Abstract: High Speed PM Generators driven by micro-turbines
are widely used in Smart Grid System. So, this paper proposes
comparative study among six classical, optimized and genetic
analytical design cases for 400 kW output power at tip speed 200
m/s. These six design trials of High Speed Permanent Magnet
Synchronous Generators (HSPMSGs) are: Classical Sizing;
Unconstrained optimization for total losses and its minimization;
Constrained optimized total mass with bounded constraints are
introduced in the problem formulation. Then a genetic algorithm is
formulated for obtaining maximum efficiency and minimizing
machine size. In the second genetic problem formulation, we attempt
to obtain minimum mass, the machine sizing that is constrained by
the non-linear constraint function of machine losses. Finally, an
optimum torque per ampere genetic sizing is predicted. All results are
simulated with MATLAB, Optimization Toolbox and its Genetic
Algorithm. Finally, six analytical design examples comparisons are
introduced with study of machines waveforms, THD and rotor losses.
Abstract: This paper proposes a new optimization techniques
for the optimization a gas processing plant uncertain feed and
product flows. The problem is first formulated using a continuous
linear deterministic approach. Subsequently, the single and joint
chance constraint models for steady state process with timedependent
uncertainties have been developed. The solution approach
is based on converting the probabilistic problems into their
equivalent deterministic form and solved at different confidence
levels Case study for a real plant operation has been used to
effectively implement the proposed model. The optimization results
indicate that prior decision has to be made for in-operating plant
under uncertain feed and product flows by satisfying all the
constraints at 95% confidence level for single chance constrained and
85% confidence level for joint chance constrained optimizations
cases.
Abstract: The optimal control problem for the viscoelastic melt
spinning process has not been reported yet in the literature. In this
study, an optimal control problem for a mathematical model of a
viscoelastic melt spinning process is considered. Maxwell-Oldroyd
model is used to describe the rheology of the polymeric material, the
fiber is made of. The extrusion velocity of the polymer at the spinneret
as well as the velocity and the temperature of the quench air and the
fiber length serve as control variables. A constrained optimization
problem is derived and the first–order optimality system is set up
to obtain the adjoint equations. Numerical solutions are carried out
using a steepest descent algorithm. A computer program in MATLAB
is developed for simulations.
Abstract: Overcurrent (OC) relays are the major protection
devices in a distribution system. The operating time of the OC relays
are to be coordinated properly to avoid the mal-operation of the
backup relays. The OC relay time coordination in ring fed
distribution networks is a highly constrained optimization problem
which can be stated as a linear programming problem (LPP). The
purpose is to find an optimum relay setting to minimize the time of
operation of relays and at the same time, to keep the relays properly
coordinated to avoid the mal-operation of relays.
This paper presents two phase simplex method for optimum time
coordination of OC relays. The method is based on the simplex
algorithm which is used to find optimum solution of LPP. The
method introduces artificial variables to get an initial basic feasible
solution (IBFS). Artificial variables are removed using iterative
process of first phase which minimizes the auxiliary objective
function. The second phase minimizes the original objective function
and gives the optimum time coordination of OC relays.