There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality.

Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

I and i

In recent years solar energy has received worldwide attention in the field of renewable energy systems Among the various research thrusts in solar PV, the most proverbial area is extracting maximum power from solar PV system Application dof Maximum Power Point Tracking (MPPT) for extracting maximum power is very much appreciated and holds the key in developing efficient solar PV system In this paper, a state of the art review on various maximum power point techniques for solar PV systems covering timeworn conventional methods and latest soft computing algorithms is presented To date critical analysis on each of the method in terms of (1) tracking speed, (2) algorithm complexity, (3) Dynamic tracking under partial shading and (4) hardware implementation is not been carried out In this regard the authors have attempted to compile a comprehensive review on various solar PV MPPT techniques based on the above criteria Further, it is envisaged that the information presented in this review paper will be a valuable gathering of information for practicing engineers as well as for new researchers

A comprehensive review on solar PV maximum power point tracking techniques

Solar photovoltaic (PV) systems under partial shading conditions (PSCs) have a nonmonotonic P – V characteristic with multiple local maximum power points, which makes the existing maximum power point tracking (MPPT) algorithms unsatisfactory performance for global MPPT, if not invalid. This paper proposes a novel overall distribution (OD) MPPT algorithm to rapidly search the area near the global maximum power points, which is further integrated with the particle swarm optimization (PSO) MPPT algorithm to improve the accuracy of MPPT. Through simulations and experimentations, the higher effectiveness and accuracy of the proposed OD-PSO MPPT algorithm in solar PV systems is demonstrated in comparison to two existing artificial intelligence MPPT algorithms.

An Overall Distribution Particle Swarm Optimization MPPT Algorithm for Photovoltaic System Under Partial Shading

Energy storages introduce many advantages such as balancing generation and demand, power quality improvement, smoothing the renewable resource’s intermittency, and enabling ancillary services like frequency and voltage regulation in microgrid (MG) operation. Hybrid energy storage systems (HESSs) characterized by coupling of two or more energy storage technologies are emerged as a solution to achieve the desired performance by combining the appropriate features of different technologies. A single ESS technology cannot fulfill the desired operation due to its limited capability and potency in terms of lifespan, cost, energy and power density, and dynamic response. Hence, different configurations of HESSs considering storage type, interface, control method, and the provided service have been proposed in the literature. This paper comprehensively reviews the state of the art of HESSs system for MG applications and presents a general outlook of developing HESS industry. Important aspects of HESS utilization in MGs including capacity sizing methods, power converter topologies for HESS interface, architecture, controlling, and energy management of HESS in MGs are reviewed and classified. An economic analysis along with design methodology is also included to point out the HESS from investor and distribution systems engineers view. Regarding literature review and available shortcomings, future trends of HESS in MGs are proposed.

Hybrid energy storage system for microgrids applications: A review

This paper proposes a method to reduce the steady-state oscillation and to mitigate the probability of losing the tracking direction of the perturb and observed (P&O)-based maximum power point tracking (MPPT) for PV system. The modified scheme retains the conventional P&O structure, but with a unique technique to dynamically alter the perturbation size. At the same time, a dynamic boundary condition is introduced to ensure that the algorithm will not diverge from its tracking locus. The modified P&O is simulated in MATLAB Simulink and its performance is benchmarked using the standard MPPT efficiency ${{\boldsymbol{\eta }}_{MPPT}}$ calculation. Furthermore, the proposed concept is validated experimentally using a buck-boost converter, fed by a solar PV array simulator (PVAS). Based on the EN 50530 dynamic irradiance tests, the proposed method achieved an average ${{\boldsymbol{\eta }}_{MPPT}}$ almost 1.1% higher than the conventional P&O when irradiance changes slowly and about 12% higher under fast change of irradiance.

A Modified P&O Maximum Power Point Tracking Method With Reduced Steady-State Oscillation and Improved Tracking Efficiency

In this paper, a simple novel control strategy is designed and analyzed for a hybrid energy storage system (HESS). In the proposed method, batteries are used to balance the slow changing power surges, whereas supercapacitors (SC) are used to balance the fast changing power surges. The main advantage of the proposed control strategy is that, the slow response of battery system including dynamics of battery, controller, and converter operation, is overcome by diverting the power surges to the SC system. The proposed method inherits charge/discharge rate control to improve the life span and reduce the current stresses on battery. The proposed method features less computational burden as it uses simple control strategy. The detailed experimental results presented validate the proposed control strategy for sudden changes in photovoltaic (PV) generation and load demand.

Design and Analysis of Novel Control Strategy for Battery and Supercapacitor Storage System

In this paper, a variable perturbation size adaptive perturb and observe (P&O) maximum power point tracking (MPPT) algorithm is proposed to track the maximum power under sudden changes in irradiance. The proposed method consists of three algorithms, namely current perturbation algorithm (CPA), adaptive control algorithm (ACA), and variable perturbation algorithm (VPA). CPA always tries to operate the photovoltaic (PV) panel at maximum power point (MPP). ACA sets the operating point closer to MPP, only if the operating limits are violated. These operating limits are expressed in terms of the operating current range of the PV panel and the sudden changes in irradiance. VPA dynamically reduces the perturbation size based on polarity of change in power. Two-stage variable size perturbation is proposed in this paper. The proposed algorithm is realized using a boost converter. The effectiveness of proposed algorithm in terms of dynamic performance and improved stability is validated by detailed simulation and experimental studies.

Variable Perturbation Size Adaptive P&O MPPT Algorithm for Sudden Changes in Irradiance

Electric vehicle (EV) charging stations will play an important role in the smart city. Uncoordinated and statistical EV charging loads would further stress the distribution system. Photovoltaic (PV) systems, which can reduce this stress, also show variation due to weather conditions. In this paper, a hybrid optimization algorithm for energy storage management is proposed, which shifts its mode of operation between the deterministic and rule-based approaches depending on the electricity price band allocation. The cost degradation model of the energy storage system (ESS) along with the levelized cost of PV power is used in the case of EV charging stations. The algorithm comprises of three parts: categorization of real-time electricity price in different price bands, real-time calculation of PV power from solar irradiation data, and optimization for minimizing the operating cost of EV charging station integrated with PV and ESS. An extensive simulation study is carried out with an uncoordinated and statistical EV charging model in the context of Singapore to check effectiveness of this algorithm. Furthermore, detailed analysis of subsidy and incentive to be given by the government agencies for higher penetration of renewable energy is also presented. This work would aid in planning of adoption of PV-integrated EV charging stations, which would expectedly replace traditional gas stations in future.

Hybrid Optimization for Economic Deployment of ESS in PV-Integrated EV Charging Stations

In this paper, a short-circuit current-based adaptive perturb and observe maximum power point tracking algorithm is proposed to extract the maximum power from photovoltaic (PV) panel under sudden changes in the irradiance. This scheme is divided into two algorithms: 1) current perturbation algorithm; and 2) adaptive control algorithm. The current perturbation algorithm makes the PV panel operate at maximum power point. The adaptive control algorithm identifies the operating limit violation and sets a new operating point nearer to maximum power point. These limits are derived in terms of changes in the irradiance and current. The new operating point is set by estimating the short-circuit current. This algorithm proposes variable current perturbation, which varies continuously with the irradiance. A boost converter is used to realize the proposed algorithm. The proposed algorithm is compared with a conventional algorithm and validated for sudden changes in the irradiance through the experimental results.

A Novel Adaptive P&O MPPT Algorithm Considering Sudden Changes in the Irradiance

The power generation from renewable power sources is variable in nature, and may contain unacceptable fluctuations in case of the wind power generation. High fluctuations in power generation may negatively impact the voltage stability of the microgrid. This problem can be alleviated by using hybrid energy storage system consisting of batteries and supercapacitors (SCs) at dc grid. A new control scheme is proposed to control the power sharing between batteries and SCs to match the generation-demand mismatch and hence to regulate the grid voltage. In the proposed control strategy, the SC supplies error component of the battery current in addition to the fast transient power demand. This added feature not only improves the dc grid voltage regulation capability but also reduces the stress levels on the battery and hence increases the life span of the battery. The main advantage of the scheme is that, the uncompensated power due to slow dynamics of the battery is diverted to the SC and keeps the state of charge within the limits for longer duration, as compared to the conventional strategy. The proposed scheme is validated through detailed experimental studies.

Sathish Kumar Kollimalla

Papers

Design and Analysis of Novel Control Strategy for Battery and Supercapacitor Storage System

Variable Perturbation Size Adaptive P&O MPPT Algorithm for Sudden Changes in Irradiance

Hybrid Optimization for Economic Deployment of ESS in PV-Integrated EV Charging Stations

A Novel Adaptive P&O MPPT Algorithm Considering Sudden Changes in the Irradiance

DC Grid Voltage Regulation Using New HESS Control Strategy