Stability enhancement of multi-machine power systems using Ant colony optimization-based static Synchronous Compensator

Kumar, Rajeev; Singh, Rajveer; Ashfaq, Haroon

doi:10.1016/j.compeleceng.2020.106589

Cited by 54 publications

(20 citation statements)

References 20 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…More importantly, to improve efficiency, we propose to apply the ACO to find a near-optimal solution. ACO has been widely applied in many fields (e.g., [16][17][18]).…”

Section: Stage Ii: Ant Colony Optimization Algorithm (Aco)mentioning

confidence: 99%

See 1 more Smart Citation

A Two-Stage Method for Target Searching in the Path Planning for Mobile Robots

Song

Huo

2020

Sensors

View full text Add to dashboard Cite

The path planning for target searching in mobile robots is critical for many applications, such as warehouse inspection and caring and surveillance for elderly people in the family scene. To ensure visual complete coverage from the camera equipped in robots is one of the most challenging tasks. To tackle this issue, we propose a two-stage optimization model to efficiently obtain an approximate optimal solution. In this model, we first develop a method to determine the key locations for visual complete coverage of a two-dimensional grid map, which is constructed by drawing lessons from the method of corner detection in the image processing. Then, we design a planning problem for searching the shortest path that passes all key locations considering the frequency of target occurrence. The testing results show that the proposed algorithm can achieve the significantly shorter search path length and the shorter target search time than the current Rule-based Algorithm and Genetic Algorithm (GA) in various simulation cases. Furthermore, the results show that the improved optimization algorithm with the priori known frequency of occurrence of the target can further improve the searching with shorter searching time. We also set up a test in a real environment to verify the feasibility of our algorithm.

show abstract

“…More importantly, to improve efficiency, we propose to apply the ACO to find a near-optimal solution. ACO has been widely applied in many fields (e.g., [16][17][18]).…”

Section: Stage Ii: Ant Colony Optimization Algorithm (Aco)mentioning

confidence: 99%

“…The ants are randomly placed at different starting locations. Each ant (θ(θ = 1, • • • , M)) determines the next location ∈ Ω to visit based on the probability χ θ i,j (t) calculated by Equations (18) and (19) until all the ants have reached all locations ∈ Ω.…”

mentioning

confidence: 99%

A Two-Stage Method for Target Searching in the Path Planning for Mobile Robots

Song

Huo

2020

Sensors

View full text Add to dashboard Cite

show abstract

“…The concept of reducing multiple machine control into multiple single machine control has been introduced by decentralized nonlinear model predictive control approach, and power system oscillation damping has been achieved [7]. An ant-colony based STATCOM has been suggested for the power system stability enhancement in a multi-machine power system [8]. The proposed optimization method has been tested for the different system disturbances and the successful oscillation damping has been achieved.…”

Section: Introductionmentioning

confidence: 99%

Power and energy system oscillation damping using multi-verse optimization

Devarapalli

Bhattacharyya

2021

SN Appl. Sci.

View full text Add to dashboard Cite

Power system oscillations are the primary threat to the stability of a modern power system which is interconnected and operates near to their transient and steady-state stability limits. Power system stabilizer (PSS) is the traditional controller to damp such oscillations, and flexible AC transmission system (FACTS) devices are advised for the improved damping performance. This paper suggests a technique for controller parameters tuning of PSS and a shunt connected FACTS device to be operated in coordination. A static synchronous compensator (STATCOM) connected in a two-machine system is considered as a test power system for the system studies. A recent meta-heuristic algorithm, Multi-Verse optimizer (MVO) has been suggested and compared with the other state-of-the-art algorithms. Improvement in system damping has been achieved by minimizing the oscillating nature of the system states by framing the objective function as a function of damping ratio and location of poles of the system. The Phillips-Heffron model of the test system has been designed by considering the system dynamics. The coordinated system behavior under the perturbation in system parameters has been observed satisfactory with the tuned controller parameters obtained from the suggested algorithm.

show abstract

“…Ant colony optimization (ACO), a new meta-heuristic algorithm has been used for the optimum solutions of power system problems like economic power dispatch and power system stabilization [20], [21]. Recently ACO algorithm has been used for optimal tuning of gain parameters to enhance the stability of multi-machine power systems [22] Also, ACO has been used to get the optimal parameters of controller for disturbance rejection in induction motor and magnetic levitation control system respectively [23], [24]. Therefore, it is decided to use ant colony optimization method in order to get optimum disturbance rejection in VSC -MTDC network.…”

Section: Introductionmentioning

confidence: 99%

Controller Parameters Optimization for Multi-Terminal DC Power System Using Ant Colony Optimization

et al. 2021

View full text Add to dashboard Cite

Voltage source converter based multi -terminal DC grids (VSC -MTDC) are widely used for integration of renewable resources. Control of these grids requires vector control method, which includes inner and outer current controllers, tuning of these controllers is very important. Conventionally used tuning methods consider approximated linear model to tune the proportional -integral (PI) parameters of voltage source converter (VSC) which fails to produce optimum disturbance rejection results. In this research an Ant Colony Optimization (ACO) technique is used to get the optimum parameters of inner and outer power control layers for multi -terminal DC system. ACO is applied simultaneously on inner and outer control layers and results are compared with classical tuning method and well established meta -herustic technique, Particle Swarm Optimization (PSO) using MATLAB software. Dynamic models of VSC -MTDC are developed in PSCAD/EMTDC to exalt the qualities of the presented tuning method. In this paper, a four terminal VSC -MTDC has been used under different sequence of events of disturbances e.g. load change on AC side, active power reference change for inverter and rectifier mode and disconnection of one terminal to evaluate the robustness of ACO algorithm with respect to classical method. The proposed tuning method gives superior results under different disturbance compared to conventional method.

show abstract

Stability enhancement of multi-machine power systems using Ant colony optimization-based static Synchronous Compensator

Cited by 54 publications

References 20 publications

A Two-Stage Method for Target Searching in the Path Planning for Mobile Robots

A Two-Stage Method for Target Searching in the Path Planning for Mobile Robots

Power and energy system oscillation damping using multi-verse optimization

Controller Parameters Optimization for Multi-Terminal DC Power System Using Ant Colony Optimization

Contact Info

Product

Resources

About