Unscheduled Intentional Islanding in Microgrid using Trust Region based Sequential Linear Programming

This article deals with the optimization of energy resource management of industrial districts, with the aim of minimizing customer energy expenses. A model of the district is employed, whose optimization gives rise to a nonlinear constrained optimization problem. Here the focus is on its numerical solution. Two different methods are considered: a sequential linear programming method and a particle swarm optimization method. Efficient implementations of both approaches are devised and the results of the tests performed on several energetic districts are reported, including a real case study.

Production planning is an important thing in company management. Every company aims to seek maximum profit in its business activities, so it must be able to utilize its resources as optimally as possible. This study was conducted to determine whether or not any production planning that has been implemented at Istana Roti Hilyah Bakery is optimal. This research aimed to maximize revenue and profit, minimize production costs and raw material usage and optimize production quantities using the sequential linear goal programming method and the simplex modification method with the assistance of LINGO software. Based on the study's results, the revenue increased by IDR 60,000, and the profit increased by IDR 66,679. The minimization value of production costs decreased by IDR 6,679, with the production amount of White Bread as many as 60 pcs, Almond Crumble Bread as many as 45 pcs, Chocolate Crumble Bread as many as 50 pcs, Wheat Bran Bread as many as 55 pcs, Sweet Comb Bread as many as 82 pcs and Jam Comb Bread as many as 84 pcs.

In the current scenario Economic Dispatch problem has taken a suitable twist as the public has become increasingly concerned with environmental matters. The dispatch of systems to minimise pollutants, as well as to achieve minimum cost are the two main constraints to be dealt with. In this paper, Global optimization techniques such as Honey Bee’s and Simulated Annealing techniques are employed together (HB-SA) to solve the Combined static Economic and Emission dispatch (CEED) problems in power system. This paper clearly is justified with the results, separately obtained for the above two techniques and is also provided with the results on applying both the algorithms separately. With practical consideration, Economic Dispatch will have non-smooth cost functions with equality and inequality constraints that make the problem, a large-scale highly constrained non linear optimization problem. As to demonstrate the effectiveness of the proposed method, it is subjected to the CEED problems considering (or) handling valve point loading effects. Comparison with other optimization techniques showed the superiority of the proposed HB-SA approach and confirmed its potential for solving nonlinear CEED problems.

Identification of dynamic parameters of a 3-DOF RPS parallel manipulator

Swarm algorithms have been successfully applied to obtain global optimal solutions for complex problems such as multi-peak problems. However these algorithms have not been applied to complicated structural and mechanical optimization problems since local optimization c apability is still inferior to general numerical optimization methods. This paper discusses new swarm metaphors that incorporate design sensitivities concerning objective and constraint functions and are applicable to structural and mechanical design optim ization problems. Single - and multiobjective optimization techniques using swarm algorithms are combined with a sequential linear programming (SLP) method. In the proposed techniques, swarm optimization algorithms and SLP are conducted simultaneously. Fina lly, truss structure design optimization problems are solved by the proposed hybrid method to verify the optimization efficiency.

This paper presents structural topology optimization applied to the coupled magneto-structural problem. The design goals are to minimize mechanical compliance and to maximize total magnetic force. To calculate the compliance and magnetic force, coupled magneto-structural analysis is performed using the finite-element method. From the solution of a magnetostatic analysis, distribution of the magnetic body force is obtained using the virtual air gap scheme. The structural analysis from the calculated force distribution then provides the mechanical compliance. The design sensitivity analysis for the optimization is performed using the adjoint method, and the derived sensitivity is verified by comparing it with the finite difference sensitivity. The optimization problem is formulated and solved using the sequential linear programming (SLP) method. To show the validity of the proposed analysis and optimization approach, design of the solenoid actuator is presented.

The paper deals with homologous topology optimization of structures undergoing large deformations. The objective function is defined so that the load-displacement curve follows the prescribed trajectry, which shows a typical snap-through buckling. The geometrically non-linear behavior of the structures is modeled using the total-Lagrangian finite element formulation and the equilibrium is found using a Newton-Raphson iterative scheme. In order to escape from the singularity at critical points, the displacement control is utilized. The sensitivities of the objective functions are found with the adjoint method and the optimization problem is solved using the sequential linear programming method. Two algorithms are proposed to obtain homologous deformation. Several numerical examples are demonstrated to validate the present optimization method.

Real-time digital simulation and graphic animation limited band-width dynamic control systems can significantly enhance the interpretation and understanding of system responses. This paper outlines an efficient techniques for generating the graphics and the timing in real-time simulation and animation of the dynamic control systems using a high-speed high- performance PC-AT microcomputer. For illustration, the simulation and animation results for the adaptive computer controlled suspension of a combat vehicle and for the gun-turret stabilization and tracking control system for combat vehicle are presented.

The impact of load characteristics and the low-voltage load shedding schedule on dynamic voltage stability is studied for part of the power grid in Beijing. The research is conducted on a real-time digital simulation (RTDS) system and based on the projected data for the power grid in the Northern China region. We show that under severe shortage of active power, the larger proportion of asynchronous motors in the total load is, the more likely voltage collapses; while the larger proportion of fixed impedance in the total load is, the more likely frequency collapses. Therefore, load characteristics has significant impact on the voltage stability. Proper application of the low-voltage load shedding schedule will improve the power grid stability

The nonlinear magnetic properties of an iron core should be considered when topology optimization (TO) is applied to a realistic problem. However, a scheme for introduction of the magnetic nonlinearity to material-density-based TO has not been rigorously established. In this paper, TO by using material density with magnetic nonlinearity is proposed. The numerical instability of the sequential linear programming method is a well-known topic. The stabilized sequential linear programming method, which realizes the stabilized convergence characteristics of an objective function, is proposed and investigated in the 3-D design problem of a magnetic circuit.

Crank block steering mechanism optimization, which is a nonlinear constrained optimization problem, is important for forklift truck to get preferable steering performance. Vector particle swarm optimization (VPSO) is a swarm intelligent algorithm proposed to solve constrained optimization problems with simple concept and easy implementation. Therefore, VPSO was proposed to optimize crank block steering mechanism of forklift truck in this paper, which will be intended for minimizing the maximal error of outer wheel steering angle, maximizing the minimal transmission angle and making the transmission capability of the force better. The experimental results obtained by VPSO are compared with the results obtained by enumeration algorithm which are reliable for optimization problems. The comparison results showed that vector particle swarm optimization can get same optimal results as enumeration algorithm in much less calculation times.

In this paper, we compare two multi-objective evolutionary algorithms by solving bi-objective linear and nonlinear constrained optimization problems. The problems considered are three instances of a realistic crop planning problem. The multiobjective algorithms compared are a well-known multi-objective evolutionary algorithm NSGAII and our own algorithm MCA. We discuss the solutions obtained and analyse the sensitivity of variables for multi-objective solutions. From our analysis, it can be concluded that there is still room for improvement in the performance of the evolutionary optimization algorithms for some of these optimization problems

A constrained linear quadratic optimization algorithm toward jerk-decoupling cartridge design

This study investigates the optimal power flow (OPF) problem for distribution networks with the integration of distributed generation (DG). By considering the objectives of minimal line loss, minimal voltage deviation and maximum DG active power output, the proposed OPF formulation is a multi‐object optimisation problem. Through normalisation of each objective function, the multi‐objective optimisation is transformed to single‐objective optimisation. To solve such a non‐convex problem, the trust‐region sequential quadratic programming (TRSQP) method is proposed, which iteratively approximates the OPF by a quadratic programming with the trust‐region guidance. The TRSQP utilises the sensitivity analysis to approximate all the constraints with linear ones, which will reduce the optimisation scale. Active set method is utilised in TRSQP to solve quadratic programming sub‐problem. Numerical tests on IEEE 33‐, PG&E 69‐ and actual 292‐, 588‐, 1180‐bus systems show the applicability of the proposed method, and comparisons with the primal–dual interior point method and sequential linear programming method are provided. The initialisation and convergence condition of the proposed method are also discussed. The computational result indicates that the proposed algorithm for DG control optimisation in distribution system is feasible and effective.

In this paper, we consider a general class of nonlinear mixed discrete programming problems. By introducing continuous variables to replace the discrete variables, the problem is first transformed into an equivalent nonlinear continuous optimization problem subject to original constraints and additional linear and quadratic constraints. Then, an exact penalty function is employed to construct a sequence of unconstrained optimization problems, each of which can be solved effectively by unconstrained optimization techniques, such as conjugate gradient or quasi-Newton methods. It is shown that any local optimal solution of the unconstrained optimization problem is a local optimal solution of the transformed nonlinear constrained continuous optimization problem when the penalty parameter is sufficiently large. Numerical experiments are carried out to test the efficiency of the proposed method.