An Ant Colony Optimized MPPT with Single Cuk Converter for Standalone Hybrid PV-Wind Power Generation for Residential Applications and Changing Operating Conditions

This research work explains the practical realization of hybrid solar wind based standalone power system with maximum power point tracker (MPPT) to produce electrical power in rural places (residential applications). The solar inspired Ant Colony Optimization (ACO) based MPPT algorithm is employed for the purpose of fast and accurate tracking power from solar and wind system. Fuzzy Logic Control (FLC) inverter controlling strategy is adopted in this presented work compared to classical PI control. Moreover, single Cuk converter is operated as impedance power adapter to execute MPPT functioning. Satisfactory practical results have been realized using dSPACE (DS1104) platform that justify the superiority of proposed algorithms designed under various operating situations.

PSO technique consists of large number of iterations which results diversion from MPP with slow updating speed.Belhachat et.al [16] has combined the performance of various MPPT techniques, which reveals that ANT Colony Optimization (ACO) method has relatively simpler implementation, very fast tracking velocity and high efficiency compared to other algorithms discussed in literature.Sundeswaran et al. [17] has implemented cascaded P & O assisted ANT Colony Optimization (ACO) method for rapid PV power tracking using PIC16F876A microcontroller.Under partial shading situations, the behavior has been examined which provides fast global searching and convergence.However, authors have discussed proposed MPPT algorithm for particular PV system power generation.Emerson et al. [18] presented ACO algorithm for PV-fuel cell integration with islanding employed with boost converter.However, there is no experimental work carried out for the system verification and analysis of power quality issues.In this paper, an ANT Colony Optimization based MPPT technique has been employed to get acceptable solutions in non-linear operating conditions compared to other method discussed in literature.The ACO based MPPT provides rapid battery changing operation with lesser dispersion of battery for hybrid PV-wind power system.
Several DC-DC converters have been reviewed for MPPT purpose, which is responsible for load matching and converts peak powers from renewable sources to load.Generally, buck, boost, buck-boost, SEPIC, Zeta, Cuk converters are considered dc-dc converters for MPPT operation which accomplish impedance balance between renewable sources and load [19][20].Buck boost converters are unable to handle MPPT operations under changing weather conditions.Moreover, compared to SEPIC and Cuk converters, buck ,boost, buck-boost and Zeta converter require high cost driver circuits with supplementary blocked diode for preventing reversal current from battery.
Equated with presented dc-dc converter topologies, Cuk converter is adequate to provide MPPT operation through entire PV/wind characteristics under every changing operating conditions with less input current ripple and inverted output.Particular power converters with battery back up have been used for hybrid PV-wind power generation systems implementations.Furthermore, individual powers converters are regulated with multiplex methods for optimal power generation which consequence conduction and switched loss in power converters.
In this research work, a single Cuk converter is employed for improvement of power conversion efficiency by reducing the power level translation.Moreover, in this hybrid PV-wind system, a Cuk converter is straightly coupled with DC link voltage rather than using dc-dc converter.The Cuk converter is placed between PMSG coupled rectifier and inverter, which is responsible DC, link voltage regulations.The Cuk converters output acts as a load line to the solar module.With the application of FLC current controller, the inverter current can be regulated using PV-wind systems [21].However, in traditional topology the dc-dc converter is employed after PV module for optimal tracking of power.
Included work, based on ACO MPPT has no requirement of supplement circuitry with voltage/current sensors and independent system responses compared to different evolutionary techniques used.Novelty of this research paper is MPPT action with ACO technique followed by FLC inverter controller for residential PV-Wind power generation has neither been discussed nor implemented experimentally under changing operating conditions with single Cuk converter as an impedance balancer using dSPACE (DS1104) platform.The equivalent mode of PV cell presented in Fig. 2 (a) comprises current source, diode and series/parallel resistances.

2.Complete Schematic of PV-Wind System
The mathematical equations describing output current ( ) based on the electrical circuits can be derived with used abbreviations [22] as: Also, can be expressed mathematically as [22]: The output current is equated finally with used abbreviations [22] as: Non-linear P-V/I-V curves at different weather profiles (irradiance and temperature) are presented clearly in Fig. 2(b) and (c), respectively.For achieving Global Maximum Point (GMP) at every operation, in this work Cukconverter is employed.

PMSG Modeling
To describe the operation of PV-Wind system under intermittent operating conditions, Permanent Magnet Synchronous Generator is employed because of zero reactive power consumption.In addition, it does not have need of gearbox with better power factor and accuracy due to self-execution behavior.The PMSG model has been developed using steady current depicted in Fig. 2 (d).Voltage and current ( & ) obtained from rectification is expressed [1] mathematically with regard to stator voltage/current ( , ).

Mathematical Modeling of Wind Turbine System
The produce power rating of wind turbine based on aerodynamic behavior is evaluated mathematically as Where,

= Pitch blade angle
The turbine tip speed is correlated with wind velocity and wind turbine rotating velocity as: The power coefficient ( , ) is calculated using mathematical relation as: Also, Mechanical torque developed using wind turbine is related with produced mechanical power as: The mechanical relation governing wind turbine system is expressed mathematically as: = Viscous force = Developed electromagnetic torque Mathematical Modeling of PMSG in dq frame is described as: Where, Fig. 3 (a) presents the generated power from wind turbine with rotor speed under variable velocity.Also, the power factor Vs rotor speed with varying wind speed characteristics in Fig. 3(b) demonstrates the optimal power produced from wind turbine achieves at optimal power factor coefficient corresponding.In this research work, electric circuit based battery model is employed which provides better dynamicity for state of charge approximation.It comprises voltage source (ideal) with series internal resistance, which evaluates battery behavior, depicted using Fig. 3 (c).A Battery (Ni-Cd) discharging characteristic is presented with Fig. 3(d) [22].

Electric Circuit based Battery Model
Final voltage controlled is obtained mathematically as:

Cuk Converter
The major disadvantages of switched mode power converters have discontinuity of supply current, low dynamic response and higher power device peak current, which made this less acceptable.In contrast with classical switched mode dc-dc converter, Cuk converter comprises less switched power loss, high current behavior with better efficiency, which acts as a power adapter between inverter and renewable sources.
The Cuk converter operation presented in Fig. 4(a) is described in two working modes.When power switch gets short-circuited and energy has been released by capacitor.Table 1 presents the specifications used during design of Cuk converter.The mathematical expression-governing mode-I conducting state is described as:

ANT colony optimization based MPPT
Colorni, Dorigo and Maniezzo invented meta-heuristics based optimized algorithm to solve difficult nonlinear issues.The particular ant to obtain the shortest path optimization generates pheromones.For the searching of foods, the movements of ants take place in different direction followed with generated pheromones.The shortest path should have high pheromones probability as it evaporates in short and methodology is repeated for different iterations to optimize the problems.
In this research work, ACO methodology is implemented by considering VPV and IPV followed by generation of target output (VTarget).Ants have been situated randomly and its movement is noted to achieve VTarget which returns to the colony after this process.Moreover, the VTarget and colony distance is treated as duty ratio of Cuk converter.Let AP variables have targeted to optimize which comprises YP produced randomly solutions (YP>=AP).Sampling Gaussian Kernel methodology is used for mathematical description as [16][17][18]: The proposed sample Process is repeated for optimization of parameters.Let ZP newly solution are produced and has addition with YP initially obtained solution.Total ZP+YP solutions have been obtained in which YP best are replicated and overall methodology is recapitulated for several iterations.Table 2 shows ACO parameters used during practical verification.This methodology is stimulated by foraging nature of ants, which are treated as blind living things, and conversion among them takes place-using pheromone alchemical.It comprises positive feedback affection, which provides better-optimized solutions.

FLC based inverter control
The inverter depicted in Fig. 4 CASE II:In case of power generation from only wind renewable sources (Not PV), the duty ratio of Cuk converter is generated to make DC link voltage fixed and controller 1 works in voltage control mode.In addition to this controller 2 tries to obtain optimal wind power by generating current signal.
CASE III:When PMSG is not in operation and only PV sources are generating power, Cuk converter has no input and there is no pulse generation using controller 1. Controller 2 produces current command signal to obtain optimal PV power generation from PV modules.

Experimental responses
Practical justification is done by comparing power tracking behavior of ACO algorithm Vs PSO, FA and ABC techniques using Fig. 5 (C).The average period required to achieve MPP is presented with comparison using Table 3.
The ACO based MPPT method takes lesser time compared to other algorithms mentioned.Moreover, the duty ratio performance with ACO MPPT is better compared to other techniques employed in Fig. 5  The steady state behavior of the designed PV system is also examined and is justified with matched PV characteristics depicted by Fig. 6(B).By means of proposed intelligent ACO, the inverter current becomes synchronized and in phase with grid utility voltage depicted by responses in Fig. 6(C).The dynamic performance of ACO based PV power system has been justified with variations in fluctuating sun insolation and can be depicted in Fig. 6(D).Fig. 7(a) demonstrates the responses obtained from hybrid PV-wind controlled ACO, which clearly interprets that MPPT operation is achieved independently without influencing one another.MPPT control has been practically substantiated using dSPACE interface.Table 4 demonstrates the used PV and Wind turbine specifications for practical justification.

Conclusion
Under extreme varying environmental conditions, the ACO based optimized methodology provides optimal power extraction from solar and wind energy sources for residential applications, which contained high convergence velocity, better-searched performance and simpler implementation as major advantage.The completed hybrid solar wind driven PMSG power system is modeled through MATLAB and provides hardware interface (dSPACE) for validation and confirmation of high power generation.Under low wind velocity, the hybrid system has low battery consumption, which demonstrates the improved controller performance.Inverter regulated with FLC-dSPACE control has power efficiency equated with classical PI-controller.The hybrid integration of solar and wind energy system have been realized experimentally under various conditions to develop novel hybrid power system followed by Cukconverter.ACO algorithms developed using m-file has complex coding interfaced to dSPACE hardware board.Included work can be extended to learning framework with internet of things based intelligent algorithms for PV-Wind hybrid system to achieve utmost power tracking efficiency.

Fig. 1
Fig. 1 demonstrates standalone hybrid PV-wind-Battery power system comprises of PV modules, PMSG based WECS, battery, voltage source inverter (VSI) and load.The ACO based MPPT is employed with single Cuk converter is operating in hybrid power generation for residential application.FLC-dSPACE based controller is used for inverter voltage regulation to retain inverter voltage regulation and frequency invariable.The employed Cuk converter imparts consistent DC link voltage for charging of battery by application of ACO MPPT.

=
Amplitude of exponential zone = Inverse time constant exponential zone

Figure 3 .
Figure 3.(a)Battery (Ni-cd) discharging behavior (b)Cuk converter (c) Inverter control (d) FLC regulated inverter controller Mathematically mean, weight, standard deviations are derived with VP random solutions.Probability of Gaussian function selection = ∑

Figure 4 .
Figure 4. (a)FLC pulse generation (b) Membership functions Error (c) Membership functions change in error (d) Membership functions duty ratio 5. MPPT and inverter controller action with single Cuk converter CASE me: The two controllers operations are decided based on presence of PV/Wind renewable sources.In case of generation of power from PV as well as wind sources, the ACO based MPPT (controller 1) produces duty ratio for Cuk power converter and FLC inverter control (controller 2) provides power generation from PV and wind renewable sources.

Fig. 5 (Figure 5 .
Fig. 5(A) depicts the practical set up developed for proposed hybrid (PV-Wind) system controlled through dSPACE, which comprises PV module, wind emulator, Cuk converter, and electric circuit based battery model.

Figure 6 .Figure 7 .Figure 8 .Figure 9 .
Figure 6.(A) Starting operation PV MPPT (B) Steady state behavior of the designed PV system (C) Inverter current becomes synchronized and in phase with grid, utility voltage (D) ACO based PV power system with variations in fluctuating sun insolationThe intermittent behavior of PV-wind system with proposed methodology is accurately tested experimentally using proposed algorithm.Abruptly, the PV-wind power system has been turned ON/OFF and

Table 1 .
Cuk converter parametersIn case of power switch gets open circuited, the energy flow takes place with forward biasing diode and input supply is responsible to charge capacitor CA.Described mathematical relations of this mode of operations are:

Table 2 .
ACO parameters used during experiment

Table 4 .
PV and Wind turbine specifications