initial and final zero velocity conditions as well as certain acceleration limits. A high-degree polynomial equation along the trajectory is proposed inside of the optimization problem. The closed-form solution of the problem had been obtained analytically. The solution includes the coefficients of the any high-degree trajectory polynomial equation where the coefficients are obtained in closed-form. Simulations several experiments show that the resulting high-degree trajectories satisfy the initial and final zero velocity conditions as well as acceleration constraint.