Towards fast state estimation using linear programming

1992 ◽  
Vol 23 (1) ◽  
pp. 41-45 ◽  
Author(s):  
A.A. El-Keib ◽  
H. Singh ◽  
A. Rubaai
Keyword(s):  
Linear Programming ◽  
State Estimation ◽  
Fast State

scholarly journals A Fast State Estimator for Integrated Electrical and Heating Networks

Energies ◽  
2020 ◽  
Vol 13 (17) ◽  
pp. 4488
Author(s):  
Chun Wang ◽  
Minghao Geng ◽  
Qingshan Xu ◽  
Haixiang Zang
Keyword(s):  
State Estimation ◽  
Balance Equation ◽  
Temperature Drop ◽  
Estimation Method ◽  
Energy Utilization ◽  
Utilization Efficiency ◽  
State Estimator ◽  
Estimation Model ◽  
Fast State ◽  
Heating Networks

Integrated electrical and heating networks (IEHNs) effectively improve energy utilization efficiency, reduce environmental pollution and realize sustainable development of energy. To realize the accurate, comprehensive and fast perception of the integrated electrical and heating networks, it is necessary to build a state estimation model. However, the robust state estimator of IEHNs based on the temperature drop equation, flow balance equation and power balance equation still have the problems of convergence and low computational efficiency. In this paper, a fast state estimation method based on weighted least absolute value is proposed, which makes partition calculation of ring-shaped heating network and radiant heating network under certain assumptions. Simulation results show that the method improves the efficiency of the robust state estimator on the premise of high accuracy.

scholarly journals AN ALGEBRAIC STATE ESTIMATION APPROACH FOR THE RECOVERY OF CHAOTICALLY ENCRYPTED MESSAGES

2006 ◽  
Vol 16 (02) ◽  
pp. 295-309 ◽  
Author(s):  
HEBERTT SIRA-RAMÍREZ ◽  
MICHEL FLIESS
Keyword(s):  
State Estimation ◽  
Chaotic System ◽  
Estimation Method ◽  
Algebraic Approach ◽  
Secret Message ◽  
Fast Time ◽  
Fast State ◽  
Computation Process ◽  
System States ◽  
Signal Time

In this article, we use a variant of a recently introduced algebraic state estimation method obtained from a fast output signal time derivatives computation process. The fast time derivatives calculations are entirely based on the consequences of using the "algebraic approach" in linear systems description (basically, module theory and non-commutative algebra). Here, we demonstrate, through computer simulations, the effectiveness of the proposed algebraic approach in the accurate and fast (i.e. nonasymptotic) estimation of the chaotic states in some of the most popular chaotic systems. The proposed state estimation method can then be used in a coding–decoding process of a secret message transmission using the message-modulated chaotic system states and the reliable transmission of the chaotic system observable output. Simulation examples, using Chen's chaotic system and the Rossler system, demonstrate the important features of the proposed fast state estimation method in the accurate extraction of a chaotically encrypted messages. In our simulation results, the proposed approach is shown to be quite robust with respect to (computer generated) transmission noise perturbations. We also propose a way to evade computational singularities associated with the local lack of observability of certain chaotic system outputs and still carry out the encrypting and decoding of secret messages in a reliable manner.

Reliability value of fast state estimation on power systems

PES T&D 2012 ◽  
2012 ◽  
Author(s):  
Marcelo A. Elizondo ◽  
Yousu Chen ◽  
Zhenyu Huang
Keyword(s):  
Power Systems ◽  
State Estimation ◽  
Fast State

Linear Programming Approach for Power System State Estimation Using Upper Bound Optimization Techniques

2010 ◽  
Vol 11 (3) ◽  
Author(s):  
Thukaram Dhadbanjan ◽  
Seshadri Sravan Kumar Vanjari
Keyword(s):  
Linear Programming ◽  
State Estimation ◽  
Upper Bound ◽  
Measurement Errors ◽  
Large Scale ◽  
Optimization Technique ◽  
Optimization Techniques ◽  
Programming Approach ◽  
Linear Programming Approach ◽  
Bound Optimization

State estimation plays an important role in real time security monitoring and control of power systems. There are many problems in the implementation of state estimator for large scale networks due to measurement errors, weights given and the numerical ill-conditioning associated with the solution techniques. In this paper a new formulation using linear programming approach is presented. The formulation is devoid of weights and errors associated with the measurements are taken care of in constraints. The non linear problem is linearized at previous operating state and constraints are set up using flow mismatches. The implementation of the formulation exploits sparse features of the network matrices and avoids matrix inversions. Upper bound optimization technique is employed to solve the linear programming problem. Illustration of the proposed approach on sample 3-bus and 6-bus systems and a practical Indian Southern grid 72 bus equivalent system are presented.

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