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[en] A Monte Carlo model of the combined GB gas and electricity network was developed to determine the reliability of the energy infrastructure. The model integrates the gas and electricity network into a single sequential Monte Carlo simulation. The model minimises the combined costs of the gas and electricity network, these include gas supplies, gas storage operation and electricity generation. The Monte Carlo model calculates reliability indices such as loss of load probability and expected energy unserved for the combined gas and electricity network. The intention of this tool is to facilitate reliability analysis of integrated energy systems. Applications of this tool are demonstrated through a case study that quantifies the impact on the reliability of the GB gas and electricity network given uncertainties such as wind variability, gas supply availability and outages to energy infrastructure assets. Analysis is performed over a typical midwinter week on a hypothesised GB gas and electricity network in 2020 that meets European renewable energy targets. The efficacy of doubling GB gas storage capacity on the reliability of the energy system is assessed. The results highlight the value of greater gas storage facilities in enhancing the reliability of the GB energy system given various energy uncertainties. -- Highlights: •A Monte Carlo model of the combined GB gas and electricity network was developed. •Reliability indices are calculated for the combined GB gas and electricity system. •The efficacy of doubling GB gas storage capacity on reliability of the energy system is assessed. •Integrated reliability indices could be used to assess the impact of investment in energy assets
[en] Highlights: • Annual domestic demand by category and daily flexible load profiles are shown to 2030. • Valuable flexible demand requires loads to be identifiable, accessible, and useful. • The extent of flexible demand varies significantly on a diurnal and seasonal basis. • Barriers to accessing domestic demand include multiple low value loads and apathy. • Existing market structure a barrier to fully rewarding individual load flexibility. - Abstract: In order to meet greenhouse gas emissions targets the Great Britain (GB) future electricity supply will include a higher fraction of non-dispatchable generation, increasing opportunities for demand side management to maintain a supply/demand balance. This paper examines the extent of flexible domestic demand (FDD) in GB, its usefulness in system balancing and appropriate incentives to encourage consumers to participate. FDD, classified as electric space and water heating (ESWH), and cold and wet appliances, amounts to 59 TW h in 2012 (113 TW h total domestic demand) and is calculated to increase to 67 TW h in 2030. Summer and winter daily load profiles for flexible loads show significant seasonal and diurnal variations in the total flexible load and between load categories. Low levels of reflective consumer engagement with electricity consumption and a resistance to automation present barriers to effective access to FDD. A value of £1.97/household/year has been calculated for cold appliance loads used for frequency response in 2030, using 2013 market rates. The introduction of smart meters in GB by 2020 will allow access to FDD for system balancing. The low commercial value of individual domestic loads increases the attractiveness of non-financial incentives to fully exploit FDD. It was shown that appliance loads have different characteristics which can contribute to an efficient power system in different ways
[en] Self-assembly of capsid proteins and genome encapsidation are two critical steps in the life cycle of most plant and animal viruses. A theoretical description of such processes from a physiochemical perspective may help better understand viral replication and morphogenesis thus provide fresh insights into the experimental studies of antiviral strategies. In this work, we propose a molecular thermodynamic model for predicting the stability of Hepatitis B virus (HBV) capsids either with or without loading nucleic materials. With the key components represented by coarse-grained thermodynamic models, the theoretical predictions are in excellent agreement with experimental data for the formation free energies of empty T4 capsids over a broad range of temperature and ion concentrations. The theoretical model predicts T3/T4 dimorphism also in good agreement with the capsid formation at in vivo and in vitro conditions. In addition, we have studied the stability of the viral particles in response to physiological cellular conditions with the explicit consideration of the hydrophobic association of capsid subunits, electrostatic interactions, molecular excluded volume effects, entropy of mixing, and conformational changes of the biomolecular species. The course-grained model captures the essential features of the HBV nucleocapsid stability revealed by recent experiments
[en] Highlights: • The SOP’s capability of bringing benefits on multiple objectives simultaneously was investigated. • A multi-objective framework was developed to improve distribution network operation with SOP. • An optimization method integrating both global and local search techniques was proposed. • The optimization method is capable of obtaining diverse Pareto optimal solutions. - Abstract: With the increasing amount of distributed generation (DG) integrated into electrical distribution networks, various operational problems, such as excessive power losses, over-voltage and thermal overloading issues become gradually remarkable. Innovative approaches for power flow and voltage controls are required to ensure the power quality, as well as to accommodate large DG penetrations. Using power electronic devices is one of the approaches. In this paper, a multi-objective optimization framework was proposed to improve the operation of a distribution network with distributed generation and a soft open point (SOP). An SOP is a distribution-level power electronic device with the capability of real-time and accurate active and reactive power flow control. A novel optimization method that integrates a Multi-Objective Particle Swarm Optimization (MOPSO) algorithm and a local search technique – the Taxi-cab method, was proposed to determine the optimal set-points of the SOP, where power loss reduction, feeder load balancing and voltage profile improvement were taken as objectives. The local search technique is integrated to fine tune the non-dominated solutions obtained by the global search technique, overcoming the drawback of MOPSO in local optima trapping. Therefore, the search capability of the integrated method is enhanced compared to the conventional MOPSO algorithm. The proposed methodology was applied to a 69-bus distribution network. Results demonstrated that the integrated method effectively solves the multi-objective optimization problem, and obtains better and more diverse solutions than the conventional MOPSO method. With the DG penetration increasing from 0 to 200%, on average, an SOP reduces power losses by 58.4%, reduces the load balance index by 68.3% and reduces the voltage profile index by 62.1%, all compared to the case without an SOP. Comparisons between SOP and network reconfiguration showed the outperformance of SOP in operation optimization.
[en] Highlights: • A sensitivity method was developed to visualize an SOP operating region in a graphical manner. • Time series of SOP set-points were provided considering various load and generation conditions. • A framework was developed to quantify the SOP operational benefit with different objectives. • This framework is able to facilitate the network operators to select SOP control schemes. - Abstract: A soft open point (SOP) is a power electronic device, usually using back-to-back voltage source converters (VSCs), installed at a previously normally open point of a distribution network. Due to its flexible and accurate control of power flows, an SOP is versatile, and increasingly being considered to mitigate voltage and thermal constraints in medium voltage (MV) networks with high penetrations of distributed generation (DG). A Jacobian matrix - based sensitivity method was used to define the operating region of an SOP when the grids/feeders at the two terminals of the SOP have various load and generation conditions, and the SOP operating region was visualized in a graphical manner. The exact operating set-points were determined by adopting a non-linear optimization considering separately different objectives. The methodology was demonstrated on an 11 kV network, considering three optimization objectives with different DG penetrations and different network observabilities. Results showed that the use of an SOP significantly increases the network’s DG hosting capacity. The objective for voltage profile improvement increased the headroom of the voltage limits by the largest margin, at the expense of increased energy losses. In contrast the objectives to achieve line utilization balancing and energy loss minimization showed the most improvement in circuit utilization and in limiting energy losses. The work helps electricity network operators to visualize an SOP’s operation status, and provides high level decision support, e.g. selecting control schemes and restraining SOP operational boundaries.
[en] Efficient and accurate prediction of the correlation functions of uniform electron gases is of great importance for both practical and theoretical applications. This paper presents a bridge-functional-based classical mapping method for calculating the correlation functions of uniform spin-unpolarized electron gases at finite temperature. The bridge functional is formulated by following Rosenfeld's universality ansatz in combination with the modified fundamental measure theory. The theoretical predictions are in good agreement with recent quantum Monte Carlo results but with negligible computational cost, and the accuracy is better than a previous attempt based on the hypernetted-chain approximation. We find that the classical mapping method is most accurate if the effective mass of electrons increases as the density falls
[en] We introduce a modified classical mapping method to predict the exchange-correlation free energy and the structure of homogeneous electron gases (HEG) at finite temperature. With the classical map temperature parameterized on the basis of the quantum Monte Carlo simulation data for the correlation energy and exact results at high and low temperature limits, the new theoretical procedure greatly improves the classical mapping method for correlating the energetic properties HEG over a broad range of thermodynamic conditions. Improvement can also be identified in predicting the long-range components of the spin-averaged pair correlation functions
[en] Heating is arguably one of the most difficult sectors to decarbonise in the UK's energy system. Meeting the 80% greenhouse gas emission reduction target by 2050 is likely to require that heat related emissions of CO_2 from buildings are near zero by 2050, and there is a 70% reduction in emissions from industry (from 1990 levels). Though it is clear that the use of the natural gas network will reduce over time, recent modelling suggests a limited residual role for gas by 2050 to help meet peaks in heat demand. High levels of uncertainty about the way in which heat will be decarbonised present a number of challenges to policy makers. This paper will explore the risks and uncertainties associated with the transition to a low carbon heat system in the UK as outlined by the 4th carbon budget review. The potential impact of key uncertainties on the levelised costs of heat technologies and the development of energy networks are explored using a sensitivity analysis approach. Policy changes required to decarbonise the heat sector are also examined. - Highlights: • We identify the key uncertainties in decarbonising heat in the UK. • A review on the current status of key heat supply technologies is presented. • The significance of key uncertainties on heat technology costs are analysed. • The impact on the development of the energy network infrastructure is assessed. • The policy and incentives required to decarbonise the heat sector are examined.
[en] This study explored the efficiencies and mechanisms of refractory organic matters removal in the stabilized landfill leachate by adding different reagents. Calcium-based and aluminum-based materials were added into the leachate as comparing experiments. XRD, FTIR, and EEM were adopted to analyze the solid products and leachate. As a result, the in situ synthesized CaAl-LDHs were more beneficial for refractory organic matters removal, especially for benzodiazepines. When CaAl-LDHs were formed, the removal efficiencies of COD, UV254, and TOC were best and achieved 58.48, 81.22, and 71.30%, respectively. For fluorescent substances, humic acid-like and fulvic acid-like compounds were efficiently removed by CaAl-LDHs. In particular, CaAl-LDHs had selective removal effects on fulvic acid-like compounds, which were characteristic of small molecular weight and major carboxyl groups.
[en] Small amounts of an impurity may affect the key properties of an ionic liquid and such effects can be dramatically amplified when the electrolyte is under confinement. Here the classical density functional theory is employed to investigate the impurity effects on the microscopic structure and the performance of ionic-liquid-based electrical double-layer capacitors, also known as supercapacitors. Using a primitive model for ionic species, we study the effects of an impurity on the double layer structure and the integral capacitance of a room temperature ionic liquid in model electrode pores and find that an impurity strongly binding to the surface of a porous electrode can significantly alter the electric double layer structure and dampen the oscillatory dependence of the capacitance with the pore size of the electrode. Meanwhile, a strong affinity of the impurity with the ionic species affects the dependence of the integral capacitance on the pore size. Up to 30% increase in the integral capacitance can be achieved even at a very low impurity bulk concentration. As a result, by comparing with an ionic liquid mixture containing modified ionic species, we find that the cooperative effect of the bounded impurities is mainly responsible for the significant enhancement of the supercapacitor performance.