The possibility of absorbing wave energy using a submerged balloon fixed to the sea bed is investigated. The balloon is in the form of a fabric encased within an array of meridional tendons which terminate at a point at the top of the balloon and at some radius at the bottom. The expansion and contraction of the balloon in waves pump air via a turbine into and out of a chamber of constant volume. A more refined model than that used by Kurniawan and Greaves [Proc. Second Offshore Energy and Storage Symp., 2015] predicts a similarly broad-banded response, but the maximum absorption is less than previously predicted. Both approaches are compared and discussed.

One of the big issues ocean-wave energy faces nowadays is the oscillation of the generated power. Among others, energy storage is a solution that has been widely proposed and validated for an adequate grid or isolated load integration. However, the unpredictability of ocean waves may pose a challenge when specifying the energy storage system (ESS) technology and specifications, especially in the case of stand-alone operation. This study presents a suitable methodology for the design of a certain wave energy converter (WEC) and the calculation of a certain stochastic model of the latter necessary for the subsequent sizing of the ESS. As a result, the storage system is defined in terms of energy, power and type of technology for the specific WEC and chosen location. The problem is accomplished in this study describing systematically the method and solving a particular example of the design of a wave converter in the Gulf of Mexico.

The authors study an independent grid where the penetration of wind energy is high and exploit the joint planning of energy storage and a renewable energy source, as it can potentially result in a more economical and efficient energy system. More specifically, they consider an energy system that consists of a gas-fired plant, and a small wind farm with a capacity for energy storage. They assume that the gas-fired plant has a maximum generation capacity that is no more than the electricity demand. They first propose an optimisation model with known wind speed and electricity demand. Then they gradually extend this deterministic model to take into account the stochastic nature of the renewable energy source and electricity demand. Furthermore, they consider the possibility of connecting their system to the National Grid, which they import from or export to when their system has an energy shortage or surplus in meeting the demand. Their results provide helpful insights in planning the joint deployment of generation capacity and energy storage, and show that the system operates more efficiently and economically when it is connected to the National Grid.

The use of hydraulic power transmission to transport offshore wind energy from deep offshore sites to shore may present a more feasible option for integrating wind farms with land-based hydro-energy storage systems. Yet the incurred losses resulting from fluid friction are significantly larger than those encountered in electrical power cables. This study investigates the possibility of compensating for such losses by exploiting cold deep-seawater (DSW) from below thermoclines. A numerical study simulating a single large-scale offshore wind turbine-driven pump supplying DSW to shore across a pipeline in the Central Mediterranean is presented. Seawater leaving the grid-connected hydroelectric power plant is allowed to flow through a centralised district air-conditioning unit operating on a vapour compression cycle. Any shortfall in DSW supply due to lack of wind is compensated for by sea surface water to maintain a constant flow rate. The analysis is repeated for seawater pipelines having different sizes. It is shown that the deep seawater supply from the offshore wind turbine, though being intermittent, reduces the energy consumption of the air-conditioning system considerably. The resulting savings are found to compensate for a significant proportion of the losses encountered in the hydraulic transmission pipeline.

A scheme for bulk electricity storage known as Pumped Thermal Energy Storage (PTES) is described. PTES uses a heat pump during the charging phase to create a hot and a cold storage space. During discharge, these thermal stores are depleted using a heat engine. This version of PTES uses packed beds (or pebble beds) as the energy store. A relatively new design feature which involves segmenting the packed beds is introduced. Various thermodynamic benefits can be achieved by reservoir segmentation, such as reduced pressure losses and increased energy stored per cycle. This report includes modelling of the storage phases, and it is found that segmentation can reduce the thermal equilibration losses that occur. A simple economic model of the PTES system is introduced so that multi-objective optimisation of efficiency and capital costs can be carried out. Sensitivity to the economic factors is briefly explored. The results show that cold packed beds in particular benefit from being segmented.

A compressed air energy storage system that uses a high pressure, isothermal air compressor/expander (C/E) has no carbon emission and is more efficient than a conventional system that uses fossil fuels. To be successful, the compressor/expander must be efficient and has high power density. However, there is a trade-off between efficiency and power density due to heat transfer. The authors’ previous work has shown that by optimising the compression/expansion trajectories in a liquid piston C/E, the power density can be improved by many times without sacrificing efficiency. Yet, to achieve the optimised trajectory, this requires a large liquid piston pump/motor that often operates at low displacement, low efficiency regime. This study proposes that by combining the liquid piston with a solid piston actuated via a hydraulic intensifier, the pump/motor size can be reduced significantly. A case study shows that with an optimal intensifier ratio, the pump/motor size is reduced by 85%, the ratio between maximum and minimum displacements is reduced by 7 times, and the mean efficiency is increased by 2.4 times. A full cycle dynamic simulation shows that the intensifier decreases, for the same pump/motor size, the total cycle time for over 50%, thus doubling the power density of the compressor/expander.

This study concerns about the heat transfer behaviour of composite phase change materials (CPCMs) based thermal energy storage components. Two types of components, a single tube and a concentric tube component, are designed and investigated. The CPCMs consist of a molten salt based phase change material, a thermal conductivity enhancement material (TCEM) and a ceramic skeleton material. A mathematical model was established to model the heat transfer behaviour. The modelling results were first compared with experiments and reasonably good agreement with the experimental data was obtained, demonstrating the reliability of the model. Extensive modelling studies were then carried out under different conditions. The influence of thermoproperties, surface roughness and size of the CPCMs as well as heat transfer fluid (HTF) velocity were examined. The results show that the thermal contact resistance between the CPCMs should be considered. Increasing the mass fraction of TCEMs and thickness of CPCMs as well as the HTF velocity intensifies the heat transfer behaviour of component. The concentric tube based component offers a better heat transfer performance compared with the single tube based component, with the total heat storage and release time ∼10 and 15% shorter, respectively, for a given set of conditions.

Buoyancy battery underwater energy storage is an emerging area of research relating to the storage of energy generated by renewable resources such as offshore wind and solar. This study presents an experimental analysis of a basic buoyancy system. Tests were performed on a container with minimal ambient fluid volume, as well as in a large offshore testing tank. Development and integration of fundamental system components is discussed in terms of experimental apparatus and larger application. Discharge cycling was performed with variables relating to discharge voltage, power, and discharge velocity obtained. Energy losses to kinetic energy and hydrodynamic drag are estimated for completed trails. The effect of pulley friction is evaluated for no-load discharge testing. Conclusions are drawn as to the observed operation of the system as designed, primary areas for performance improvements, and next steps for system development.

This study reports the effect of iron sulphide and copper composites on the electrochemical performance of nickel–iron batteries. Nickel stripes were coated with an iron-rich electroactive paste and were cycled against commercial nickel electrodes. The electrodes electrochemical and physical characterisation were carried out by using galvanostatic charge/discharge, cyclic voltammetry, X-ray diffraction, and atomic force microscopy techniques. The authors’ experimental results would indicate that the addition of iron sulphide and copper (II) sulphate significantly enhances the performance of the battery. Their in-house made iron-based electrodes exhibit good performance, with great potential for grid energy storage applications.

Grid connected electrical energy storage is expected to enable the integration of variable renewable generation in the future. As the electricity sector develops wholesale electricity prices will change, which will change the way in which storage technologies are operated. This study investigates the sensitivity of storage revenue to uncertain market variables. Results indicate that higher gas prices, carbon prices and average demand would increase peak electricity prices, leading to larger daily price spreads and increased storage revenue. Increased wind generation, however, would reduce opportunities for price arbitrage and lessen storage revenue. Wind power also affects the way in which devices are operated and changes the characteristics which are rewarded by the market. With increased wind capacity, storage devices cycle less regularly as operation is driven by substantial changes in wind power output, rather than daily demand patterns. As a result, slower discharge times are more favourable and revenue is more sensitive to rates of self-discharge. Furthermore, there is less variation in wholesale electricity price and consequently conversion efficiency is more critical to performance.

This study provides review of grid-tied architectures used in photovoltaic (PV) power systems, classified by the granularity level at which maximum power point tracking (MPPT) is applied. Grid-tied PV power systems can be divided into two main groups, namely centralised MPPT and distributed MPPT (DMPPT). The DMPPT systems are further classified according to the levels at which MPPT can be applied, i.e. string, module, submodule, and cell level. Typical topologies for each category are also introduced, explained and analysed. The classification is intended to help readers understand the latest developments of grid-tied PV power systems and inform research directions.

This study proposes a new back-to-back current source converter (BTB-CSC) suitable for medium-voltage high power wind energy conversion systems (WECSs). It employs a dual three-phase permanent magnet synchronous generator and two current source inverters with a phase-shift transformer at the grid side. The proposed BTB-CSC has the following advantages: reduced power circuit and control complexity; low switching losses (zero switching losses at the inverter side); and independent control of active and reactive powers. Power system computer aided design (PSCAD)/electromagnetic transients including DC (EMTDC) simulations are used as to assess the steady state and dynamic behaviour of the proposed system under different operating conditions. It is shown that the proposed WECS can ride-through ac faults. Experimental results from scaled prototype of the proposed WECS are used to validate the simulations.

The development of battery energy storage system (BESS) facilitates the integration of renewable energy sources in the distribution system. Both distribution generation and mobile BESS (MBESS) can enhance the reliability of the distribution system. MBESS can facilitate the island operation of microgrids. This study proposes a set of methodologies to assess the reliability of power distribution network with the penetrations of MBESS and intermittent distribution sources. First, an analytic approach based on Markov models is applied for assessing the reliability analysis of the MBESS in distribution system. Then the method is verified by Monte Carlo simulation method and extended to a more complex distribution system. The model of MBESS is developed based on the real operation data. Case study on the IEEE test system has successfully verified the effectiveness of the proposed approach.

Renewable energy penetration in the low-voltage grid faces several limitations due to the current grid topology. Master/slave micro-grids could help solving these issues, by offering additional services to the grid such as the power management of the distributed power energy sources. In some cases, the power produced by the distributed energy sources exceeds the local consumption of the low-voltage grid. The consequent reverse power flow can be either dangerous (for the medium voltage) or impossible (for a micro-grid with limited storage). The droop characteristic of commercial inverter can be exploited to avoid this behaviour. However, stability problems can arise due to a low phase-locked-loop (PLL) bandwidth. This study investigates the stability of this solution depending on the bandwidth of the PLL of the distributed power generation sources.

Low-voltage distribution grids (LV) experience unbalanced voltage condition due to the high penetration levels of rooftop mounted single-phase photovoltaic (PV), the existence of single-phase transformers, unbalanced cable impedances and different load levels on each phase. The voltage unbalance (VU) has a harmful impact on the loads and equipment connected to grid that leads to overheating and fast thermal ageing. There are several solutions proposed to mitigate the VU, that requires the installation of extra hardware components or incorporate complex type of controllers that need special tuning procedures and special arrangements. Therefore, in this study a new and simple control approach of three-phase grid connected PV inverter is proposed to mitigate the unbalanced voltage. The new control approach is able to fully mitigate the unbalanced voltage without the need to extra hardware installation or negative sequence voltage magnitude and phase angle measurements, provided that the ampacity of the converter is high enough. The new system is tested in a LV grid with high PV penetration from Germany. The results show that the VU factor did not exceed 0.8% at the feeder connection point.

An isolated high-power multi-terminal DC/DC converter is studied in this paper, based on hybrid modular multilevel converter configuration consisting of full-bridge submodules (FBSMs) and half-bridge submodules. To decrease the investment and power losses, a reduced arm FBSMs ratio (<0.5) scheme is adopted. A detailed analysis on the relationship of the DC/DC converter inner AC voltage and the arm FBSMs ratio under reduced DC voltage is presented. Based on this, a control strategy during DC fault is proposed which continues operating the converter connected to the faulty DC side with reactive current absorption. Under the same arm FBSMs ratio, compared to the conventional strategy of blocking the faulty side converter during a DC fault, the proposed unblocking method with reactive current injection can not only achieve greater DC fault current declining rate, but also ensure maximum power transfer between the interconnected healthy DC grids by maintaining a higher inner AC voltage in the DC/DC converter. The two strategies are compared and validated by simulations using PSCAD/EMTDC under different arm FBSMs ratio.

This study presents a new strategy for estimating the states (rotor flux and speed) and the load torque to implement a multivariable controller for a sensorless three-phase squirrel-cage induction machine in wind energy conversion systems. The multivariable control is carried out using input–output feedback law and its objective is to track profiles of the rotational speed and the rotor flux amplitude. The state estimation considerably improves the performance of rotor flux based model reference adaptive system in the variable speed region of operation. The technique uses Kalman filter as a rotor flux observer and an artificial neural network adaption mechanism to estimate the rotor speed. The state estimation requires only the measurements of the stator voltages and currents. The estimation method, for both states and torque, is not invasive as no mechanical sensors are needed. The wind energy conversion system and the proposed control-estimation techniques are simulated in Matlab/Simulink software platform and tested using the OPAL-RT real-time simulator (OP5600) to verify the accuracy of the proposed control-estimation method.

This study present a new islanding detection technique based on relevance vector machine (RVM) containing various types of distributed generations (DGs). The proposed scheme is based on utilising negative sequence component of current (I ₂), acquired at the terminal of the target DG. Various islanding and non-islanding events with variable real and reactive power, change in network topology and diverse X/R ratio have been generated by modelling IEEE 34 bus system in real time digital simulator (RTDS^®/RSCAD) environment. The samples of I ₂ for one cycle duration from the inception of islanding/non-islanding events are given as input to the proposed RVM classifier. The proposed classifier is able to discriminate between islanding and non-islanding events with an accuracy of 98.62% by utilising only 40% of the total dataset in training. Moreover, it is capable to classify islanding condition rapidly and correctly even with perfect power balance situation. Furthermore, it remains immune to change in network configuration/entirely different network and X/R ratio of various types of DGs. Comparative analysis of the proposed scheme in terms of accuracy, testing time and number of relevance vectors (RVs) with the existing schemes shows its superiority in discriminating islanding situation with non-islanding events.

A variety of supervised forecasting models using numerical weather prediction data have been utilised for short-term wind power forecasting. These forecasting models only use meteorological variables of the target wind farm as essential features. This study proposes a novel method to improve existing supervised forecasting models such as support vector machines, artificial neural networks, and Gaussian processes (GPs) for higher forecasting accuracy. The proposed method develops a data-driven feature extraction procedure to utilise unlabelled numerical weather data, and the feature extraction procedure transforms extended numerical weather variables into supplementary input features which then can be used for supervised forecasting models. The only modification to an existing supervised forecasting model is the addition of these supplementary input features, and thus does not alter the training algorithm of the supervised forecasting model. For illustrative purposes, the GP is used as the supervised forecasting model to be improved. Numerical evaluation of the proposed method was performed on a subset of data provided in the 2012 Global Energy Forecasting Competition (GEF 2012). Evaluation results reveal that the proposed method achieves higher forecasting accuracy for all wind farms.

This study describes the design and analysis of an anti-phase pendulum motion-based electromagnetic energy harvester. The proposed energy harvester consists of a magnet-based pendulum, a coil-based pendulum, shaft, connecting rod, and housing. Two pendulums were connected in parallel, which can move in anti-phase motion, using a rotatable connecting rod. Mechanical, electrical, and magnetic behaviours were investigated through the simulations (MATLAB, ANSYS Maxwell) and experiments. The anti-phase pendulum motion can reduce the induction time. This phenomenon has the effect of improving the output voltage of the electromagnetic induction, which is experimentally verified. Experimental results demonstrated that the induction time is shortened by 21%, and the output power showed a 37% increase compared with the single-phase pendulum motion. The dependence of the output on the input conditions was also investigated extensively in terms of the frequency, displacement, mass, and electrical load resistance. The maximum output power of 247 μW was obtained at anti-phase pendulum motion. In addition, the proposed anti-phase motion phenomenon can be used effectively to improve the output voltage of an electromagnetic induction-based energy harvester.

This study deals with placement of wind turbines in distribution networks for maximising the probabilistic index of load supply capability (LSC). To calculate this index, one of the most accurate and efficient probabilistic simulation methods known as Latin hypercube sampling is used. Variations of load and output power of wind turbines are considered in the probabilistic evaluation of LSC. Moreover, the constraints of maximum voltage drop and current carrying capacity of conductors are considered as the limiting factors of the network LSC. Since there is a correlation between the network load and the output power of wind turbines, considering this correlation in simulations will push the results closer to reality. Therefore, the Cholesky decomposition approach is used to take into account the correlation between the input variables of the problem. Casestudiesare carried out on the 33-bus IEEE distribution network. The results of case studies demonstrate the effectiveness of the proposed methodology.

In this study, a three-phase grid-tied single-stage solar energy conversion system (SECS) is implemented using a leaky least mean square (LLMS) based control algorithm. The SECS extracts the solar energy from the photovoltaic cells and converts it into electrical energy. The SECS makes use of voltage source inverter to invert the extracted DC power into the three-phase AC power. Apart from SECS, this system configures a three-phase grid, ripple filters and connected linear or non-linear loads. The main objective of this system is to eliminate power quality issues such as harmonics, voltage fluctuations and flickers, unbalancing in loads, reactive power requirement and so on. Moreover, this system operates at unity power factor and zero voltage regulation modes. In this study, SECS employs a single-stage topology controlled by perturb & observe approach of maximum power point tracking technique and for extracting fundamental component of load currents, a LLMS-based adaptive neural network control method is used. This system is modelled, designed and simulated in MATLAB using simpower system toolbox and experimental validation is carried out on a developed prototype in the laboratory.