Trade-offs in PMU and IED Deployment for Active Distribution State Estimation Using Multi-objective Evolutionary Algorithm

2018 ◽  
Vol 67 (6) ◽  
pp. 1298-1307 ◽  
Author(s):  
Sachidananda Prasad ◽  
D. M. Vinod Kumar
Keyword(s):  
Evolutionary Algorithm ◽  
State Estimation ◽  
Multi Objective ◽  
Trade Offs ◽  
Distribution State

scholarly journals An Evolutionary Algorithm with Advanced Goal and Priority Specification for Multi-objective Optimization

2003 ◽  
Vol 18 ◽  
pp. 183-215 ◽  
Author(s):  
K. C. Tan ◽  
E. F. Khor ◽  
T. H. Lee ◽  
R. Sathikannan
Keyword(s):  
Control System ◽  
Evolutionary Algorithm ◽  
Population Distribution ◽  
Hard Disk Drives ◽  
Voice Coil Motor ◽  
Servo Control ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Servo Control System ◽  
Trade Offs

This paper presents an evolutionary algorithm with a new goal-sequence domination scheme for better decision support in multi-objective optimization. The approach allows the inclusion of advanced hard/soft priority and constraint information on each objective component, and is capable of incorporating multiple specifications with overlapping or non-overlapping objective functions via logical 'OR' and 'AND' connectives to drive the search towards multiple regions of trade-off. In addition, we propose a dynamic sharing scheme that is simple and adaptively estimated according to the on-line population distribution without needing any a priori parameter setting. Each feature in the proposed algorithm is examined to show its respective contribution, and the performance of the algorithm is compared with other evolutionary optimization methods. It is shown that the proposed algorithm has performed well in the diversity of evolutionary search and uniform distribution of non-dominated individuals along the final trade-offs, without significant computational effort. The algorithm is also applied to the design optimization of a practical servo control system for hard disk drives with a single voice-coil-motor actuator. Results of the evolutionary designed servo control system show a superior closed-loop performance compared to classical PID or RPT approaches.

scholarly journals Multi-Objective Optimisation of the Energy Performance of Lightweight Constructions Combining Evolutionary Algorithms and Life Cycle Cost

Energies ◽  
2018 ◽  
Vol 11 (7) ◽  
pp. 1863 ◽  
Author(s):  
Rui Oliveira ◽  
António Figueiredo ◽  
Romeu Vicente ◽  
Ricardo Almeida
Keyword(s):  
Life Cycle ◽  
Evolutionary Algorithm ◽  
Life Cycle Cost ◽  
Goodness Of Fit ◽  
Energy Performance ◽  
Department Of Energy ◽  
United States Department ◽  
Front Solution ◽  
Multi Objective ◽  
Trade Offs

This paper discusses the thermal and energy performance of a detached lightweight building. The building was monitored with hygrothermal sensors to collect data for building energy model calibration. The calibration was performed using a dynamic simulation through EnergyPlus® (EP) (Version 8.5, United States Department of Energy (DOE), Washington, DC, USA) with a hybrid evolutionary algorithm to minimise the root mean square error of the differences between the predicted and real recorded data. The results attained reveal a good agreement between predicted and real data with a goodness of fit below the limits imposed by the guidelines. Then, the evolutionary algorithm was used to meet the compliance criteria defined by the Passive House standard for different regions in Portugal’s mainland using different approaches in the overheating evaluation. The multi-objective optimisation was developed to study the interaction between annual heating demand and overheating rate objectives to assess their trade-offs, tracing the Pareto front solution for different climate regions throughout the whole of Portugal. However, the overheating issue is present, and numerous best solutions from multi-objective optimisation were determined, hindering the selection of a single best option. Hence, the life cycle cost of the Pareto solutions was determined, using the life cycle cost as the final criterion to single out the optimal solution or a combination of parameters.

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