Cyber-Physical Power System Multi-Objective Planning Algorithm with NSGA-II

2021 ◽  
Author(s):  
Keren Chen ◽  
Nan Zheng ◽  
Qiyuan Cai ◽  
Changyong Lin ◽  
Yuanfei Li ◽  
...  
Keyword(s):  
Power System ◽  
Nsga Ii ◽  
Multi Objective ◽  
Planning Algorithm

Multi-Objective Economic Environmental Dispatch of Variable Hydro-Wind-Thermal Power System

2021 ◽  
Vol 12 (2) ◽  
pp. 16-35
Author(s):  
Suman Kumar Dey ◽  
Deba Prasad Dash ◽  
Mousumi Basu
Keyword(s):  
Power System ◽  
Thermal Power ◽  
Nox Emission ◽  
Fuel Cost ◽  
Nsga Ii ◽  
So2 Emission ◽  
Emission Level ◽  
Multi Objective ◽  
Thermal Power System ◽  
Operational Constraints

This article presents a multi-objective economic environmental/emission dispatch (EED) of variable head hydro-wind-thermal power system. The combination of NOx emission, SO2 emission, and fuel cost are minimized for non-smooth hydrothermal plants while satisfying various operational constraints like non-smooth fuel cost, penalty coefficient, and wind power uncertainty. The objectives—cost, NOx emission, and SO2 emission—are optimized at the same time. In this research, the non-dominated sorting genetic algorithm-II (NSGA-II) has been employed for solving the given problem where the total cost, NOx emission level, and SO2 emission level are optimized at the same time while satisfying all the operational constraints. The simulation results that are obtained by applying the two test systems on the proposed scheme have been evaluated against strength pareto evolutionary algorithm 2 (SPEA 2).

scholarly journals FACTS location and size for reactive power system compensation through the multi-objective optimization

2010 ◽  
Vol 20 (4) ◽  
pp. 473-489 ◽  
Author(s):  
Messaoud Belazzoug ◽  
Mohamed Boudour ◽  
Karim Sebaa
Keyword(s):  
Power System ◽  
Reactive Power ◽  
Test System ◽  
Load Flow ◽  
Electrical Network ◽  
Multi Objective Optimization ◽  
Nsga Ii ◽  
Flow Equations ◽  
Multi Objective ◽  
System Compensation

FACTS location and size for reactive power system compensation through the multi-objective optimizationThe problem of the FACTS (Flexible Alternative Current Transmission System Devices) location and size for reactive power system compensation through the multi-objective optimization is presented in this paper. A new technique is proposed for the optimal setting, dimension and design of two kinds of FACTS namely: Static Volt Ampere reactive (VAR) Compensator (SVC) and Thyristor Controlled Series Compensator (TCSC) handling the minimization of transmission losses in electrical network. Using the proposed scheme, the type, the location and the rating of FACTS devices are optimized simultaneously. The problem to solve is multi criteria under constraints related to the load flow equations, the voltages, the transformer turn ratios, the active and reactive productions and the compensation devices. Its solution requires the the advanced algorithms to be applied. Thus, we propose an approach based on the evolutionary algorithms (EA) to solve multi-criterion problem. It is similar to the NSGA-II method (Ellitist Non Dominated Sorting Genetic Algorithm). The Pareto front is obtained for continuous, discrete and multiple of five MVArs (Mega Volt Ampere reactive) of compensator devices for the IEEE 57-bus test system (IEEE bus test is a standard network).

A New Method for Network Reconfiguration of the Shipboard Power System

2013 ◽  
Vol 347-350 ◽  
pp. 1283-1287
Author(s):  
Xuan Fang Yang ◽  
Jia Lin Wang
Keyword(s):  
Power System ◽  
Optimal Algorithm ◽  
Network Reconfiguration ◽  
Test Results ◽  
Nsga Ii ◽  
Multi Objective ◽  
Shipboard Power System ◽  
Shipboard Power ◽  
Switch Operation ◽  
Integrated Power System

The Multi-objective Optimal AlgorithmNSGA-II for Network reconfiguration of the shipboard power system is proposed to overcome the shortcomings of single objective optimal algorithm. This paper chooses the least of lost loads and cost of switch operation as objective function, uses capacity and structure as constraints, codes two-dimensional gene with switch and uses NSGA-II to solve the multi-objective and multi-restriction network reconfiguration problem. The test results of a typical integrated power system show that the model can balance each objective to avoid extreme results, which make restoration schemes more practical.

Fuzzy multi-objective location and routing problem

2020 ◽  
Vol 39 (3) ◽  
pp. 3259-3273
Author(s):  
Nasser Shahsavari-Pour ◽  
Najmeh Bahram-Pour ◽  
Mojde Kazemi
Keyword(s):  
Firefly Algorithm ◽  
High Reliability ◽  
Research Area ◽  
Nsga Ii ◽  
Location Routing Problem ◽  
Routing Problem ◽  
Location Allocation ◽  
Multi Objective ◽  
Location Routing ◽  
The Cost

The location-routing problem is a research area that simultaneously solves location-allocation and vehicle routing issues. It is critical to delivering emergency goods to customers with high reliability. In this paper, reliability in location and routing problems was considered as the probability of failure in depots, vehicles, and routs. The problem has two objectives, minimizing the cost and maximizing the reliability, the latter expressed by minimizing the expected cost of failure. First, a mathematical model of the problem was presented and due to its NP-hard nature, it was solved by a meta-heuristic approach using a NSGA-II algorithm and a discrete multi-objective firefly algorithm. The efficiency of these algorithms was studied through a complete set of examples and it was found that the multi-objective discrete firefly algorithm has a better Diversification Metric (DM) index; the Mean Ideal Distance (MID) and Spacing Metric (SM) indexes are only suitable for small to medium problems, losing their effectiveness for big problems.

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