Small-scale, residential, and distributed energy resources (DER), which are electric vehicles (EVs), heat pumps (HPs), and photovoltaic (PV) arrays, were studied to evaluate their impact on the UK future residential demand and their impact on UK distribution networks. Centralized and decentralized controllers were planned in order to defer reinforcement, while connecting DER units to distribution networks. The centralized controller allocates EV charging durations considering network constraints. The decentralized controller adjusts EV and HP loads based on consumer satisfaction, network constraints, and electricity prices. Normal probability distribution and median filter were used to predict aggregated power of EVs, HPs, and PV arrays on a half-hourly basis over a year. Because of an expected surplus of PV power generation, a considerable demand reduction followed by a sharp demand increase will occur with these residential DER units during summer days in 2035. A low voltage section of test network was used to study the impact of uncontrolled EV charging loads on a three-phase four-wire system. Different combinations of EVs, HPs, and PV arrays were used to investigate their uncertainties in a low voltage section of real network. Real-world trials were used to generate the individual power of residential customers and DER units. Results of unbalanced power flow indicated that network constraints exceeded their limits with a high number of these low carbon technologies. Using an extended section of the test network, the central controller maintains voltage magnitudes, voltage unbalance factors, and power flows within their limits, by re-allocating EV charging durations accordingly. The decentralized controller was designed to minimize electricity bills of EV and HP users. This controller adjusts EV and HP loads to maintain consumer satisfaction and network constraints within their specified boundaries. Consumer satisfaction was determined using mathematical models of EV battery state-of-charge levels and the indoor temperatures of HP houses. The decentralized controller was used to connect predicted numbers of EVs and HPs to a real distribution network, while overcoming the need for network reinforcement, third parties (aggregators), and extensive communication systems.

Nitrogen constitutes a natural part of air and is a non-global warming gas. There have been recent attempts to use it as a working medium in high voltage circuit breakers to replace SF6, which is an excellent insulating and arc quenching gas but also a strong greenhouse gas with a Global Warming Potential (GWP) of 23,900 and a life time of 3,200 years. To employ the full potential of nitrogen for use in high voltage circuit breakers, the properties and radiation characteristics of its mixture with Polytetrafluoroethylene (PTFE) vapour, an electrical and thermal insulation material, need to be known, forming the objectives of the present work. This research has investigated the capability of nitrogen and SF6 on insulating and quenching an electric arc in a high voltage circuit breaker. Depending on the current of the electric arc range from 100 A to 330 A, the arc can be extinguished in 25-50 ms with nitrogen gas flow, while it takes 20-45 ms with SF6. The peak voltage of the electric arc with SF6 is 10% higher than it is with nitrogen. According to the preliminary data obtained in the experimental investigation, it seems possible that SF6 can be replaced by nitrogen as the operation gas in high voltage circuit breakers. Research on the properties and radiation characteristics of a gas mixture of nitrogen and PTFE is required to allow modelling of a nitrogen filled circuit breaker. Net Emission Coefficient (NEC) describes the radiation characteristics of the hottest area in an electric arc. The NEC of a nitrogen and PTFE mixture is computed by using the most advanced method considering both continuum and line radiation. The result shows that the influence of PTFE on the NEC cannot be neglected. The influence of uncertainty in atomic data on the calculated NEC is studied. A 50% adjustment in the uncertainty of the atomic data on high energy levels results in a 0.001% variation of the NEC because of the low population density of the particles with high energy levels involved. Due to the lack of experimental results of the mixture, the validity of the model is confirmed by a good agreement between the results calculated and those obtained by experiments or those predicted by the other research groups for pure nitrogen gas and pure PTFE vapour. Results show that influence of PTFE vapour on the NEC of the mixture is substantial. It has been determined that the NEC of the mixture cannot be estimated by NEC of the pure gases multiplied by their proportions in the mixture. Re-absorption has to be considered when the temperature is lower than 25,000 K. To solve the Radiation Transfer Equation (RTE), the P1 and Discrete Ordinate Method (DOM) have been used to calculate the radiation with re-absorption. The P1 approximation is computationally cheaper but it has poor accuracy. The accuracy of DOM is determined by the number of calculation bands. It is obvious that the more bands used, the higher the accuracy. A comparison of the DOM 8-5 and 5-3 methods indicates a balanced compromise between accuracy and cost of calculation with DOM 8-5. A two-temperature model was applied to solve the properties of the plasma in non-LTE condition when the temperature gradient is sufficiently high. A number of existing calculation methods are discussed. A modification of Godin's method has been proposed to satisfy the two-temperature model. Results of a gas mixture composition, obtained by different methods, are analysed. The modified method leads to results that agree very well with those from the existing methods but with better convergence that when the Newton-Raphson algorithm is used to obtain the solution. Results with different molar percentages of PTFE vapour have been presented and discussed. The results for pure nitrogen and pure PTFE vapour have been compared with existing data to verify the validity of the method.

The current distribution network operation and planning framework is rather centralised. The distribution network operator (DNO) makes decisions on congestion management and network upgrades without communicating with the consumers and taking into account their actual valuation of electricity supply and flexibility. Customers’ valuation, reflecting their willingness to curtail or reschedule their loads, is based on their requirements, preferences and perceptions regarding energy use. This value is currently assumed identical 1) for all consumers of the same type (i.e., residential, commercial and industrial) and 2) for every unit of energy supplied, irrespective of the specific service it provides to the consumer. Furthermore, specific operations of time-coupling technologies, such as electric vehicles and wet appliances, are not integrated in the current framework. Therefore, their valuation of supply is disregarded in distribution network planning. The time-coupling technologies provide the opportunity for DNOs to redistribute the energy over the time instead of reducing the demand. Finally, the current distribution network charging schemes are based on the overall customers’ energy consumption or capacity and not the differentiated impacts of individual user preferences. Hence, they do not accurately reflect the contribution of each customer to the total network expenditure. Building on the advanced metering and control capabilities of the emerging smart grid, this work explores the impact of integrating the differentiated valuation of electricity supply for different customers and different levels of supplied energy in distribution network planning. To quantify customers’ valuation, their flexibilities are modelled based on their willingness to curtail and reschedule their loads to avoid additional network charges. Customer interruption costs are then reduced, since the supply interruption of customers with low supply valuation and the non-critical part of their demand is prioritised during network failures. As a result, the need for capital-intensive network reinforcements is limited and the total network expenditure is reduced. Finally, a cost-reflective network charging scheme based on the principles of locational marginal pricing is proposed. This scheme enables an equitable treatment of customers with differentiated supply valuation as well as full recovery of investment costs for DNOs.

The integration of Distributed Energy Resource (DER) technologies such as heat pumps, electric vehicles and small-scale generation into the electricity grid at the household level is limited by technical constraints. This work argues that location is an important aspect for the control and integration of DER and that network topology can inferred without the use of a centralised network model. It addresses DER integration challenges by presenting a novel approach that uses a decentralised multi-agent system where equipment controllers learn and use their location within the low-voltage section of the power system. Models of electrical networks exhibiting technical constraints were developed. Through theoretical analysis and real network data collection, various sources of location data were identified and new geographical and electrical techniques were developed for deriving network topology using Global Positioning System (GPS) and 24-hour voltage logs. The multi-agent system paradigm and societal structures were examined as an approach to a multi-stakeholder domain and congregations were used as an aid to decentralisation in a non-hierarchical, non-market-based approach. Through formal description of the agent attitude INTEND2, the novel technique of Intention Transfer was applied to an agent congregation to provide an opt-in, collaborative system. Test facilities for multi-agent systems were developed and culminated in a new embedded controller test platform that integrated a real-time dynamic electrical network simulator to provide a full-feedback system integrated with control hardware. Finally, a multi-agent control system was developed and implemented that used location data in providing demand-side response to a voltage excursion, with the goals of improving power quality, reducing generator disconnections, and deferring network reinforcement. The resulting communicating and self-organising energy agent community, as demonstrated on a unique hardware-in-the-loop platform, provides an application model and test facility to inspire agent-based, location-aware smart grid applications across the power systems domain.

Electron injection in dye-sensitized solar cells (DSSC) has been extensively studied in the present thesis. Many transient and steady-state experimental techniques were utilized: ultrafast transient absorption spectroscopy in the visible, near-IR and mid-IR regions; time-correlated single photon counting; incident photon to current conversion measurement; temperature dependence of luminescence and device efficiency; determination of energy conversion efficiency parameters. All these methods were collated and analysed as a whole, providing a very detailed picture of the electron injection. It was found that in devices utilizing the most efficient Ru-bipyridyl dyes and commercially viable, performance optimized iodine/triiodide electrolytes, electron injection kinetics are multiphasic, with significant components in the femtosecond, tens of picoseconds and in nanosecond regimes. The broad non-exponential kinetics gave rise to non-100% efficient injection. A fraction of the dyes manage to decay giving rise to luminescence. All of these observations were fully quantified and validated by performing measurements on different systems. The huge length of the delay lines in TAS measurements and very broad probe wavelengths used in the current work gave a very detailed picture of the injection process. Along the way, some very basic experiments were done, which added confidence to the results obtained in the thesis. In addition, interesting phenomena occurring in the ultrafast timescales were found and spectra of transient species such as the dye excited states were recorded. Finally, relevance of the current work to the practical aspects of the solar cells was described and future work discussed.

Hybrid perovskite semiconductors from the MAPbX3 family (MA= CH3NH3; X = I, Br, Cl) can be used to make efficient ( > 22 %) solar cells despite disorder introduced by solution processing. Much remains to be understood about these materials. Optical constants of MAPbX3 single crystals derived from ellipsometry measurements are assigned to inter-band transitions from electronic structure calculations. These are used to simulate the contributions from different optical transitions to a typical transient absorption spectrum. The ellipsometry measurements are further used to show the reversible formation of CH3NH3PbI2·H2O and/or (CH3NH3)4PbI6·2H2O in single crystals thin films and devices upon exposure of MAPbI3 to water vapour, which is an important degradation pathway. Quasi-elastic neutron measurements allowed the dynamics of MA cations to be probed in the material. The dipolar MA+ reorientate between preferred alignments with a room temperature residence time of ~14 ps. Collective realignment of MA+ to screen a device’s built-in potential could reduce photovoltaic performance. However, the timescale for a domain wall to traverse a typical device is roughly estimated to be ~0.1 – 1 ms, faster than most observed hysteresis in MAPbI3 solar cells. Temperature dependent Raman and terahertz spectroscopy measurements indicate that MA+ reorientations are crucial to the transport properties of the material. Most of the vibrational features in MAPbX3 observed between 50 and 3500 cm-1 are assigned to calculated vibrational modes. The presence of additional peaks in the experimental spectra might be due to mode splitting caused by dynamic effects. The spectral linewidths of MAPbX3 indicate unusually short phonon lifetimes, linked to its low lattice thermal conductivity. This suggests that optical rather than acoustic phonon scattering prevails at room temperature in these materials, limiting charge mobility. These findings highlight the central role of disorder and heterogeneity to the optoelectronic properties of MAPbX3 and its impact on device behaviour and stability.

Accurate on-board temperature monitoring of lithium-ion batteries is important for safety and control purposes. Impedance temperature detection (ITD) is a promising approach for temperature estimation, whereby the internal cell temperature is directly inferred from online electrochemical impedance spectroscopy (EIS) measurements at a single frequency. Previously, ITD was used to infer the volume-average cell temperature; the present work focuses on extending ITD to enable estimation of the spatially-resolved temperature distribution of cells with internal temperature gradients. Two novel hybrid methods for temperature monitoring are introduced, based on combining impedance measurements with (i) an additional surface temperature measurement, and (ii) a thermal model. These methods predict the temperature distribution of the cell in either 1-D or 2-D, and can therefore identify localised hot spots, and hence the global maximum cell temperature. In each case, the methods are experimentally validated using cylindrical LiFePO4 cells (26650 for the 1-D experiments, 32113 for the 2-D experiments) monitored with periodic 215 Hz impedance measurements, and fitted with an internal thermocouple and one or more surface thermocouples for validation. Method (i) is shown to be more accurate than a standard ITD method based on impedance measurement only: e = 0.6?C vs. 2.6?C respectively, over a 3500 s drive cycle. In method (ii), the impedance measurement forms part of a state/parameter estimation algorithm; in this case, the performance of an extended Kalman filter using impedance measurement is shown to be comparable - although slightly inferior - to an equivalent Kalman Filter using a conventional surface temperature measurement. This work also presents a novel low-order 2-D thermal model based on the spectral-Galerkin (SG) method. The model can be used in conjunction with the proposed hybrid methods or in a conventional temperature monitoring scheme. Time- and frequency domain simulations show that the SG model using as few as 4 states is capable of accurately modelling the thermal dynamics of a large format cylindrical cell with a highly transient heat generation input. The model can account for different external temperatures and/or convection coefficients at each surface - a generality which makes it suitable for simulating various battery cooling configurations.

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This thesis describes multilevel converters (MLC) designed for use with a repurposed electronic vehicle battery (battery 2nd life). MLC is of particular interest due to the low harmonic distortion content and reduced voltage stress in the switching devices. A detailed study of the MLC topologies and modulation techniques is presented. Space vector modulation is analysed and implemented to evaluate the converter. A comprehensive assessment of the MLC is presented using wide bandgap (WBG) devices highlighting the devices’ thermal and high switching frequency features.