Optimization of Multi Objective Load Frequency Control Using Cuckoo Search Algorithm

Micro hydro has been chosen because it has advantages both economically, technically and as well as in terms of environmental friendliness. Micro hydro is suitable to be used in areas that difficult to be reached by the grid. Problems that often occur in the micro hydro system are not the constant rotation of the generator that caused by a change in load demand of the consumer. Thus causing frequency fluctuations in the system that can lead to damage both in the plant and in terms of consumer electrical appliances. The appropriate control technology should be taken to support the optimum performance of micro hydro. Therefore, this study will discuss a strategy of load frequency control by using Energy Storage. Superconducting magnetic energy storage (SMES) and capacitor energy storage (CES) are devices that can store energy in the form of a fast magnetic field in the superconducting coil. For the optimum performance, it is necessary to get the optimum tuning of SMES and CES parameters. The artificial intelligence methods, Cuckoo Search Algorithm (CSA) are used to obtain the optimum parameters in the micro hydro system. The simulation results show that the application of the CSA that use to tune the parameters of hybrid SMES-CES-PID can reduce overshoot oscillation of frequency response in micro hydro power plant.

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Optimizing Voltage Profile and Loss Minimization using Multi Objective Cuckoo Search Algorithm

2021 IEEE 11th IEEE Symposium on Computer Applications & Industrial Electronics (ISCAIE) ◽

10.1109/iscaie51753.2021.9431835 ◽

2021 ◽

Author(s):

Mohamad Izwan Zainal ◽

Zuhaila Mat Yasin ◽

Zuhaina Zakaria

Keyword(s):

Search Algorithm ◽

Cuckoo Search ◽

Cuckoo Search Algorithm ◽

Voltage Profile ◽

Loss Minimization ◽

Multi Objective

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Optimization strategy of wireless charger node deployment based on improved cuckoo search algorithm

EURASIP Journal on Wireless Communications and Networking ◽

10.1186/s13638-021-01951-1 ◽

2021 ◽

Vol 2021 (1) ◽

Author(s):

Yang Wang ◽

Feifan Wang ◽

Yujun Zhu ◽

Yiyang Liu ◽

Chuanxin Zhao

Keyword(s):

Sensor Network ◽

Sensor Node ◽

Search Algorithm ◽

Optimal Solution ◽

Cuckoo Search ◽

Cuckoo Search Algorithm ◽

Sensor Nodes ◽

Optimization Strategy ◽

Multi Objective ◽

Received Power

AbstractIn wireless rechargeable sensor network, the deployment of charger node directly affects the overall charging utility of sensor network. Aiming at this problem, this paper abstracts the charger deployment problem as a multi-objective optimization problem that maximizes the received power of sensor nodes and minimizes the number of charger nodes. First, a network model that maximizes the sensor node received power and minimizes the number of charger nodes is constructed. Second, an improved cuckoo search (ICS) algorithm is proposed. This algorithm is based on the traditional cuckoo search algorithm (CS) to redefine its step factor, and then use the mutation factor to change the nesting position of the host bird to update the bird’s nest position, and then use ICS to find the ones that maximize the received power of the sensor node and minimize the number of charger nodes optimal solution. Compared with the traditional cuckoo search algorithm and multi-objective particle swarm optimization algorithm, the simulation results show that the algorithm can effectively increase the receiving power of sensor nodes, reduce the number of charger nodes and find the optimal solution to meet the conditions, so as to maximize the network charging utility.

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