Related Experiment Video
Updated: Apr 20, 2026
11:53
Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm
Published on: December 9, 2012
13.6K
An optimal multi-objective paradigm for trade-off between strategic PMU deployment and enhanced state estimation
K Anand1, Tapan Prakash1, Himadri Lala2
1School of Electrical Engineering, Vellore Institute of Technology, Vellore, 632001, India.
Scientific Reports
|April 18, 2026
Summary
This study optimizes power grid visibility by strategically deploying Phasor Measurement Units (PMUs). The new multi-objective approach balances deployment costs and state estimation accuracy for improved grid management.
Area of Science:
- Electrical Engineering
- Power Systems Analysis
Background:
- Strategic deployment of Phasor Measurement Units (PMUs) is crucial for grid visibility and cost reduction.
- Balancing PMU deployment with state estimation accuracy presents a significant challenge in power system operations.
Purpose of the Study:
- To introduce a novel multi-objective paradigm for optimizing the strategic PMU deployment (SDP) problem.
- To enhance the balance between grid visibility, state estimation accuracy, and deployment costs.
Main Methods:
- Utilized a multi-objective Brown Bear optimization (MBOA) algorithm for SDP.
- Employed weighted least squares (WLS) for state estimation and Newton-Raphson for load flow analysis.
- Evaluated state estimation error by comparing WLS results with and without SDP data.
Main Results:
- The proposed paradigm achieved a superior balance between SDP, maximum redundancy, and state estimation accuracy.
- MBOA demonstrated better performance compared to other multi-objective algorithms on IEEE 30-bus and Polish 2383-bus systems.
- The Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and Wilcoxon signed-rank test validated the approach's superiority.
Conclusions:
- The developed multi-objective paradigm effectively addresses the trade-offs in PMU deployment and state estimation.
- MBOA is a highly effective optimization technique for the strategic PMU deployment problem in power systems.
Related Concept Videos
01:29Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving
415
Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
415
01:28Methods of Medium Optimization
63
Optimizing growth media enhances microbial proliferation and maximizes product yield. Statistical experimental design methodologies provide structured and reproducible approaches, offering progressively higher levels of robustness and efficiency.The One-Factor-at-a-Time (OFAT) MethodThe One-Factor-at-a-Time (OFAT) method involves adjusting a single variable while keeping all others constant. However, it cannot detect interactions between variables, often leading to suboptimal outcomes when...
63
01:09Decision Making: P-value Method
7.5K
The process of hypothesis testing based on the P-value method includes calculating the P- value using the sample data and interpreting it.
First, a specific claim about the population parameter is proposed. The claim is based on the research question and is stated in a simple form. Further, an opposing statement to the claim is also stated. These statements can act as null and alternative hypotheses: a null hypothesis would be a neutral statement while the alternative hypothesis can...
First, a specific claim about the population parameter is proposed. The claim is based on the research question and is stated in a simple form. Further, an opposing statement to the claim is also stated. These statements can act as null and alternative hypotheses: a null hypothesis would be a neutral statement while the alternative hypothesis can...
7.5K
01:25Multimachine Stability
633
Multimachine stability analysis is crucial for understanding the dynamics and stability of power systems with multiple synchronous machines. The objective is to solve the swing equations for a network of M machines connected to an N-bus power system.
In analyzing the system, the nodal equations represent the relationship between bus voltages, machine voltages, and machine currents. The nodal equation is given by:
In analyzing the system, the nodal equations represent the relationship between bus voltages, machine voltages, and machine currents. The nodal equation is given by:
633
01:24One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation
1.5K
This lesson introduces two critical methods in pharmacokinetics, the Wagner-Nelson and Loo-Riegelman methods, used for estimating the absorption rate constant (ka) for drugs administered via non-intravenous routes. The Wagner-Nelson method relates ka to the plasma concentration derived from the slope of a semilog percent unabsorbed time plot. However, it is limited to drugs with one-compartment kinetics and can be impacted by factors like gastrointestinal motility or enzymatic degradation.
On...
On...
1.5K