Voltage Sensing Using an Asynchronous Charge-to-Digital Converter for Energy-Autonomous Environments

In future systems with relatively unreliable and unpredictable energy sources such as harvesters, the system power supply may become non-deterministic. For energy effective operations, Vdd is an important parameter in any meaningful system control mechanism. Reliable and accurate on-chip voltage sensors are therefore indispensible for the power and computation management of such systems. Existing voltage sensing methods are not suitable because they usually require a stable and known reference (voltage, current, time, frequency, etc.), which is difficult to obtain in this environment. This paper describes an autonomous reference-free voltage sensor designed using an asynchronous counter powered by the charge on a capacitor and a small controller. Unlike existing methods, the voltage information is directly generated as a digital code. The sensor, fabricated in the 180 nm technology node, was tested successfully through performing measurements over the voltage range from 1.8 V down to 0.8 V.

Selecting users in energy-efficient collaborative spectrum sensing

Cognitive radio network is defined as an intelligent wireless communication network that should be able to adaptively reconfigure its communication parameters to meet the demands of the transmission network or the user. In this context one possible way to utilize unused licensed spectrum without interfering with incumbent users is through spectrum sensing. Due to channel uncertainties, single cognitive (opportunistic) user cannot make a decision reliably and hence collaboration among multiple users is often required. Here collaboration among large number of users tends to increase power consumption and introduces large communication overheads. In this paper, the number of collaborating users is optimized in order to maximize the probability of detection for any given power budget in a cognitive radio network, while satisfying constraints on the false alarm probability. We show that for the maximum probability of detection, collaboration of only a subset of available opportunistic users is required. The robustness of our proposed spectrum sensing algorithm is also examined under flat Rayleigh fading and AWGN channel conditions.

The opportunities and limitations of using CFD in the development of wave energy converters

Most Wave Energy Converters (WECs) being developed are fundamentally different from known marine structures. Limited experience is a fundamental challenge for the design, especially issues concerning load assumptions and power estimates. Reynolds-Averaged Navier-Stokes (RANS) CFD methods are being used successfully in many areas of marine engineering. They have been shown to accurately simulate many hydrodynamic effects and are a helpful tool for investigating complex flows. The major drawback is the significant computational power required and the associated overhead with pre and post-processing. This paper presents the challenges and advantages in the application of RANS CFD methods in the design process of a wave energy converter and compares the time, labour and ultimately financial requirements for obtaining practical results.

The effect of the spectral distribution of wave energy on the performance of a bottom hinged flap type wave energy converter

The power output from a wave energy converter is typically predicted using experimental and/or numerical modelling techniques. In order to yield meaningful results the relevant characteristics of the device, together with those of the wave climate must be modelled with sufficient accuracy.

The wave climate is commonly described using a scatter table of sea states defined according to parameters related to wave height and period. These sea states are traditionally modelled with the spectral distribution of energy defined according to some empirical formulation. Since the response of most wave energy converters vary at different frequencies of excitation, their performance in a particular sea state may be expected to depend on the choice of spectral shape employed rather than simply the spectral parameters. Estimates of energy production may therefore be affected if the spectral distribution of wave energy at the deployment site is not well modelled. Furthermore, validation of the model may be affected by differences between the observed full scale spectral energy distribution and the spectrum used to model it.

This paper investigates the sensitivity of the performance of a bottom hinged flap type wave energy converter to the spectral energy distribution of the incident waves. This is investigated experimentally using a 1:20 scale model of Aquamarine Power’s Oyster wave energy converter, a bottom hinged flap type device situated at the European Marine Energy Centre (EMEC) in approximately 13m water depth. The performance of the model is tested in sea states defined according to the same wave height and period parameters but adhering to different spectral energy distributions.

The results of these tests show that power capture is reduced with increasing spectral bandwidth. This result is explored with consideration of the spectral response of the device in irregular wave conditions. The implications of this result are discussed in the context of validation of the model against particular prototype data sets and estimation of annual energy production.

Design of Scaled Bridge Prototype for Energy Harvesting Testing

Energy harvesting from ambient vibration is a promising field, especially for applications in larger infrastructures such as bridges. These structures are more frequently monitored for damage detection because of their extended life, increased traffic load and environmental deterioration. In this regard, the possibility of sourcing the power necessary for the sensors from devices embedded in the structure, thus cutting the cost due to the management of battery replacing over the lifespan of the structure, is particularly attracting. Among others, piezoelectric devices have proven to be especially effective and easy to apply since they can be bonded to existing host structure. For these devices the energy harvesting capacity is achieved directly from the variation in the strain conditions from the surface of the structure. However these systems need to undergo significant research for optimisation of their harvesting capacity and for assessing the feasibility of application to various ranges of bridge span and load. In this regard scaled bridge prototypes can be effectively used not only to assess numerical models and studies in an inexpensive and repeatable way but also to test the electronic devices under realistic field conditions. In this paper the theory of physical similitude is applied to the design of bridge beams with embedded energy harvesting systems and health monitoring sensors. It will show both how bridge beams can be scaled in such a way to apply and test energy harvesting systems and 2) how experimental data from existing bridges can be applied to prototypes in a laboratory environment. The study will be used for assessing the reliability of the system over a train bridge case study undergoing a set load cycles and induced localised damage.

Investigation of the process energy demand in polymer extrusion: a brief review and an experimental study

Extrusion is one of the fundamental production methods in the polymer processing industry and is used in the production of a large number of commodities in a diverse industrial sector. Being an energy intensive production method, process energy efficiency is one of the major concerns and the selection of the most energy efficient processing conditions is a key to reducing operating costs. Usually, extruders consume energy through the drive motor, barrel heaters, cooling fans, cooling water pumps, gear pumps, etc. Typically the drive motor is the largest energy consuming device in an extruder while barrel/die heaters are responsible for the second largest energy demand. This study is focused on investigating the total energy demand of an extrusion plant under various processing conditions while identifying ways to optimise the energy efficiency. Initially, a review was carried out on the monitoring and modelling of the energy consumption in polymer extrusion. Also, the power factor, energy demand and losses of a typical extrusion plant were discussed in detail. The mass throughput, total energy consumption and power factor of an extruder were experimentally observed over different processing conditions and the total extruder energy demand was modelled empirically and also using a commercially available extrusion simulation software. The experimental results show that extruder energy demand is heavily coupled between the machine, material and process parameters. The total power predicted by the simulation software exhibits a lagging offset compared with the experimental measurements. Empirical models are in good agreement with the experimental measurements and hence these can be used in studying process energy behaviour in detail and to identify ways to optimise the process energy efficiency.

A quality-scalable and energy-efficient approach for spectral analysis of heart rate variability

Today there is a growing interest in the integration of health monitoring applications in portable devices necessitating the development of methods that improve the energy efficiency of such systems. In this paper, we present a systematic approach that enables energy-quality trade-offs in spectral analysis systems for bio-signals, which are useful in monitoring various health conditions as those associated with the heart-rate. To enable such trade-offs, the processed signals are expressed initially in a basis in which significant components that carry most of the relevant information can be easily distinguished from the parts that influence the output to a lesser extent. Such a classification allows the pruning of operations associated with the less significant signal components leading to power savings with minor quality loss since only less useful parts are pruned under the given requirements. To exploit the attributes of the modified spectral analysis system, thresholding rules are determined and adopted at design- and run-time, allowing the static or dynamic pruning of less-useful operations based on the accuracy and energy requirements. The proposed algorithm is implemented on a typical sensor node simulator and results show up-to 82% energy savings when static pruning is combined with voltage and frequency scaling, compared to the conventional algorithm in which such trade-offs were not available. In addition, experiments with numerous cardiac samples of various patients show that such energy savings come with a 4.9% average accuracy loss, which does not affect the system detection capability of sinus-arrhythmia which was used as a test case. 

Thermography-based virtual MPPT scheme for improving PV energy efficiency under partial shading conditions

This paper proposes a new thermography-based maximum power point tracking (MPPT) scheme to address photovoltaic (PV) partial shading faults. Solar power generation utilizes a large number of PV cells connected in series and in parallel in an array, and that are physically distributed across a large field. When a PV module is faulted or partial shading occurs, the PV system sees a nonuniform distribution of generated electrical power and thermal profile, and the generation of multiple maximum power points (MPPs). If left untreated, this reduces the overall power generation and severe faults may propagate, resulting in damage to the system. In this paper, a thermal camera is employed for fault detection and a new MPPT scheme is developed to alter the operating point to match an optimized MPP. Extensive data mining is conducted on the images from the thermal camera in order to locate global MPPs. Based on this, a virtual MPPT is set out to find the global MPP. This can reduce MPPT time and be used to calculate the MPP reference voltage. Finally, the proposed methodology is experimentally implemented and validated by tests on a 600-W PV array. 

Energy Saving - Another Perspective for Parameter Optimization of P and PI Controllers

Modern control methods like optimal control and model predictive control (MPC) provide a framework for simultaneous regulation of the tracking performance and limiting the control energy, thus have been widely deployed in industrial applications. Yet, due to its simplicity and robustness, the conventional P (Proportional) and PI (Proportional–Integral) control are still the most common methods used in many engineering systems, such as electric power systems, automotive, and Heating, Ventilation and Air Conditioning (HVAC) for buildings, where energy efficiency and energy saving are the critical issues to be addressed. Yet, little has been done so far to explore the effect of its parameter tuning on both the system performance and control energy consumption, and how these two objectives are correlated within the P and PI control framework. In this paper, the P and PI controllers are designed with a simultaneous consideration of these two aspects. Two case studies are investigated in detail, including the control of Voltage Source Converters (VSCs) for transmitting offshore wind power to onshore AC grid through High Voltage DC links, and the control of HVAC systems. Results reveal that there exists a better trade-off between the tracking performance and the control energy through a proper choice of the P and PI controller parameters.

Economical and coordinated dispatch of CHP based microgrid with renewable energy resources

The advantages of high energy efficiency and economic benefit promote the wide application of combined heat and power system (CHP) based microgrid. Firstly, a mathematical model of the CHP based microgrid is developed. Then, a cost function for the coordination of heat and electric load is proposed. Finally, an optimal dispatch model is developed to achieve the economical and coordinated operation of the CHP based microgrid system. Simulation results verify effectiveness of the proposed dispatch model, which is a powerful tool for the energy management of CHP based microgrid with renewable energy resources.

Energy and environmental forensic analysis for public buildings.

This paper outlines a forensic method for analysing the energy, environmental and comfort performance of a building. The method has been applied to a recently developed event space in an Irish public building, which was evaluated using on-site field studies, data analysis, building simulation and occupant surveying. The method allows for consideration of both the technological and anthropological aspects of the building in use and for the identification of unsustainable operational practice and emerging problems. The forensic analysis identified energy savings of up to 50%, enabling a more sustainable, lower-energy operational future for the building. The building forensic analysis method presented in this paper is now planned for use in other public and commercial buildings.