Design and real-time implementation of a new auto-tuned adaptive MPPT control for a photovoltaic system Raseswari Pradhan, Bidyadhar Subudhi ⇑ Department of Electrical Engineering, Centre of Excellence on Renewable Energy System, National Institute of Technology Rourkela, Odisha 769008, India article info Article history: Received 1 July 2013 Received in revised form 10 July 2014 Accepted 26 July 2014 Keywords: Polynomial PV model RLS method MPPT Auto-tuned PID controller abstract This paper presents design of an auto-tuning based adaptive maximum power point tracker (ATAMPPT) for a photovoltaic (PV) system. The maximum power point (MPP) of a PV system varies continuously in accordance with changing weather conditions. To cope up with fast varying weather conditions, there is a necessity of an adaptive MPPT system in which MPP of the PV system needs to be quickly estimated and tracked. The proposed ATAMPPT comprises of a DC/DC boost converter equipped with an adaptive MPPT algorithm. This ATAMPPT is incorporated between the PV system and load. In this new MPPT system, a polynomial curve-fitting approach is employed to model the PV system whose parameters are identified on-line using a Recursive-Least-Square (RLS) algorithm. Further, the real-time performance of the pro- posed MPPT system is validated by using a prototype PV control system set-up developed in our labora- tory. The performances of the proposed ATAMPPT have been compared with that of three existing MPPTs namely Perturb and Observe (P&O) and an adaptive P&O MPPT. From the obtained results it is observed that the overall approach of the proposed ATAMPPT control is simple, user-friendly and it exhibits accu- rate MPP tracking. Ó 2014 Elsevier Ltd. All rights reserved. Introduction A PV system can harvest maximum possible power if it is oper- ated at its MPP. In view of achieving this maximum PV power, a MPPT is employed between the PV panel and load. MPPT is a very important component of a PV system which consists of a MPPT algorithm, a controller, PWM generator, comparator and a DC/DC boost converter. The MPPT algorithm calculates the reference oper- ating point of the PV system that aligns with the MPP. A DC/DC boost converter forces the PV system to operate at MPP as calculated by the MPPT algorithm. A PWM generator generates gate-pulses according to the signal received from the controller. Designing a suitable MPPT algorithm and a controller are very important tasks in achieving maximum power harvest in a PV system [1]. A good number of MPPT algorithms and their implementations are reported in [2] for constant and fast changing weather condi- tions and also for partial shedding mismatched conditions. Incre- mental Conductance (INC) and Perturb and Observe (P&O) methods are more popular MPPTs because of their simplicity and ease in implementations [3]. Also, INC and P&O MPPTs have been modified to improve the PV power harvesting efficiency and MPP tracking accuracy [4–8]. An adaptive P&O (APO) proposed in [5] is a low cost MPPT that involves a simple adaptive MPP tracking algorithm, a PI-controller and a sensor. But, the main concern in all these MPPTs is the dependency of MPP tracking response on the perturbation size. Also, the tracking signal oscillates around its reference point even at the steady-state [9–10]. On the other hand, Newton–Raphson method (NRM) is found to be an appropri- ate technique for determination of MPP because it does not depend on empirical formula and trial and error [11]. Although NRM algo- rithm deals with double integral term of the tracking signal, but the estimated MPPs using NRM are not oscillatory like P&O and INC MPPTs. Also, the NRM technique is a very convenient tech- nique to calculate MPPs on-line by considering linearized mathe- matical model of the PV panel and DC/DC boost converter [12]. The main concern in maximum PV power harvesting is to design and implement a controller in the situation of fast changing weather conditions because the MPP of a PV panel is dependent on the weather conditions [13]. PI and PID-controllers are commer- cially accepted controllers owing to ease in their implementation. But opportunities exist in modifying these controllers to achieve adaptive control actions [14–17]. A fixed gain PID-controller can- not handle fast variations in weather conditions for a wide operat- ing range [15,16]. Although adaptive controllers such as the model reference adaptive controller (MRAC) and self-tuning regulator (STR) have been successfully applied to PID-controlled DC/DC http://dx.doi.org/10.1016/j.ijepes.2014.07.080 0142-0615/Ó 2014 Elsevier Ltd. All rights reserved. ⇑ Corresponding author. Electrical Power and Energy Systems 64 (2015) 792–803 Contents lists available at ScienceDirect Electrical Power and Energy Systems journal homepage: www.elsevier.com/locate/ijepes