Dynamic Boost Based DMPPT Emulator

The Distributed Maximum Power Point Tracking (DMPPT) approach is a promising solution to improve the energetic performance of mismatched PhotoVoltaic (PV) systems. However, there are still several factors that can reduce DMPPT energy efficiency, including atmospheric conditions, the efficiency of the power stage, constraints imposed by the topology, the finite rating of silicon devices, and the nonoptimal value of string voltage. In order to fully explore the advantages offered by the above solution, the implementation of a Boost based DMPPT emulator is of primary concern, especially if it behaves as a controlled voltage or current source. The repeatability of experimental tests, the tighter control of climatic conditions, the closing of the gap between the physical dimensions of a PV array and the space available in a university lab, the simplicity with which new algorithms can be tested, and the low maintenance costs are just some of the benefits offered by an emulator. This paper describes the realization and use of a Boost based Distributed Maximum Power Point Tracking (DMPPT) emulator and shows its high flexibility and potential. The device is able to emulate the output current vs. voltage (I-V) characteristics of many commercial PhotoVoltaic (PV) modules with a dedicated Boost DC/DC converter. The flexibility is guaranteed by the ability to reproduce both I = f (V) and V = g(I) characteristics at different values of not only the irradiance levels but also the maximum allowed voltage across the switching devices. The system design is based on a commercial power supply controlled by a low-cost Arduino board by Arduino (Strambino, Torino, Italy). Data acquisition is performed through a lowcost current and voltage sensor by using a multichannel board by National Instruments. Experimental results confirm the capability of the proposed device to accurately emulate the output I-V characteristic of Boost based DMPPT systems obtained by varying the atmospheric conditions, the rating of silicon devices, and the electrical topology

Integrated energy management converter based on maximum power point tracking for photovoltaic solar system

This paper presents an integrated power control system for photovoltaic systems based on maximum power point tracking (MPPT). The architecture presented in this paper is designed to extract more power from photovoltaic panels under different partial obscuring conditions. To control the MPPT block, the integrated system used the ripple correlation control algorithm (RCC), as well as a high-efficiency synchronous direct current (DC-DC) boost power converter. Using 180 nm complementary metal-oxide-semiconductor (CMOS) technology, the proposed MPPT was designed, simulated, and layout in virtuoso cadence. The system is attached to a two-cell in series that generates a 5.2 V average output voltage, 656.6 mA average output current, and power efficiency of 95%. The final design occupies only 1.68 mm2

Improving the Efficiency of Energy Harvesting Embedded System

In the past decade, mobile embedded systems, such as cell phones and tablets have infiltrated and dramatically transformed our life. The computation power, storage capacity and data communication speed of mobile devices have increases tremendously, and they have been used for more critical applications with intensive computation/communication. As a result, the battery lifetime becomes increasingly important and tends to be one of the key considerations for the consumers. Researches have been carried out to improve the efficiency of the lithium ion battery, which is a specific member in the more general Electrical Energy Storage (EES) family and is widely used in mobile systems, as well as the efficiency of other electrical energy storage systems such as supercapacitor, lead acid battery, and nickel–hydrogen battery etc. Previous studies show that hybrid electrical energy storage (HEES), which is a mixture of different EES technologies, gives the best performance. On the other hand, the Energy Harvesting (EH) technique has the potential to solve the problem once and for all by providing green and semi-permanent supply of energy to the embedded systems. However, the harvesting power must submit to the uncertainty of the environment and the variation of the weather. A stable and consistent power supply cannot always be guaranteed. The limited lifetime of the EES system and the unstableness of the EH system can be overcome by combining these two together to an energy harvesting embedded system and making them work cooperatively. In an energy harvesting embedded systems, if the harvested power is sufficient for the workload, extra power can be stored in the EES element; if the harvested power is short, the energy stored in the EES bank can be used to support the load demand. How much energy can be stored in the charging phase and how long the EES bank lifetime will be are affected by many factors including the efficiency of the energy harvesting module, the input/output voltage of the DC-DC converters, the status of the EES elements, and the characteristics of the workload. In this thesis, when the harvesting energy is abundant, our goal is to store as much surplus energy as possible in the EES bank under the variation of the harvesting power and the workload power. We investigate the impact of workload scheduling and Dynamic Voltage and Frequency Scaling (DVFS) of the embedded system on the energy efficiency of the EES bank in the charging phase. We propose a fast heuristic algorithm to minimize the energy overhead on the DC-DC converter while satisfying the timing constraints of the embedded workload and maximizing the energy stored in the HEES system. The proposed algorithm improves the efficiency of charging and discharging in an energy harvesting embedded system. On the other hand, when the harvesting rate is low, workload power consumption is supplied by the EES bank. In this case, we try to minimize the energy consumption on the embedded system to extend its EES bank life. In this thesis, we consider the scenario when workload has uncertainties and is running on a heterogeneous multi-core system. The workload variation is represented by the selection of conditional branches which activate or deactivate a set of instructions belonging to a task. We employ both task scheduling and DVFS techniques for energy optimization. Our scheduling algorithm considers the statistical information of the workload to minimize the mean power consumption of the application while satisfying a hard deadline constraint. The proposed DVFS algorithm has pseudo linear complexity and achieves comparable energy reduction as the solutions found by mathematical programming. Due to its capability of slack reclaiming, our DVFS technique is less sensitive to small change in hardware or workload and works more robustly than other techniques without slack reclaiming

Energy challenges for ICT

The energy consumption from the expanding use of information and communications technology (ICT) is unsustainable with present drivers, and it will impact heavily on the future climate change. However, ICT devices have the potential to contribute signi - cantly to the reduction of CO2 emission and enhance resource e ciency in other sectors, e.g., transportation (through intelligent transportation and advanced driver assistance systems and self-driving vehicles), heating (through smart building control), and manu- facturing (through digital automation based on smart autonomous sensors). To address the energy sustainability of ICT and capture the full potential of ICT in resource e - ciency, a multidisciplinary ICT-energy community needs to be brought together cover- ing devices, microarchitectures, ultra large-scale integration (ULSI), high-performance computing (HPC), energy harvesting, energy storage, system design, embedded sys- tems, e cient electronics, static analysis, and computation. In this chapter, we introduce challenges and opportunities in this emerging eld and a common framework to strive towards energy-sustainable ICT

A survey of emerging architectural techniques for improving cache energy consumption

The search goes on for another ground breaking phenomenon to reduce the ever-increasing disparity between the CPU performance and storage. There are encouraging breakthroughs in enhancing CPU performance through fabrication technologies and changes in chip designs but not as much luck has been struck with regards to the computer storage resulting in material negative system performance. A lot of research effort has been put on finding techniques that can improve the energy efficiency of cache architectures. This work is a survey of energy saving techniques which are grouped on whether they save the dynamic energy, leakage energy or both. Needless to mention, the aim of this work is to compile a quick reference guide of energy saving techniques from 2013 to 2016 for engineers, researchers and students

New Three Phase Photovoltaic Energy Harvesting System for Generation of Balanced Voltages in Presence of Partial Shading, Module Mismatch, and Unequal Maximum Power Points

The worldwide energy demand is growing quickly, with an anticipated growth rate of 48% from 2012 to 2040. Consequently, investments in all forms of renewable energy generation systems have been growing rapidly due to growth rate and climate concerns. Increased use of clean renewable energy resources such as hydropower, wind, solar, geothermal, and biomass is expected to noticeably alleviate many present environmental concerns associated with fossil fuel-based energy generation. In recent years, wind and solar energies have gained the most attention among all other renewable resources. As a result, both have become the target of extensive research and development for dynamic performance optimization, cost reduction, and power reliability assurance. The performance of Photovoltaic (PV) systems is highly affected by environmental and ambient conditions such as irradiance fluctuations and temperature swings. Furthermore, the initial capital cost for establishing the PV infrastructure is very high. Therefore, it is essential that the PV systems always harvest the maximum energy possible by operating at the most efficient operating point, i.e. Maximum Power Point (MPP), to increase conversion efficiency to reach 100% and thus result in lowest cost of captured energy. The dissertation is an effort to develop a new PV conversion system for large scale PV grid-connected systems which provides 99.8% efficacy enhancements compared to conventional systems by balancing voltage mismatches between the PV modules. Hence, it analyzes the theoretical models for three selected DC/DC converters. To accomplish this goal, this work first introduces a new adaptive maximum PV energy extraction technique for PV grid-tied systems. Then, it supplements the proposed technique with a global search approach to distinguish absolute maximum power peaks within multi-local peaks in case of partially shaded PV module conditions. Next, it proposes an adaptive MPP tracking (MPPT) strategy based on the concept of model predictive control (MPC) in conjunction with a new current sensor-less approach to reduce the number of required sensors in the system. Finally, this work proposes a power balancing technique for injection of balanced three-phase power into the grid using a Cascaded H-Bridge (CHB) converter topology which brings together the entire system and results in the final proposed PV power system. The developed grid connected PV solar system is evaluated using simulations under realistic dynamic ambient conditions, partial shading, and fully shading conditions and the obtained results confirm its effectiveness and merits comparted to conventional systems. The resulting PV system offers enhanced reliability by guaranteeing effective system operation under unbalanced phase voltages caused by severe partial shading

Solar energy radiation measurement with a low–power solar energy harvester

Solar energy radiation measurements are essential in precision agriculture and forest monitoring and can be readily performed by attaching commercial pyranometers to autonomous sensor nodes. However this solution significantly increases power consumption up to tens of milliwatts and can cost hundreds of euros. Since many autonomous sensor nodes are supplied from photovoltaic (PV) panels which currents depend on solar irradiance, we propose to double PV panels as solar energy sensors. In this paper, the inherent operation of the low-power solar energy harvester of a sensor node is also used to measure the open circuit voltage and the current at the maximum power point (IMPP), which allows us to determine solar irradiance and compensate for its temperature drift. The power consumption and cost added to the original solar energy harvester are minimal. Experimental results show that the relation between the measured IMPP and solar irradiance is linear for radiation above 50¿W/m2, and the relative uncertainty limit achieved for the slope is ±2.4% due the light spectra variation. The relative uncertainty limit of daily solar insolation is below ±3.6% and is hardly affected by the so called cosine error, i.e. the error caused by reflection and absorption of light in PV panel surface.Peer ReviewedPostprint (author's final draft

High Granularity approaches for effective energy delivery from Photovoltaic Sources

Silicon solar cell technology is a fully mature technology but the need to compete with traditional and other renewable energy sources urges to improve the overall efficiency of a photovoltaic (PV) system by a significant amount. Regardless of the solar panel efficiency, the difference between the nominal performance of a PV system and the energy actually produced is quite high, and it can be quantified in the order of 20%. A loss term, often underestimated, depends on possible failure of the Maximum Power Point Tracking (MPPT) algorithms in the presence of multiple maximum power points in power-voltage characteristic, arising in mismatch conditions. This work proposes High Granularity (HG) approaches in order to improve the PV energy yield: a monitoring strategy, a modeling and a power flux control of the whole PV system, all performed at level of single elementary source (i.e., PV cell or PV panel). An innovative HG sensor infrastructure was developed, and the measurements were exploited to perform an automatic PV system reconfiguration, and to design an information based MPPT. Moreover, the data validated a circuit HG model describing the PV system at single cell level, which also accounts for the electrothermal effect. The model was exploited in an automatic tool which translates an AutoCAD project of a PV plant in an equivalent circuit netlist. Finally, the results were employed to investigate the effectiveness of distributed power conversion – in particular the efficiency of the multilevel cascaded H bridge converter controlled by means of an innovative strategy, which overcomes some issues related to the need of performing a distributed MPPT, was assessed

Energy Harvesting and Energy Storage Systems

This book discuss the recent developments in energy harvesting and energy storage systems. Sustainable development systems are based on three pillars: economic development, environmental stewardship, and social equity. One of the guiding principles for finding the balance between these pillars is to limit the use of non-renewable energy sources