• Energy Research

Indoor photovoltaic (PV) application gains in attraction for low-power electronic systems, which requires accurate methods for performance predictions in indoor environments. Despite this, the knowledge on the performance of commonly used photovoltaic device models and their parameter estimation techniques in these scenarios is very limited. Accurate models are an essential tool for conducting feasibility analyses and component dimensioning for indoor photovoltaic systems. In this paper, we therefore conduct a comparison of the one- and two-diode models with parameters estimated based on two well-known methods. We evaluate the models' performance on datasets of photovoltaic panels intended for indoor use, and illumination conditions to be expected in indoor environments lit by artificial light sources. The results demonstrate that the one-diode model outperforms the two-diode model with respect to the estimation of the overall I-V characteristics. The two-diode model results instead in lower maximum power point errors. Both models show a sensitivity to initial conditions, such as the selection of the diode ideality factor, as well as the curve form of the photovoltaic panel to be modeled, which has not been acknowledged in previous research.

Abstract Models of photovoltaic devices are used to compare the properties of photovoltaic cells and panels, and to predict their I-V characteristics. To a large extent, modeling methods are based on the one-diode equivalent circuit. Although much research exists on the implementation and evaluation of these methods for typical outdoor conditions, their performance at indoor illumination levels is largely unknown. Consequently, this work performs a systematic study of methods for the parameter extraction of one-diode models under indoor conditions. We selected, reviewed and implemented commonly used methods, and compared their performance at different illumination levels. We have shown that most methods can achieve good accuracies with extracted parameters regardless of the illumination condition, but their accuracies vary significantly when the parameters are scaled to other conditions. We conclude that the physical interpretation of extracted parameters at low illumination is to a large extent questionable, which explains errors based on standard scaling approaches.

The introduction of nonlinearities into energy harvesting in order to improve the performance of linear harvesters has attracted a lot of research attention recently. The potential benefits of nonlinear harvesters have been evaluated under sinusoidal or random excitation. In this paper, the performances of electromagnetic energy harvesters with linear and nonlinear springs are investigated under real vibration data. Compared to previous studies, the parameters of linear and nonlinear harvesters used in this paper are more realistic and fair for comparison since they are extracted from existing devices and restricted to similar sizes and configurations. The simulation results showed that the nonlinear harvester did not generate higher power levels than its linear counterpart regardless of the excitation category. Additionally, the effects of nonlinearities were only available under a high level of acceleration. The paper also points out some design concerns when harvesters are subjected to real vibrations.

Models of photovoltaic devices are an important tool for the estimation of their I-V characteristics. These characteristics, in turn, can be used to optimize production, compare devices, or predict the output power under different illumination conditions. Equivalent circuit models are the most common model types utilized. Although these models and the estimation of their parameters are thoroughly investigated, little is known about their performance under indoor illumination conditions. This, however, is essential for applications where photovoltaic devices are used indoors, such as for PV-powered sensors, wearables or Internet of Things devices. In this paper, a comprehensive and quantitative study of parameter estimation methods for the two-diode model is conducted, focusing particularly on the performance at indoor illumination levels. We reviewed and implemented a set of six common parameter estimation methods, and evaluate the performance of the estimated parameters on a typical photovoltaic module utilized in indoor scenarios. The results of this investigation demonstrate that there is a large performance variation between different parameter estimation methods, and that many methods have difficulties to estimate accurate parameters at low illumination conditions. Moreover, the majority of methods result in physically infeasible parameters, at least under some of the evaluated conditions. When applying physically motivated parameter scaling methods to these parameters, large estimation errors are observed, which limits the model's applicability for power estimation purposes.

Condition monitoring devices in hydraulic systems that use batteries or require wired infrastructure have drawbacks that affect their installation, maintenance costs, and deployment flexibility. Energy harvesting technologies can serve as an alternative power supply for system loads, eliminating batteries and wiring requirements. Despite the interest in pressure fluctuation energy harvesters, few studies consider end-to-end implementations, especially for cases with low-amplitude pressure fluctuations. This generates a research gap regarding the practical amount of energy available to the load under these conditions, as well as interface circuit requirements and techniques for efficient energy conversion. In this paper, we present a self-powered sensor that integrates an energy harvester and a wireless sensing system. The energy harvester converts pressure fluctuations in hydraulic systems into electrical energy using an acoustic resonator, a piezoelectric stack, and an interface circuit. The prototype wireless sensor consists of an industrial pressure sensor and a low-power Bluetooth System-on-chip that samples and wirelessly transmits pressure data. We present a subsystem analysis and a full system implementation that considers hydraulic systems with pressure fluctuation amplitudes of less than 1 bar and frequencies of less than 300 Hz. The study examines the frequency response of the energy harvester, the performance of the interface circuit, and the advantages of using an active power improvement unit adapted for piezoelectric stacks. We show that the interface circuit used improves the performance of the energy harvester compared to previous similar studies, showing more power generation compared to the standard interface. Experimental measurements show that the self-powered sensor system can start up by harvesting energy from pressure fluctuations with amplitudes starting at 0.2 bar at 200 Hz. It can also sample and transmit sensor data at a rate of 100 Hz at 0.7 bar at 200 Hz. The system is implemented with off-the-shelf circuits.

Abstract The variable reluctance principle can be used to convert rotational kinetic energy into electrical energy, creating a Variable Reluctance Energy Harvester (VREH) based on electromagnetic induction. This can be used to implement self-sustaining wireless sensors in rotating applications. In this paper, we present and investigate a novel design of a VREH with high volumetric power density that targets low-speed rotating applications. The design uses an m-shaped pole-piece and two opposing magnets. We theoretically analyze key design parameters that influence the VREH’s output power, and relate these parameters to geometrical design factors of the proposed structure. Key design factors include the coil height, the permanent magnet height and the tooth height. A method based on numerical simulations is introduced, enabling to determine the optimal geometrical dimensions of the proposed structure under given size-constraints. The results demonstrate that the method leads to optimal structure configurations, which has been evaluated for different cases and is verified experimentally. Good agreement between numerical simulations and experiments are reported with deviations in output power estimation below 3%. The optimized m-shaped VREH, moreover, provides output power levels sufficient for wireless sensor operation, even in low-speed rotating applications.