Constrained LAV State Estimation Using Penalty Functions
نویسندگان
چکیده
Inequality constraints are often needed in optimization problems in order to deal with uncertainty. This paper introduces a simple technique that allows enforcement of inequality constraints in `1 norm problems without any modi cations to existing programs. The solution of `1 norm problems is required, for example, in implementing LAV (Least Absolute Value) state estimators in electric power systems. The paper shows how LAV state estimators with inequality constraints can be useful for estimating the state of external systems. This is important in a competitive environment where precise information about a utility's neighboring systems may not be available.
منابع مشابه
The Integration of Multi-Factor Model of Capital Asset Pricing and Penalty Function for Stock Return Evaluation
One of the main concerns of investors is the evaluation of the return on investment, which is conducted using various models such as the CAPM (single-factor model), Fama-French three/five-factor models, and Roy and Shijin’s six-factor model and other models known as multi-factor models. Despite the widespread use of these models, their major drawbacks include sensitivity to unexpected changes, ...
متن کاملFast Approximations to Lav Solutions for State Estimation of Power Systems
This paper describes a fast and efficient technique to calculate approximate LAV (Least Absolute Value) solutions in power system state estimation. The method uses a two level approach in which accurate LAV solutions are obtained on a slower time scale and approximate LAV solutions are obtained by solving generalized power flows on a much faster time scale. These approximate LAV estimates, whic...
متن کاملProposing a Constrained-GSA for the Vehicle Routing Problem
In the past decades, vehicle routing problem (VRP) has gained considerable attention for its applications in industry, military, and transportation applications. Vehicle routing problem with simultaneous pickup and delivery is an extension of the VRP. This problem is an NP-hard problem; hence finding the best solution for this problem which is using exact method, take inappropriate time, and th...
متن کاملA Study of Adaptive Penalty Functions for Constrained Genetic Algorithm- Based Optimization
Constrained optimization via the Genetic Algorithm (GA) is often a challenging endeavor, as the GA is most directly suited to unconstrained optimization. Traditionally, external penalty functions have been used to convert a constrained optimization problem into an unconstrained problem for GA-based optimization. This approach requires the somewhat arbitrary selection of penalty draw-down coeffi...
متن کاملSuperlinearly convergent exact penalty projected structured Hessian updating schemes for constrained nonlinear least squares: asymptotic analysis
We present a structured algorithm for solving constrained nonlinear least squares problems, and establish its local two-step Q-superlinear convergence. The approach is based on an adaptive structured scheme due to Mahdavi-Amiri and Bartels of the exact penalty method of Coleman and Conn for nonlinearly constrained optimization problems. The structured adaptation also makes use of the ideas of N...
متن کامل