Photovoltaic Radiation Research Articles

A Robust Power Management Strategy With Multi-Mode Control Features for an Integrated PV and Energy Storage System to Take the Advantage of ToU Electricity Pricing

In this paper, a power management strategy (PMS) for an integrated residential solar photovoltaic (PV) and energy storage unit (ESU) is proposed for both grid-connected and islanded operations to take the advantage of time-of-use pricing. This is an effective solution to integrate storage and renewable energy sources, such as solar PV, with the conventional grid to improve the reliability and efficiency of the power system and to reduce the total electricity cost for the consumer. An automatic switching control strategy is proposed to realize a smooth switching among the various operation modes of the proposed energy management strategy. The integrated PV-storage system is composed of a 5-kW PV array, a 3.5-kW·h ESU formed by 12-V single lead acid batteries, and three power converters. The PMS ensures seamless switching of the ESU converter between the charging and the discharging mode and seamless switching between the inverting and the rectifying mode of the grid converter. It also ensures that the local loads are supplied when the grid fails. An experimental setup has been implemented in the laboratory using the real-time field-programmable gate array general-purpose inverter control card from National Instrument to verify the practical feasibility of the proposed PMS under the various scenarios of the PV irradiation, load changings, and the state of charge of the ESU. The results show that the proposed PMS is effective and robust against various scenarios.

A standalone BLDC based solar air cooler with MPP tracking for improved efficiency

This article proposes the idea of using Solar Energy (SE) as a source of power for designing and developing a standalone air-cooling system. This type of application is particularly suited for rural areas that have a considerable amount of solar radiation and have no access to grid systems. The proposed system is comprised of a photovoltaic (PV) array, DC-DC boost converter and DC-DC buck converter. Two Permanent Magnet Brushless Direct Current (PMBLDC) motors are employed to drive a centrifugal water pump and an air blower coupled to their individual shafts. The air blower is connected with a DCDC boost converter that ensures a maximum power point (MPP) operation. A centrifugal water pump is connected with a DC-DC buck converter. The challenging task in an air cooling system is to maintain the constant speed of the blower under variable irradiance conditions. The power provided by the solar PV array can be shared between the two DC-DC converters in such a way that the BLDC motor connected with the blower will maintain a constant speed by maintaining the constant voltage of the DCDC boost converter. The rest of the available PV power will be handled by the pump. The suitability of the proposed system for various perturbations is evaluated by simulating the proposed system using a MATLAB/Simulink and is validated by conducting experiments. Case studies have been performed with a variable PV irradiance and the results are explored.

Adaptive backstepping approach for dc‐side controllers of Z ‐source inverters in grid‐tied PV system applications

Z -source inverters (ZSIs) are single-stage power converters with both voltage buck and boost capabilities provided by the unique impedance network and the ability to operate during shoot-through states. This study proposes a novel non-linear adaptive backstepping method for dc-side controllers in a multi-loop control scheme of the ZSI in grid-tied photovoltaic (PV) systems. Despite the variability of the capacitor and inductor values in the ZSI impedance network, the proposed controller guarantees robust and stable operation under varying levels of PV irradiance and temperature. The shoot-through duty ratio of the ZSI is obtained directly from the output of an MPPT algorithm and the measured PV and inductor currents. This strategy overcomes the disadvantages of the conventional approach such as the non-minimum phase at the dc side of the ZSI. It also eliminates the need to linearise the voltage/current characteristics of the PV arrays and ZSI model. The ac-side controllers consist of an outer proportional-integral voltage controller and an inner deadbeat current controller to achieve unity power factor and stable capacitor voltage in spite of grid voltage fluctuations. The efficacy of the proposed adaptive backstepping controller and the multi-loop control scheme is validated by offline and hardware-in-the-loop real-time simulations.

Real-time Photovoltaic Simulator Using Current Feedback Control

In this proposal article, mathematical model of Photovoltaic model is investigated the relationship of the Photo Voltaic's irradiance, temperature and parameters comparing to its output power. It leads in to an analyzing and developing of the Photovoltaic Simulator. By which, Photovoltaic simulator is utilized by the DC converter circuit with a current feedback control. This may be useful if is possible to implementing into a real world Photovoltaic simulator. In this paper, Photovoltaic simulator is modeled using MATLAB/Simulink program, which is composed of DC converter and a proper control scheme. It can be observed from the simulation results that I-V relationship of the Photovoltaic simulator is quite the same as of such Photovoltaic mathematical model. This means that, it is possible to build a real Photovoltaic simulator in commercial in a further work.

Hierarchical controls selection based on PV penetrations for voltage rise mitigation in a LV distribution network

In recent years, the penetration level of distributed energy resources (DER) in the low voltage (LV) networks are increasing rapidly which has resulted in causing the voltage rise problem, even at the far end customer point in distribution networks (DNs). This paper presents a coordinated hierarchical controls selection method for mitigating the overvoltage problem using available resources in DNs, for example, static synchronous compensators (STATCOM) and battery energy storage (BES) systems. The proposed method recommends the installation of new control devices, such as photovoltaic (PV) smart voltage source inverter (VSI) with reactive power compensation capability, residential BES installations, and power sharing among neighboring distributed generator (DG) units depending on PV penetration levels at the LV network. The requirements of the proposed installation of the compensation devices are based on three criteria: (i) higher PV penetration scenarios; (ii) satisfying relevant standards; and (iii) economic perspectives. The interactions among standard VSI (operated at unity power factor (pf)) and smart VSI (variable pf) are also considered in the proposed method to mitigate the voltage rise problems. The results show that only after exceeding certain PV penetrations, the LV network requires a coordinated operation from STATCOM/BES and advanced compensation devices to sustain terminal voltages within permissible (±6%) limits. The proposed method is verified with extensive case studies utilizing real PV irradiance and customer loads data with nonlinear dynamic DER models connected with an urban LV network in the PSCAD/EMTDC software environment.

Explicit degradation modelling in optimal lead–acid battery use for photovoltaic systems

Lead–acid battery is a storage technology that is widely used in photovoltaic (PV) systems. Battery charging and discharging profiles have a direct impact on the battery degradation and battery loss of life. This study presents a new 2-model iterative approach for explicit modelling of battery degradation in the optimal operation of PV systems. The proposed approach consists of two models: namely, economic model and degradation model which are solved iteratively to reach the optimal solution. The economic model is a linear programming optimisation problem that calculates the optimal hourly battery use profile based on an assumed value of the battery degradation cost. The degradation model, in turn, gives the battery degradation cost based on the battery use profile, temperature and battery characteristics. The models are solved iteratively to finally reach to the optimal battery use considering battery degradation. The proposed approach has been applied to a 4 kWp PV system and the performance of the proposed approach were evaluated. Applicability of the proposed approach in determining the optimal storage size and the economic battery life were also shown. Advantages and the capability of the proposed approach in considering PV generation and irradiation variations were also evaluated through seasonality analysis.

Graph-Based Semi-supervised Learning for Fault Detection and Classification in Solar Photovoltaic Arrays

Fault detection in solar photovoltaic (PV) arrays is an essential task for increasing reliability and safety in PV systems. Because of PV's nonlinear characteristics, a variety of faults may be difficult to detect by conventional protection devices, leading to safety issues and fire hazards in PV fields. To fill this protection gap, machine learning techniques have been proposed for fault detection based on measurements, such as PV array voltage, current, irradiance, and temperature. However, existing solutions usually use supervised learning models, which are trained by numerous labeled data (known as fault types) and therefore, have drawbacks: 1) the labeled PV data are difficult or expensive to obtain, 2) the trained model is not easy to update, and 3) the model is difficult to visualize. To solve these issues, this paper proposes a graph-based semi-supervised learning model only using a few labeled training data that are normalized for better visualization. The proposed model not only detects the fault, but also further identifies the possible fault type in order to expedite system recovery. Once the model is built, it can learn PV systems autonomously over time as weather changes. Both simulation and experimental results show the effective fault detection and classification of the proposed method.

Optimal Dispatch of Residential Photovoltaic Inverters Under Forecasting Uncertainties

Efforts to ensure reliable operation of existing low-voltage distribution systems with high photovoltaic (PV) generation have focused on the possibility of inverters providing ancillary services such as active power curtailment and reactive power compensation. Major benefits include the possibility of averting overvoltages, which may otherwise be experienced when PV generation exceeds the demand. This paper deals with ancillary service procurement in the face of solar irradiance forecasting errors. In particular, assuming that the forecasted PV irradiance can be described by a random variable with known (empirical) distribution, the proposed uncertainty-aware optimal inverter dispatch (OID) framework indicates which inverters should provide ancillary services with a guaranteed a-priori risk level of PV generation surplus. To capture forecasting errors, and strike a balance between risk of overvoltages and (re)active power reserves, the concept of conditional value-at-risk is advocated. Due to AC power balance equations and binary inverter selection variables, the formulated OID involves the solution of a nonconvex mixed-integer nonlinear program. However, a computationally-affordable convex relaxation is derived by leveraging sparsity-promoting regularization approaches and semidefinite relaxation techniques. The proposed scheme is tested using real-world PV-generation and load-profile data for an illustrative low-voltage residential distribution system.

Impact of Energy Storage and Variability of PV on Power System Reliability

The variability of renewable sources has high impact on power system reliability, e.g. photovoltaic (PV), and energy storage (ES) is one of several options for better grid reliability [1–3]. This paper serves to establish power system reliability of hierarchical level 1 (HL1) using analytical techniques. The IEEE Reliability Test System (IEEE-RTS) generation model and load model are applied to convolute a system risk model. Incorporating PV improves system reliability but the variability of PV power output compromises on PV capacity credit. ES is included into system risk model to enhance system reliability performance. System adequacy indices are investigated to show the system reliability performance. Impact on system generation cost, via variation of PV and ES capacities are presented. Actual Singapore PV irradiance data and Energy Market Company price information are incorporated in this study. This analytical technique can help Independent Service Operators (ISO) to evaluate the potential of PV to benefit system reliability and find ways to improve its potentials.