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The efficiency of solar photovoltaic (PV) panels is greatly reduced by panel soiling and high temperatures. A mechanism for eliminating both of these sources of inefficiencies is presented by integrating solar PV generation with a compressed air system. High-pressure air can be stored and used to blow over the surface of PV panels, removing present dust and cooling the panels, increasing output power. A full-system mathematical model of the proposed system is presented, comprised of compressed air generation and storage, panel temperature, panel cleaning, and PV power generation. Simulation results indicate the benefit of employing compressed air for cleaning and cooling solar PV panels. For a fixed volume of compressed air, it is advantageous to blow air over the panels early in the day if the panel is soiled or when solar radiation is most abundant with the highest achievable flow rate if the panel is clean. These strategies have been shown to achieve the greatest energy captures for a single PV panel. When comparing the energy for air compression to the energy gain from cleaning a single PV over a two-week period, an energy ROI of 23.8 is determined. The system has the potential to eliminate the requirement for additional manual cleaning of solar PV panels.

Solar photovoltaic (PV) panels are subject to inefficiencies from panel soiling and high temperatures. A system is proposed to eliminate these sources by integrating PV generation with a compressed air system. The stored high-pressure air can be used to blow over the surface of the panels, removing present particles and providing a convective cooling effect, increasing overall generation efficiency. A mathematical model of the charging process of the proposed system has been derived, comprising of PV generation, a DC-DC boost converter, DC motor, air compressor and air tank. Closed-loop PID control has been implemented to control the duty cycle of the boost converter to maintain a constant voltage supply to the motor, given a variable voltage source from PV generation. The control has shown to be effective in the extreme cases of change in input radiation to the PV panels. It is expected this work can aid in the further design and development of the integrated PV-compressed air system for cooling and cleaning.

Although the penetration of renewable energy in power systems has been substantially increased globally in the last decade, fossil fuels are still important in providing the essential flexibility required to reliably maintain the system balance. In 2019, more than one quarter of power generation in Europe and over 40% of the UK’s electricity generation was from fossil fuels (mainly gas). For achieving the net-zero greenhouse gas emission target around the middle of this century, these fossil fuels have to be decarbonised in the coming decades. Bulk-scale energy storage has been recognised as a key technology to overcome the reduced dispatchability associated with the decrease of fossil fuels in generation. Taking the UK power system as a case study, this paper presents an assessment of geological resources for bulk-scale compressed air energy storage (CAES), and an optimal planning framework for CAES in combination with solar and wind to replace fossil fuels in the power generation system. The analysis reveals up to 725 GWh of ready-to-use capacity by utilising existing underground salt caverns in the UK. These potential CAES sites with added solar and wind generation equal to the generation from fossil fuels in 2018 can reduce carbon emissions by 84% with a cost increase by 29%, compared to the system in 2018. The results indicate the plausibly achievable cost-effectiveness of CAES as bulk-scale energy storage for power system decarbonisation in countries the geological resources are available.

The compressed air energy storage (CAES) system is a very complex system with multi-time-scale physical processes. Following the development of computational technologies, research on CAES system model simulation is becoming more and more important for resolving challenges in system pre-design, optimization, control and implementation. In this chapter, five types of simulation model for CAES system and components have been explained and compared based on the discharging process of the CAES. Principles for choosing suitable model methods targeting different purposes for CAES system have been described, and a novel data-driven dynamic simulation approach for the complex system is demonstrated. The result shows that the data-driven simulation approach can reduce computational cost sharply and may help build CAES system-level real-time simulation in the future.

The increasing integration of large-scale electricity generation from renewable energy sources in the grid requires support through cheap, reliable, and accessible bulk energy storage technologies, delivering large amounts of electricity both quickly and over extended periods. Compressed air energy storage (CAES) represents such a storage option, with three commercial facilities using salt caverns for storage operational in Germany, the US, and Canada, with CAES now being actively considered in many countries. Massively bedded halite deposits exist in the UK and already host, or are considered for, solution-mined underground gas storage (UGS) caverns. We have assessed those with proven UGS potential for CAES purposes, using a tool developed during the EPSRC-funded IMAGES project, equations for which were validated using operational data from the Huntorf CAES plant. From a calculated total theoretical ‘static’ (one-fill) storage capacity exceeding that of UK electricity demand of ≈300 TWh in 2018, filtering of results suggests a minimum of several tens of TWh exergy storage in salt caverns, which when co-located with renewable energy sources, or connected to the grid for off-peak electricity, offers significant storage contributions to support the UK electricity grid and decarbonisation efforts.

Solar photovoltaics (PV) are becoming one of the main sources of renewable energy to reduce carbon emissions of electricity supply. It is well recognised that dust accumulation and high temperatures result in a dramatic reduction in the performance of PV panels. To improve the efficiency of solar PV panels, a compressed air-based regulation method which can simultaneously clean and cool PV panels is studied and tested. A modelling study of the dust adhesion and detachment mechanism is conducted and the temperature variation caused by the air blowing process is analysed. Dynamic models of the compressed air release are derived which can be used to guide the design of the regulation system for increasing PV power output. A test system is developed for verifying various design and system parameters. The test results are used to validate the suitability of the modelling and illustrate how the inefficiency arising from soiling and high temperatures can be mitigated with the regulated compressed airflow. PV arrays serving in an arid region are adopted for this study and the increased energy yield arising from the cleaning and cooling effects is evaluated via the experimental test. The relationship between the airflow duration, various sizes of particles cleaning from the surface and power generation efficiency improvement is investigated to maximise the net power output increase from the PV panel. The results of this study can contribute to improving PV efficiency and help to realise decarbonisation in energy industry.

Compressed air energy storage is a well-used technology for application in high voltage power systems, but researchers are also investing efforts to minimize the cost of this technology in medium and low voltage power systems. Integration of this energy storage requires a robust control of the power electronic converter to control the power injection due to the dynamic behavior of the system. The conventional linear control design requires a thorough knowledge of the system parameters, but the uncertain disturbances caused by the mechanical properties of the energy storage is neglected in the design and the system fails in presence of such instances. In this paper an adaptive control-based boost converter and sliding mode control-based three phase inverter for a grid integrated compressed air energy storage system of up to 1 kW has been presented that can mitigate any uncertain disturbances in the system without prior knowledge of the system parameters. The experimental results along with the simulation results are also presented to validate the efficiency of the system.

Current power systems are still highly reliant on dispatchable fossil fuels to meet variable electrical demand. As fossil fuel generation is progressively replaced with intermittent and less predictable renewable energy generation to decarbonize the power system, Electrical energy storage (EES) technologies are increasingly required to address the supply-demand balance challenge over a wide range of timescales. However, the current use of EES technologies in power systems is significantly below the estimated capacity required for power decarbonization. This paper presents a comprehensive review of EES technologies and investigates how to accelerate the uptake of EES in power systems by reviewing and discussing techno-economic requirements for EES. Individual EES technologies and power system applications are described, which provides guidance for the appraisal of specific EES technologies for specific power system services. Plausibly required scales and technology types of EES over different regions are then reviewed, followed by discussions on storage cost modelling and predictions for different EES technologies. Opportunities and challenges in developing scalable, economically viable and socio-environmental EES technologies are discussed. The paper explores EES's evolving roles and challenges in power system decarbonization and provides useful information and guidance on EES for further R&D, storage market building and policy making in the transition to zero-carbon power systems.

Compressed-air energy storage (CAES) plants operate by using motors to drive compressors, which compress air to be stored in suitable storage vessels. The energy stored in the compressed air can be released to drive an expander, which in turn drives a generator to produce electricity. Compared with other energy storage (ES) technologies, CAES plants have a very large power rating and storage capacity, low self-discharge, and a long lifetime. These attributes make it the most promising and cost-effective method for bulk ES grid services. Conventional CAES plants have a relatively low roundtrip efficiency; however, research studies into more advanced CAES concepts, such as adiabatic and isothermal CAES, seek to improve this. The world has a large capacity for storing compressed air underground, meaning that CAES could provide a significant amount of the world's future ES needs. This chapter gives the working principals of CAES, compares CAES with other ES technologies, lists the grid services that CAES is most suited to, introduces advanced CAES designs and current projects, examines the exergy analysis of CAES plants and components, reports the global potential for CAES, and offers future research directions and challenges.

Advanced Adiabatic Compressed Air Energy Storage (AA-CAES) has received much attention in the recent years due to its merits of no fossil fuel consumption, low costs, fast start-up and wide-ranging part load ability. It is considered to have a variety of power gird applications including providing reserve services. Although a number of studies are reported in the optimal scheduling strategy of using compressed air energy storage, very few studies have been reported in AA-CAES reserve capacity modelling. This paper presents a reserve capacity model for an AA-CAES facility considering its working mode conversion process, the dynamic characteristics, the air pressure limitations, the thermal storage capacity limitations and the power output limitations of AA-CAES. The developed reserve capacity model is then used in the power system optimal joint energy and reserve scheduling. In the scheduling, the limits on the reserve capacities of Thermal Power Units (TUs) and Interruptible Loads (ILs), which are caused by AA-CAES, are taken into account. The developed scheduling model are used to analyse the impacts of AA-CAES on the system energy and reserve schedules, the system operation costs and the wind curtailment. Numerical simulation results indicate that the participation of AA-CAES in power system operation does not only reduce the system energy and reserve costs, but also mitigate the wind curtailment. However, it is found that AA-CAES is unsuitable for undertaking the system reserve demand alone and using AA-CAES to provide reserve services may increase the system total reserve demand.

As the number of renewable energy sources connected to the grid has increased, the need to address the intermittency of these sources becomes essential. One solution to this problem is to install energy storage technologies on the grid to provide a buffer between supply and demand. One such energy storage technology is Compressed Air Energy Storage (CAES), which is suited to large-scale, long-term energy storage. Large scale CAES requires underground storage caverns, such as the salt caverns situated in the Cheshire Basin, UK. This study uses cavern data from the Cheshire Basin as a basis for performing an energy and exergy analysis of 10 simulated CAES systems to determine the exergy storage potential of the caverns in the Cheshire Basin and the associated work and power input and output. The analysis revealed that a full charge of all 10 caverns could store 25.32 GWh of exergy, which can be converted to 23.19 GWh of work, which requires 43.27 GWh of work to produce, giving a round trip efficiency of around 54%. This corresponds to an input power of 670.07 GW and an output power of 402.74 GW. The Cheshire Basin could support around 100 such CAES plants, giving a potential total exergy storage capacity of 2.53 TWh and a power output of 40 TW. This is a significant amount of storage which could be used to support the UK grid. The total exergy destroyed during a full charge, store, and discharge cycle for each cavern ranged from 299.02 MWh to 1600.00 MWh.

The scroll-type air motor, also named the scroll expander, has been widely used for different applications due to its characteristics of compact structure and high energy conversion efficiency. However, the leakage and the friction result in non-negligible energy losses. This paper presents the recent work on developing a new scroll-type air motor with mounted permanent magnetic spirals and investigates its potential in leakage reduction and efficiency improvement, especially at low-pressure air supply conditions. A method for the implementation of the magnetic scroll air motor is proposed. A prototype is manufactured, and initial experimental tests are conducted to study the generalized torque distribution. A mathematical model for the magnetic scroll air motor is developed, and a corresponding simulation study is presented. The study shows that the proposed magnetic scroll air motor structure is feasible in terms of manufacturing and has the potential to reduce the air leakage and, thus, to improve the energy efficiency by a maximum of around 15% at a supply pressure of 2 x 10(5) Pa, with a flank leakage clearance reference of 0.06 mm.

The field of large-scale electrical energy storage is growing rapidly in both academia and industry, which has driven a fast increase in the research and development on adiabatic compressed air energy storage. The significant challenge of adiabatic compressed air energy storage with its thermal energy storage is in the complexity of the system dynamic characteristics arising from the multi-physical (pneumatic, thermal, mechanical and electrical) processes. This has led to a strong demand for simulation software tools specifically for dynamic modelling and transient control of relevant multi-scale components, subsystems and whole systems with different configurations. The paper presents a feasibility study of a simulation tool development implemented by the University of Warwick Engineering team to achieve this purpose. The developed tool includes a range of validated simulation models from the fields of pneumatics, thermodynamics, heat transfer, electrical machines and power grids. The structure of the developed tool is introduced and a component library is built up on the Matlab/Simulink platform. The mathematical descriptions of key components are presented, which precedes a presentation of four case studies of different applications. The case studies demonstrate that the simulation software tool can be used for dynamic modelling of multi-scale adiabatic compressed air energy storage components and systems, real performance analysis, dynamic control strategy implementation and feasibility studies of applications of adiabatic compressed air energy storage integrated with power grids. The paper concludes that the continued development and use of such a tool is both feasible and valuable.

The trend in the automotive industry is towards electric vehicles (EV), however, the industry will depend on gasoline engines for many years to come. There is also increased demand for the reduction of greenhouse gases. This work develops an adaptive model-based optimal control algorithm based on Sub-Structured Neural Network (SSANN), Multi-Objective Genetic Algorithms (GA), Multi-Objective Dragonfly Algorithm (MODA) and a fuzzy based inference system. The SSANN based on an individual engine speed are combined into a SSANN, whose output is connected to a fuzzy based inference system which extrapolates between trained engine speeds. The SSANN outputs are then used to evaluate the objective function of the optimisation process, which is performed using GA and MODA. The SSANN is retrained if the error is out of defined limit, which allows the system to adapt with engine ageing. The purpose of this work is to contribute to online engine calibration and control to improve engine performance and reduce greenhouse gas emissions.

Air scroll expanders are increasingly used in energy recovery systems, such as Organic Rankine Cycles (ORC) and compressed air exhaust recovery, and in small scale Compressed Air Energy Storage (CAES) systems. Most of these systems use waste high pressure fluid to drive the expander, which in turn provides mechanical energy directly, or drives a generator. The purpose of this work is to investigate the feasibility of combining the expander and generator into one device by modifying an air scroll expander by inserting magnets and coils into the scrolls and exploiting the relative motion between them to directly generate electricity. The magnetic field generated by the magnets is simulated using Finite Element Analysis (FEA) techniques and a 3D printed prototype. It was found that having multiple magnets in the moving scroll produce a magnetic field with numerous peaks of magnetic flux density. The number, position and size of the peaks were dependent on the number, position, size and polarity of the magnets. The presence of peaks in the magnetic flux indicates that the device could be used to generate electricity with the addition of coils and warrants further investigation.

Electricity sector is among the main carbon emissions contributors. This sector has the potential to reduce its carbon emissions through producing electric energy from zero emitting facilities and through the optimization of the consumption in a way to better accommodate low carbon emissions. Hydrogen society per se combined with smart grids, as this is analyzed in this manuscript, can present substantial contribution towards climate change mitigation.

With the increase of power generation from renewable energy sources and due to their intermittent nature, the power grid is facing the great challenge in maintaining the power network stability and reliability. To address the challenge, one of the options is to detach the power generation from consumption via energy storage. The intention of this paper is to give an overview of the current technology developments in compressed air energy storage (CAES) and the future direction of the technology development in this area. Compared with other energy storage technologies, CAES is proven to be a clean and sustainable type of energy storage with the unique features of high capacity and long-duration of the storage. Its scale and cost are similar to pumped hydroelectric storage (PHS), thus CAES has attracted much attention in recent years while further development for PHS is restricted by the availability of suitable geological locations. The paper presents the state-of-the-art of current CAES technology development, analyses the major technological barriers/weaknesses and proposes suggestions for future technology development. This paper should provide a useful reference for CAES technology research and development strategy.

In order to remain competitive, automotive companies use advanced simulation methods to assist in product development. Hardware in the loop (HIL) simulation is one such technique. To use HIL in the development of automotive electronic control units (ECU), accurate simulation models of the ECU's sensors and actuators are needed. In this work, a full dynamic mathematical model of an automotive windshield wiper system is developed and validated. In the modelling phase, the wiper motor is analysed and a unique mathematical model is developed to capture the devices two speed operation. A multi-body dynamic model of the linkages is implemented using the MathWorks' SimMechanics software. The model is validated experimentally and its parameters are identified using genetic algorithms. The model is then simplified to allow it to be simulated in real time, making it suitable for HIL simulation. The HIL compatible model is used in the development of Automotive ECUs.