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Author(s): Gajendra Singh Rathore, B. Gopal Krishna, R.N. Patel, Sanjay Tiwari


Address: Photonics Research Laboratory, School of Studies in Electronics & Photonics, Pt. Ravishankar Shukla University, Raipur, India
Department of Electrical Engineering, National Institute of Technology, Raipur, India

Published In:   Volume - 34,      Issue - 1,     Year - 2021

Cite this article:
Rathore et al. (2021). Various Techniques of MPPT Based Charge Controller & Comparison of A/C with D/C Home Appliances - A Review. Journal of Ravishankar University (Part-B: Science), 34(1), pp. 87-95.

Journal of Ravishankar University–B, 34 (1), 87-95 (2021)



Various Techniques of MPPT Based Charge Controller & Comparison of A/C with D/C Home Appliances - A Review

Gajendra Singh Rathorea*, B. Gopal Krishnaa, R.N. Patelb, Sanjay Tiwaria

aPhotonics Research Laboratory, School of Studies in Electronics & Photonics, Pt. Ravishankar Shukla University, Raipur, India

bDepartment of Electrical Engineering, National Institute of Technology, Raipur, India

*Corresponding author:

[Received: 27 May 2021; Revised: 25 June 2021; Accepted: 22 July 2021]


Abstract. Controlling the PV array to generate the maximum power at certain environment conditions, the efficiency of the PV generation system could be improved. Using control algorithms, the PV array can operate at the maximum power point. This self-optimization process is referred as Maximum power point tracking (MPPT). A maximum power point tracker (MPPT) is a power electronic DC-DC converter inserted between the PV array and its load to achieve optimum matching. Researchers have studied & developed numerous methods and used many algorithms to track the Maximum power point of PV Module and extract maximum power using MPPT technique. This review article accumulates various algorithms through which MPPT could be attained and assists the researchers to understand the principle of their working. The paper also gives an idea to about less explored DC appliances & their viabilities in existing & proposed DC system.

Keywords: PV system, Modeling & Simulation, MPPT Charge Controllers, INC algorithm, P&O algorithm, DC home


In last few years, it has become noticeable that fossil fuel resources are fast depleting and that the fossil fuel era is gradually coming to an end. This is particularly true for oil and natural gas. It will be useful therefore to examine the rates of consumption of the different sources of energy and to give some indications of the reserves available. As per International Energy Agency, the demand of energy grew by 2.3% worldwide last year, which claimed to be quickest of any decade. Natural gas as the fuel is emerged as one of the preferred, resulting in record growth and accounting for 45% of the rise in energy consumption. Demand for all fuels increased, with fossil fuels meeting nearly 70% of the growth for the second year running. Solar and wind generation grew at double-digit pace, with solar alone increasing by 31%. Renewables were a major contributor to this power generation expansion, accounting for remarkable gain of nearly half of electricity demand growth.

Electrical energy is produced using different sources of energy mainly categorized as non-renewable and renewable energy. We are aware that the non-renewable sources are posing a serious threat to the earth’s environment so, to mitigate the threat posed by constant using of non-renewable sources, the electricity supply industry is gradually moving to the use of renewable energy sources, which represent a sustainable path. Out of explored renewable energy sources, the PV power generation has enormous potential to reduce CO2 emissions very effectively, Despite of the numerous merits, few lags we enlisted is that, the solar resource is quite unpredictable and power can only be produce during daytime. The irregular behavior of moving clouds can cause fluctuations in the output power of PV generators. If a large amount of photovoltaic power is injected into the power grid then large power fluctuations will be expected, which have the potential to cause voltage imbalances, frequency instabilities and power imbalances in the power grid (Tiwari Sanjay et al., 2014; Tiwari Sanjay et al., 2009; Tiwari Sanjay et al., 2006; Appen J. V. et al., 2013).

Such intermittence of the solar energy resource is the reason why solar PV power is considered to be an intermittent source of power and to be classified as non-firm generation. Energy storage turns this on its head, as it compensates very effectively for the fluctuating power outputs of the PV generators, provided the Battery Energy Storage System (BESS) has been properly rated at the design stage. To supplement the output power of PV generators, in-situ energy storage devices are often used. This allows excess power to be stored and used at times when there is insufficient PV power generation due to cloudy weather or no PV power generation at all, such as at night. The BESS technology has the potential to improve the reliability and power quality of the electrical energy fed into the utility grid (Spiers D., 2012).


Maximum Power Point Tracking

The efficiency of the PV system can be increased by using power electronic devices along with maximum power point controller. The extraction of maximum available power from a photovoltaic module is done by Maximum Power Point Tracking Controller. The efficiency of the photovoltaic system may be substantially increased by using maximum power point tracker (MPPT). Several algorithms are developed to track the maximum power point efficiently. Most of the existing MPPT algorithms suffer from the drawback of being slow tracking. Due to this, the utilization efficiency is reduced. The various methods of maximum power point technique algorithms such as Incremental Conductance (INC) and Perturbation and Observation (P&O) have been discussed.

The output obtained from the MPPT controller contains harmonics due to the closed loop tracking of sun light. This can be eliminated by using the filter circuits. From this, the obtained output is given to power electronic devices DC-DC converter and inverter. The various power electronic converters circuits and the control techniques are discussed. In the article, a survey has been done on the performances of different algorithms used to implement Maximum Power Point Tracking, Power electronic circuits and their controlling using various controlling techniques are reviewed.

Antoneta Iluliana Bratcu et al. (Antoneta Iluliana Bratcu et al., 2008) studied maximum power point tracking of grid-connected PV arrays by using extremum seeking control. Using a two-stage conversion system that comprised of a DC-DC boost converter and a DC-AC inverter, the energy generated by PV array is transferred to single-phased utility grid. The performance of a control method based upon extremum seeking control (ESC) is then evaluated and demonstrated. ESC basically belongs to P&O based Maximum power point tracking technique. The simulation results proved ESC as effective technique for tracking at variable environmental conditions.

Incremental conductance method based maximum power point tracking technique to achieve the maximum power point is demonstrated by Esram et al. (Esram T. et al., 2008) to locate the current operating point in PV characteristic. To attain the maximum power point of the PV module, Bhasme et al. (Bhasme Swati et al., 2012) used current feedback loop with PI controller. Researcher made a comparison of measured value of PV Current with reference values and found the curves closer. The measurements were done under standard climatic condition.

Makhlouf et al. (Makhlouf M. et al., 2012) presented mathematical modeling of MPPT to achieve the voltage and current at the maximum power point and hence the maximum power. K. Manohar et al. (Manohar K. et al., 2012) used Perturb-and-observe method to attain maximum power point tracking and analyze fault. Boost circuit is used by Wenhao et al. (CAI Wenhao et al., 2012) to achieve the MPPT. It uplifts the low voltage of PV array to permissible line voltage.

Maximum power point tracking control technique is used primarily to extract maximum capable power of the PV modules at particular solar irradiance and temperature at any time frame. Numerous algorithms were developed to track the maximum power point effectively. It is observed that slow tracking is one of the prominent issues with most of the MPPT algorithms as a result of which the utilization efficiency is reduced. To improve the solar energy efficiency various MPPT control techniques are developed; such as Incremental Conductance (INC), Hill Climbing or Perturbation and Observation (P&O), Artificial Neural Network (ANN) with back propagation technique, Fuzzy Logic Controller Intelligent Control (FLCIC) with DC-DC converter, Particle Swarm Optimization, Open Circuit Voltage Control (OCVC), Short-Circuit Current Control (SCCC), feedback of power variation with voltage technique, feedback of power variation with current technique, single input fuzzy controller for tracking MPP, Ant Colony Optimization (ACO), and Genetic Algorithm (GA) methods.

Wu et al. (Wu L. et al., 2007) illustrates that the output obtained from the PV system is regulated by MPPT and it provides that output to the DC converter and inverter. The power transferred to the load or network is increased, if the PV output voltage is higher than MPP. The variation on MPPT efficiency depends on cell temperature and fill factor as observed by Piegari and Rizzo (Piegari L. et al., 2010). The paper presents the observation of MPPT techniques for different applications and systems.

Azli et al. (Azli N.A. et al., 2008) identifies the efficiency variation of 4-5% by considering the modification in fill factor with geographical & climate condition. Paper also proposes that with variation in temperature of the PV system the MPPT performance also improves. Modeling of MPPT with buck converter having less than 0.5% oscillations in the output power is discussed by Tauseef and Nowicki (Tauseef M. et al., 2012). The paper also suggests that the ratio of  does not relies completely on the climatic conditions as far as MPPT controller for PV cell with two-diode model is concerned.

To connect the PV panel with batteries and inverters to utility grid, a single chip IC circuit for MPPT is designed by Mattavelli et al. (Mattavelli P. et al., 2010). The system facilitates to test the MPPT response for PV short-circuit current variations and by implementing step DC voltage, the transient response of the system has been verified.

Al-Bahadili et al. (Al-Bahadili H. et al., 2013) simulated a system to evaluate the MPPT algorithm performance for PV system and the design provides flexibility to study different PV solar cells operating at varying irradiance level and temperature. Wu et al. (Wu X. et al., 2009) anticipated the MPPT method performances to attain the efficiency of 98% of the real output power in the common insolation condition.

It is observed that under rapid weather changing conditions, power losses are significant, and this could be reduced by implementing voltage control MPPT as proposed by Kadri et al. (Kadri R. et al., 2011). The above system is also effective for reflecting the power grid side using grid current components. The change in power by the different level of irradiation and the correct direction of MPP could be reflected by error signal of a PI outer voltage regulator. With the proposed method of Thao and Uchida (Thao N.G.M. et al., 2013) for single phase grid connected system the MPP will assist to reach unity power factor even if the solar irradiance and temperature vary abruptly.

Incremental Conductance (INC) based MPPT Techniques

Incremental Conductance Technique, an algorithm used to attain MPP operating point, works on the principle of adaptive step variation in voltage as a function of slope of PV curve. The curve pattern is used for iteration steps to get changes in voltage step value. This adaptive variation makes PV system sensitive towards the varying atmospheric condition and quickly attains the MPP operating point so that more and more energy could be extracted from PV generation system. The MPP is tracked by identifying the peak of the P-V curve. INC uses instantaneous conductance I/V and dI/dV for tracking MPPT. Based on the values of dI/dV, the algorithm varies the duty cycle and determines the location of the operating point of the PV module in the P-V curve showing that the PV module operates at the MPP along with both sides of the MPP in the P-V curve. Flow chart of the algorithm is as shown in Figure 2.

INC algorithm in MPP tracking technique determines the direction of radiation to change the voltage even when rapid change in climate condition observed and quickly tracks and calculate the MPP. This speed is further improved by implementing variable step size INC algorithm, which is being presented by Liu et al. (Liu F. et al., 2008). This technique eliminates the oscillation issue of P&O algorithm, although the efficiency variation is not that significant in any of the algorithm, under uniform climate condition (Hohm D. P. et al., 2003; Esram T. et al., 2007). The inclusion of high sampling compliance and speed control results in relatively high cost. Hill climbing algorithm was the widely accepted in MPP tracking during earlier days but later it gets obsolete as it persist the drawback of larger step size error with increase in speed and higher error step size reduces the efficiency of MPPT under rapid atmospheric fluctuations (Kazmi S. M. R. et al., 2009). The biggest complication for implementing INC algorithm was the selection of fixed voltage change step size which can fulfill the demand of tracking speed along with retaining MPP, large step size makes the system easier to reach MPP but at the same time this creates the condition of oscillation around MPP while smaller step size reduces the problem of oscillation but the tracking speed slowdowns.

Liu et al. (Liu B. et al., 2007) acknowledged the condition and designed an enhanced Incremental Conductance algorithm to negotiate between the dynamic response and steady state oscillation by implementing variable voltage step size. This algorithm contracted the oscillations and improved the efficiency of system.

Yusof et al. (Yusof Y. et al., 2004) designed an algorithm using C-programming which can sustain the variation occurred by temperature and also reduce the effects produced by variable voltage of battery. Comparison amongst four different MPPT techniques were carried out by Murtaza et al. (Murtaza A.F. et al., 2013) using MATLAB model and found INC based technique to be far better amongst them, when weather condition are varying quickly. This method showed good dynamic performance. Keyrouz and Georges (Keyrouz F. et al., 2011) merged two algorithms to track the rapidly varying environmental condition.

Wolfs and Li (Wolfs P. et al., 2006) calculated the cell output power and perturbed the cell voltage for every MPPT cycle for comparing Hill Climbing or Perturbation and Observation and Incremental Conductance methods. They used P&O algorithm to overcome the oscillation problem in INC technique. To validate a tracking theoretical performance analysis, a triple junction solar cell model was simulated. Using DC-DC converter as isolation stage for load connected PV system, Adly et al. (Adly M. et al., 2012) tested the Incremental Conductance under fast changing environmental conditions & analyzed that 15% energy extraction losses could be saved using INC algorithm.

To harvest maximum output power from a PV module Nabulsi et al. (Nabulsi A. Al et al., 2011) suggested Hill Climbing using Incremental Conductance based MPPT technique. The authors optimized the duty cycle, which resulted in maximum power delivery from the PV system through DC/DC converter to the load, but the oscillation of operating point around MPP introduced power losses in the system.

Perturbation and Observation based MPPT algorithm

The P&O algorithm is also called “hill-climbing”, while both names refer to the same algorithm depending on how it is implemented. Hill-climbing consist of a perturbation on the duty cycle of the power converter and P&O algorithm refers to perturbation in the operating voltage of the DC link between the PV array and the power converter. The basic principle on which P&O algorithm works is, if there is a positive change in the power, the perturbation should be kept in the same direction and if the power decreases, then the next perturbation should be in the opposite direction. The process is kept on repetition until the Maximum Power Point is reached which causes oscillation around the peak. This oscillation could be reduced by reducing the perturbation size. Generally, the perturbation size is kept very small in order to keep the power variation as small as possible but this trade-off makes the algorithm slower to track the environmental variations & hence this cannot be implemented where fast varying atmospheric conditions is observed.

The PV power fluctuations caused by variation observed in irradiance level in the Hill Climbing P&O method is elucidated by Liu et al. (Liu C. et al., 2004), according to the paper, the incremental change in power is measured & if value is positive, the operating voltage is increased to get Maximum power point while the direction of voltage modification is reversed when found negative and bring the operating point as closest to MPPT as possible (Yafaoui A. et al., 2007). The process can be understood by following flowchart figure 3.

AC and DC Technology

In context of electrical power distribution, earlier, Direct current (DC) was the standard current but due to flaws in DC system, AC turned in as the current standard due to its ability to step up low voltage into high voltage, and to transmit it over long with the help of the transformer. The revolution in the power electronics sector, bought back the development & transmission of DC power (Rashid M., 2011). DC transformers that can step- up and step-down a DC voltage is already developed in the form of Power electronic converters. DC transmission has already been a widely accepted technology in the world (Rudervall R., 2000). A number of high voltage DC transmission systems over long distance have been widely installed, which performs more excellent than AC regarding the economy and environment. In the field of the distribution system, data center became a promising market for DC system due to its high requirement of DC (Al Lee G. et al., 2012). Some of the pilot projects reported that distribution systems in the DC version are able to avoid conversion stage losses and result in more than 10% energy saving, even 20% reduction of the overall operating cost of data center can be achieved (Becker D. J. et al., 2011; Anand S. et al., 2010). Therefore, DC distribution presents a more efficient way for data center. In addition, telecommunication systems are used to transfer large amount of data, where the 48V DC distribution system is used to provide high reliability (Anand S. et al., 2010).

The advantages of DC multi terminal networks with large number of decentralized power generators are well mentioned by Doncker (Doncker R.W.D., 2014). Advantages like higher efficiency in energy conversion systems, higher power capacity in DC cables, Lower cost in structure used for energy conversion systems, less maintenance cost and higher reliability of the decentralized power generators are among the few of them. The concept of DC micro-grid and its ability to be controlled at constant value is conceptualized by Hiroaki Kakigano (Kakigano Hiroaki, 2006). Paper acknowledges the positive effect of DC micro-grid to the utility grid & to the customers.

Hammerstrom (Hammerstrom D.J., 2007) compiled the advantages of DC grid distribution system over AC grid distribution system. These advantages incorporate uninterruptible supplies, voltage stability, reliability, renewable energy resources, variable-speed drives, power quality concerns, fluorescent lighting and electronics.

The publication (Ferreira J.A., 2016; Hailu Tsegay, 2016) shows the protection strategies of voltage weak DC distribution system. The analysis of different DC grid architectures was carried out by comparing voltage stiff and voltage weak DC distribution grids. The natural behaviors of such systems from a control and a protection perspective are also addressed.

DC Appliances

There are numerous energy efficient products that are internally compatible with DC. These DC appliances utilize DC power internally. Among these products are the LED lights, mobile phones, laptops, PC’s and many electronic loads such as DC refrigerators, DC blenders, heaters, DC fans, hair dryers etc. LVDC distribution system is suggested by Salomonsson (Salomonsson A.S. et al., 2007) for sensitive electronic loads in office buildings & house hold, using different loads, which includes a lamp, a compact fluorescent lamp, a computer and a coffee maker, using AC and DC system for evaluation and comparison purposes and less losses were observed when the load was supplied with the DC system compared to the conventional AC system as per experimental results.

The energy efficiency analysis of DC products was carried out by Garbesi (Garbesi Karina, 2011). The studies shows the comparison for DC and AC products using DC lamps, air conditioners, refrigerator/freezers and it was observed that the DC products were found more energy efficient than the AC products based on available data. However, in this study, it was also concluded that the DC products were costlier than the AC products of same specification but efficiency is found much higher which can come out as a parameter to trade-off and definitely the technological advances will reduce their pricing later on. In another perspective, direct current is currently involved in another project in which the AC grid instead of updating to DC, is totally converted to DC grid which will be economically viable in terms of equipment installation costs.

Koh et al. (Koh L.H. et al., 2011) developed a LVDC grid lighting system using LED lamps and demonstrated that the energy savings in the LVDC LED system was more in comparison to the conventional AC lighting system.


The review has presented a comprehensive study and provides a brief comparison amongst various types of algorithm primarily Incremental Conductance (INC) and Perturbation & Observation (P&O) techniques for implementation of MPPT based power extraction from photovoltaic system. Numerous modifications such as number of control variables, control strategies, circuitry etc. done by researchers is being analysed and compared; which offers an idea to implement the most suitable technique as per available parameters for specific application. With the above study, we observed that upto 4% of the efficiency is affected by the variations of the fill factor which can be saved using MPPT technique, this also helps to extract 98% of real maximum output power and it is also observed that 15% energy extraction losses could be saved using INC algorithm.

Despite having limitation of slow tracking and low utilization efficiency INC and P&O based MPPT algorithm still remains the favorite and few further modifications can improvise the extraction efficiency. Improved filter circuits could be used to reduce the harmonic content at the output of DC-DC converter while high frequency current ripples could be minimized using filter capacitors. The contributions in the potential area of charge controllers and power conditioners encouraged the power generation using Solar Modules although it is expected that better methods of modeling and control design will make the photovoltaic system more efficient for grid integration.

In this article AC and DC are also compared based on current technology and it was also found out that there was a 14% energy savings if AC/DC conversions are avoided and 33% gain shifting to DC. The analysis and evaluation of technical and economic aspects could be carried out on common electric devices and household appliances to determine the possibility and feasibility of transition to DC. However, the evaluation of DC distribution grid transition for common electric devices and household appliances will be limited to low DC distribution grids for residential sector. We anticipate that DC system will draw less energy from grid due to less conversion stages in grid feed-out process than AC system. In low PV generation with small battery, power from PV and grid will go through more conversion stages in AC system than that in DC system, thus, might results in more losses.


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Author(s): Gajendra Singh Rathore; B. Gopal Krishna; R.N. Patel; Sanjay Tiwari

DOI: 10.52228/JRUB.2021-34-1-13         Access: Open Access Read More