Development of innovative robust stability enhancement algorithms for distribution systems containing distributed generators

This project was a step forward in improving the voltage profile of traditional low voltage distribution networks with high photovoltaic generation or high peak demand. As a practical and economical solution, the developed methods use a Dynamic Voltage Restorer or DVR, which is a series voltage compensator, for continuous and communication-less power quality enhancement. The placement of DVR in the network is optimised in order to minimise its power rating and cost. In addition, new approaches were developed for grid synchronisation and control of DVR which are integrated with the voltage quality improvement algorithm for stable operation.

Probabilistic load flow for distribution systems with uncertain PV generation

Large integration of solar Photo Voltaic (PV) in distribution network has resulted in over-voltage problems. Several control techniques are developed to address over-voltage problem using Deterministic Load Flow (DLF). However, intermittent characteristics of PV generation require Probabilistic Load Flow (PLF) to introduce variability in analysis that is ignored in DLF. The traditional PLF techniques are not suitable for distribution systems and suffer from several drawbacks such as computational burden (Monte Carlo, Conventional convolution), sensitive accuracy with the complexity of system (point estimation method), requirement of necessary linearization (multi-linear simulation) and convergence problem (Gram–Charlier expansion, Cornish Fisher expansion). In this research, Latin Hypercube Sampling with Cholesky Decomposition (LHS-CD) is used to quantify the over-voltage issues with and without the voltage control algorithm in the distribution network with active generation. LHS technique is verified with a test network and real system from an Australian distribution network service provider. Accuracy and computational burden of simulated results are also compared with Monte Carlo simulations.

Characterization of Actinobacteria Degrading and Tolerating Organic Pollutants

Species of the genera Rhodococcus, Gordonia and Mycobacterium are known as degraders of recalcitrant pollutants. These bacteria are good survivors in harsh environments. Due to such properties these organisms are able to occupy a wide range of environmental niches. The members of these taxa have been suggested as tools for biotechnical applications such as bioremediation and biosynthesis. At the same time several of the species are known as opportunistic human pathogens. Therefore, the detailed characterization of any isolate that has potential for biotechnological applications is very important. This thesis deals with several corynebacterial strains originating from different polluted environments: soil, water-damaged indoor walls, and drinking water distribution systems. A polyphasic taxonomic approach was applied for characterization of the isolates. We found that the strains degrading monoaromatic compounds belonged to Rhodococcus opacus, a species that has not been associated with any health problem. The taxonomic position of strain B293, used for many years in degradation research under different names, was clarified. We assigned it to the species Gordonia polyisoprenivorans. This species is classified under European Biohazard grouping 1, meaning that it is not considered a health hazard for humans. However, there are reports of catheter-associated bacteraemia caused by G. polyisoprenivorans. Our results suggested that the ability of the organism to grow on phthalate esters, used as softeners in medical plastics, may be associated with the colonization of catheters and other devices. In this thesis Mycobacterium lentiflavum, a new emerging opportunistic human pathogen, was isolated from biofilms growing in public drinking water distribution systems. Our report on isolation of M. lentiflavum from water supplies is the second report on this species from drinking water systems, which may thus constitute a reservoir of M. lentiflavum. Automated riboprinting was evaluated for its applicability in rapidly identifying environmental mycobacteria. The technique was found useful in the characterization of several species of rapidly and slowly growing environmental mycobacteria. The second aspect of this thesis refers to characterization of the degradation and tolerance power of several R. opacus, M. murale and G. polyisoprenivorans strains. R. opacus GM-14 utilizes a wide range of aromatic substrates, including benzene, 15 different halobenzenes, 18 phenols and 7 benzoates. This study revealed the high tolerance of R. opacus strains toward toxic hydrophobic compounds. R. opacus GM-14 grew in mineral medium to which benzene or monochlorobenzene was added in amounts of 13 or 3 g l-1, respectively. R. opacus GM-29 utilized toluene and benzene for growth. Strain GM-29 grew in mineral medium with 7 g l-1 of liquid toluene or benzene as the sole carbon source, corresponding to aqueous concentrations of 470 and 650 mg l-1, respectively. Most organic solvents, such as toluene and benzene, due to their high level of hydrophobicity, pass through the bacterial membrane, causing its disintegration. In this thesis the mechanisms of adaptation of rhodococci to toxic hydrophobic compounds were investigated. The rhodococcal strains increased the level of saturation of their cellular fatty acids in response to challenge with phenol, chlorophenol, benzene, chlorobenzene or toluene. The results indicated that increase in the saturation level of cellular fatty acids, particularly that in tuberculostearic acid, is part of the adaptation mechanism of strains GM-14 and GM-29 to the presence of toxic hydrophobic compounds.

Analysis of cool roof coatings for residential demand side management in tropical Australia

Cool roof coatings have a beneficial impact on reducing the heat load of a range of building types, resulting in reduced cooling energy loads. This study seeks to understand the extent to which cool roof coatings could be used as a residential demand side management (DSM) strategy for retrofitting existing housing in a constrained network area in tropical Australia where peak electrical demand is heavily influenced by residential cooling loads. In particular this study seeks to determine whether simulation software used for building regulation purposes can provide networks with the ‘impact certainty’ required by their DSM principles. The building simulation method is supported by a field experiment. Both numerical and experimental data confirm reductions in total consumption (kWh) and energy demand (kW). The nature of the regulated simulation software, combined with the diverse nature of residential buildings and their patterns of occupancy, however, mean that simulated results cannot be extrapolated to quantify benefits to a broader distribution network. The study suggests that building data gained from regulatory simulations could be a useful guide for potential impacts of widespread application of cool roof coatings in this region. The practical realization of these positive impacts, however, would require changes to the current business model for the evaluation of DSM strategies. The study provides seven key recommendations that encourage distribution networks to think beyond their infrastructure boundaries, recognising that the broader energy system also includes buildings, appliances and people.

Social networks and use of social supports of minority elders in East Harlem

Considerable empirical research substantiates the importance of social networks on health and well-being in later life. A study of ethnic minority elders living in two low income public housing buildings in East Harlem was undertaken to gain an understanding of the relationship between their health status and social networks. Findings demonstrate that elders with supportive housing had better psychological outcomes and used significantly more informal supports when in need. However, elders with serious health problems had poorer outcomes regardless of their level of social support. This study highlights the potential of supportive living environments to foster social integration and to optimise formal and informal networks.

A robust three phase power flow algorithm for radial distribution systems

An efficient load flow solution technique is required as a part of the distribution automation (DA) system for taking various control and operations decisions. This paper presents an efficient and robust three phase power flow algorithm for application to radial distribution networks. This method exploits the radial nature of the network and uses forward and backward propagation to calculate branch currents and node voltages. The proposed method has been tested to analyse several practical distribution networks of various voltage levels and also having high R/X ratio. The results for a practical distribution feeder are presented for illustration purposes. The application of the proposed method is also extended to find optimum location for reactive power compensation and network reconfiguration for planning and day-to-day operation of distribution networks.

Distributed Load Control in Multiphase Radial Networks

The current power grid is on the cusp of modernization due to the emergence of distributed generation and controllable loads, as well as renewable energy. On one hand, distributed and renewable generation is volatile and difficult to dispatch. On the other hand, controllable loads provide significant potential for compensating for the uncertainties. In a future grid where there are thousands or millions of controllable loads and a large portion of the generation comes from volatile sources like wind and solar, distributed control that shifts or reduces the power consumption of electric loads in a reliable and economic way would be highly valuable.

Load control needs to be conducted with network awareness. Otherwise, voltage violations and overloading of circuit devices are likely. To model these effects, network power flows and voltages have to be considered explicitly. However, the physical laws that determine power flows and voltages are nonlinear. Furthermore, while distributed generation and controllable loads are mostly located in distribution networks that are multiphase and radial, most of the power flow studies focus on single-phase networks.

This thesis focuses on distributed load control in multiphase radial distribution networks. In particular, we first study distributed load control without considering network constraints, and then consider network-aware distributed load control.

Distributed implementation of load control is the main challenge if network constraints can be ignored. In this case, we first ignore the uncertainties in renewable generation and load arrivals, and propose a distributed load control algorithm, Algorithm 1, that optimally schedules the deferrable loads to shape the net electricity demand. Deferrable loads refer to loads whose total energy consumption is fixed, but energy usage can be shifted over time in response to network conditions. Algorithm 1 is a distributed gradient decent algorithm, and empirically converges to optimal deferrable load schedules within 15 iterations.

We then extend Algorithm 1 to a real-time setup where deferrable loads arrive over time, and only imprecise predictions about future renewable generation and load are available at the time of decision making. The real-time algorithm Algorithm 2 is based on model-predictive control: Algorithm 2 uses updated predictions on renewable generation as the true values, and computes a pseudo load to simulate future deferrable load. The pseudo load consumes 0 power at the current time step, and its total energy consumption equals the expectation of future deferrable load total energy request.

Network constraints, e.g., transformer loading constraints and voltage regulation constraints, bring significant challenge to the load control problem since power flows and voltages are governed by nonlinear physical laws. Remarkably, distribution networks are usually multiphase and radial. Two approaches are explored to overcome this challenge: one based on convex relaxation and the other that seeks a locally optimal load schedule.

To explore the convex relaxation approach, a novel but equivalent power flow model, the branch flow model, is developed, and a semidefinite programming relaxation, called BFM-SDP, is obtained using the branch flow model. BFM-SDP is mathematically equivalent to a standard convex relaxation proposed in the literature, but numerically is much more stable. Empirical studies show that BFM-SDP is numerically exact for the IEEE 13-, 34-, 37-, 123-bus networks and a real-world 2065-bus network, while the standard convex relaxation is numerically exact for only two of these networks.

Theoretical guarantees on the exactness of convex relaxations are provided for two types of networks: single-phase radial alternative-current (AC) networks, and single-phase mesh direct-current (DC) networks. In particular, for single-phase radial AC networks, we prove that a second-order cone program (SOCP) relaxation is exact if voltage upper bounds are not binding; we also modify the optimal load control problem so that its SOCP relaxation is always exact. For single-phase mesh DC networks, we prove that an SOCP relaxation is exact if 1) voltage upper bounds are not binding, or 2) voltage upper bounds are uniform and power injection lower bounds are strictly negative; we also modify the optimal load control problem so that its SOCP relaxation is always exact.

To seek a locally optimal load schedule, a distributed gradient-decent algorithm, Algorithm 9, is proposed. The suboptimality gap of the algorithm is rigorously characterized and close to 0 for practical networks. Furthermore, unlike the convex relaxation approach, Algorithm 9 ensures a feasible solution. The gradients used in Algorithm 9 are estimated based on a linear approximation of the power flow, which is derived with the following assumptions: 1) line losses are negligible; and 2) voltages are reasonably balanced. Both assumptions are satisfied in practical distribution networks. Empirical results show that Algorithm 9 obtains 70+ times speed up over the convex relaxation approach, at the cost of a suboptimality within numerical precision.

An Embedded Stress Sensor for Concrete SHM Based on Amorphous Ferromagnetic Microwires

A new smart concrete aggregate design as a candidate for applications in structural health monitoring (SHM) of critical elements in civil infrastructure is proposed. The cement-based stress/strain sensor was developed by utilizing the stress/strain sensing properties of a magnetic microwire embedded in cement-based composite (MMCC). This is a contact-less type sensor that measures variations of magnetic properties resulting from stress variations. Sensors made of these materials can be designed to satisfy the specific demand for an economic way to monitor concrete infrastructure health. For this purpose, we embedded a thin magnetic microwire in the core of a cement-based cylinder, which was inserted into the concrete specimen under study as an extra aggregate. The experimental results show that the embedded MMCC sensor is capable of measuring internal compressive stress around the range of 1-30 MPa. Two stress sensing properties of the embedded sensor under uniaxial compression were studied: the peak amplitude and peak position of magnetic switching field. The sensitivity values for the amplitude and position within the measured range were 5 mV/MPa and 2.5 mu s/MPa, respectively.

A bacia hidrográfica Lagos-São João pós década de 1960: um estudo das transformações espaciais da região e suas influências sobre a qualidade ambiental

A Bacia Hidrográfica Lagos São João, localizada no sudoeste do Estado do Rio de Janeiro, abrange 13 municípios que abrigam cerca de 520 mil habitantes. Na temporada de férias esse número sobe para mais de 1 milhão de pessoas. A pastagem constitui o principal tipo de uso do solo, em seguida vem as áreas urbanas e as salinas. A partir da década de 1960 essa região passou a receber maior contingente populacional, tanto de veranistas quanto de moradores fixos, beneficiados pela implantação de novas vias de acesso, como a Ponte Rio-Niteroi e pela construção da represa de Juturnaíba, que ampliou o abastecimento de água dos municípios. Surge neste contexto a especulação imobiliária, que acelera a ocupação das terras próximas a Lagoa de Araruama. Rapidamente essas terras foram loteadas e o setor da construção civil foi ganhando força. Entretanto, a região não contou com adequado planejamento, e os investimentos em saneamento básico e outras infraestruturas urbanas não acompanharam o ritmo da construção civil, que cada vez mais investia em casas, prédios e condomínios, que ampliaram consideravelmente a área urbana e a ocupação da zona costeira. Sendo assim, ficou visível o aumento da malha urbana e a ocupação de áreas impróprias, como as margens dos corpos hídricos, os manguezais, dunas e restingas, além da redução da cobertura vegetal. Dessa forma, foi substancial a perda de qualidade ambiental na região, sobretudo, com relação a água da lagoa e dos rios, que passaram a receber maior volume de efluentes sem tratamento. O potencial turístico da região tem sido explorado e provocado altos investimentos dos agentes de especulação imobiliária, entretanto além de promover a ocupação em áreas irregulares, leva a privatização de espaços públicos e incentiva o fenômeno da segunda residência. A chegada de novos turistas iniciou o processo de desenvolvimento do turismo e, consequentemente, a redução da produção salineira. Com isso, o espaço local ganhou novos significados, inseridos pela lógica da urbanização turística. Foi essa nova lógica transformadora que, gradativamente, valorizou a paisagem local, ampliando e encarecendo o seu consumo. Além de ampliar as transformações espaciais, tendo em vista a expansão da malha urbana verificada nas imagens de satélites, atuais, que foram comparadas com fotografias aéreas de décadas anteriores. Todas as transformações ocorridas na região apresentam alguma relação com o desencadeamento de novos problemas ambientais identificados nos seus ecossistemas, sobretudo a Lagoa de Araruama, ou a ampliação de problemas anteriormente existentes.

System studies of the superconducting fault current limiter in electrical distribution grids

A superconducting fault current limiter (SFCL) in series with a downstream circuit breaker could provide a viable solution to controlling fault current levels in electrical distribution networks. In order to integrate the SFCL into power grids, we need a way to conveniently predict the performance of the SFCL in a given scenario. In this paper, short circuit analysis based on the electromagnetic transient program was used to investigate the operational behavior of the SFCL installed in an electrical distribution grid. System studies show that the SFCL can not only limit the fault current to an acceptable value, but also mitigate the voltage sag. The transient recovery voltage (TRV) could be remarkably damped and improved by the presence of the SFCL after the circuit breaker is opened to clear the fault. © 2007 British Crown Copyright.

GENESI: Wireless sensor networks for structural monitoring

The GENESI project has the ambitious goal of bringing WSN technology to the level where it can provide the core of the next generation of systems for structural health monitoring that are long lasting, pervasive and totally distributed and autonomous. This goal requires embracing engineering and scientific challenges never successfully tackled before. Sensor nodes will be redesigned to overcome their current limitations, especially concerning energy storage and provisioning (we need devices with virtually infinite lifetime) and resilience to faults and interferences (for reliability and robustness). New software and protocols will be defined to fully take advantage of the new hardware, providing new paradigms for cross-layer interaction at all layers of the protocol stack and satisfying the requirements of a new concept of Quality of Service (QoS) that is application-driven, truly reflecting the end user perspective and expectations. The GENESI project will develop long lasting sensor nodes by combining cutting edge technologies for energy generation from the environment (energy harvesting) and green energy supply (small form factor fuel cells); GENESI will define models for energy harvesting, energy conservation in super-capacitors and supplemental energy availability through fuel cells, in addition to the design of new algorithms and protocols for dynamic allocation of sensing and communication tasks to the sensors. The project team will design communication protocols for large scale heterogeneous wireless sensor/actuator networks with energy-harvesting capabilities and define distributed mechanisms for context assessment and situation awareness. This paper presents an analysis of the GENESI system requirements in order to achieve the ambitious goals of the project. Extending from the requirements presented, the emergent system specification is discussed with respect to the selection and integration of relevant system components.The resulting integrated system will be evaluated and characterised to ensure that it is capable of satisfying the functional requirements of the project

Finance for water and sanitation as a public service

Drawing on empirical evidence gathered through the PSIRU database, this contribution aims at addressing the potential of public finance to enhance the provision of water supply and sanitation as a public service. It highlights the problems associated with (and the disappointing results obtained from) resort to Private Sector Participation and private finance, both historically and in the last 15-20 years, in developed and developing countries. It also addresses the advantages of using public finance as a more cost-effective and equitable instrument to achieve developmental objectives such as the expansion of service coverage and development of water and sanitation infrastructure. The potential of public operations in maximising developmental impact from the social, economic and environmental points of view is then explored referring to specific examples from a variety of countries and regions. These include the in-house restructuring of public operations to enhance transparency, accountability and effectiveness, as well as the use of Public-Public Partnerships (PUPs) to build capacity. Attention is devoted to the specific financial requirements of expanding sewerage services at global level to achieve MDGs or broader developmental goals. These requirements are revisited in light of a regional breakdown of coverage gaps, available resources and development aid flows. These findings challenge the established view among international and bilateral agencies that expanding sewerage services in developing countries is excessively costly and should be abandoned as a priority because unaffordable. This contribution draws on a number of PSIRU Reports, and particularly the following. - http://www.psiru.org/reports/2008-03-W-sewers.pdf - http://boell-latinoamerica.org/download_es/agua08_privatizacion_LA_2007.pdf - http://boell-latinoamerica.org/download_es/agua08_agua_un_servicio_publico.pdf - http://www.psiru.org/reports/2006-03-W-investment.pdf All PSIRU Reports are accessible at http://www.psiru.org/publicationsindex.asp.

Probabilistic Models to Describe the Dynamics of Migrating Microbial Communities

In all but the most sterile environments bacteria will reside in fluid being transported through conduits and some of these will attach and grow as biofilms on the conduit walls. The concentration and diversity of bacteria in the fluid at the point of delivery will be a mix of those when it entered the conduit and those that have become entrained into the flow due to seeding from biofilms. Examples include fluids through conduits such as drinking water pipe networks, endotracheal tubes, catheters and ventilation systems. Here we present two probabilistic models to describe changes in the composition of bulk fluid microbial communities as they are transported through a conduit whilst exposed to biofilm communities. The first (discrete) model simulates absolute numbers of individual cells, whereas the other (continuous) model simulates the relative abundance of taxa in the bulk fluid. The discrete model is founded on a birth-death process whereby the community changes one individual at a time and the numbers of cells in the system can vary. The continuous model is a stochastic differential equation derived from the discrete model and can also accommodate changes in the carrying capacity of the bulk fluid. These models provide a novel Lagrangian framework to investigate and predict the dynamics of migrating microbial communities. In this paper we compare the two models, discuss their merits, possible applications and present simulation results in the context of drinking water distribution systems. Our results provide novel insight into the effects of stochastic dynamics on the composition of non-stationary microbial communities that are exposed to biofilms and provides a new avenue for modelling microbial dynamics in systems where fluids are being transported.

Habitat for Humanity: Calibrating Best Practice Against the MDGs

Poverty alleviation lies at the heart of contemporary international initiatives on development. The key to development is the creation of an environment in which people can develop their potential, leading productive, creative lives in accordance with their needs, interests and faith. This entails, on the one hand, protecting the vulnerable from things that threaten their survival, such as inadequate nutrition, disease, conflict, natural disasters and the impact of climate change, thereby enhancing the poor’s capabilities to develop resilience in difficult conditions. On the other hand, it also requires a means of empowering the poor to act on their own behalf, as individuals and communities, to secure access to resources and the basic necessities of life such as water, food, shelter, sanitation, health and education. ‘Development’, from this perspective, seeks to address the sources of human insecurity, working towards ‘freedom from want, freedom from fear’ in ways that empower the vulnerable as agents of development (not passive recipients of benefaction).

Recognition of the magnitude of the problems confronted by the poor and failure of past interventions to tackle basic issues of human security led the United Nations (UN) in September 2000 to set out a range of ambitious, but clearly defined, development goals to be achieved by 2015. These are known as the Millennium Development Goals (MDGs). The intention of the UN was to mobilise multilateral international organisations, non-governmental organisations and the wider international community to focus attention on fulfilling earlier promises to combat global poverty. This international framework for development prioritises: the eradication of extreme poverty and hunger; achieving universal primary education; promoting gender equality and empowering women; reducing child mortality; improving maternal health; combating HIV/AIDS, malaria and other diseases; ensuring environmental sustainability; and developing a global partnership for development. These goals have been mapped onto specific targets (18 in total) against which outcomes of associated development initiatives can be measured and the international community held to account. If the world achieves the MDGs, more than 500 million people will be lifted out of poverty. However, the challenges the goals represent are formidable. Interim reports on the initiative indicate a need to scale-up efforts and accelerate progress.
Only MDG 7, Target 11 explicitly identifies shelter as a priority, identifying the need to secure ‘by 2020 a significant improvement in the lives of at least 100 million slum dwellers’. This raises a question over how Habitat for Humanity’s commitment to tackling poverty housing fits within this broader international framework designed to allievate global poverty. From an analysis of HFH case studies, this report argues that the processes by which Habitat for Humanity tackles poverty housing directly engages with the agenda set by the MDGs. This should not be regarded as a beneficial by-product of the delivery of decent, affordable shelter, but rather understood in terms of the ways in which Habitat for Humanity has translated its mission and values into a participatory model that empowers individuals and communities to address the interdependencies between inadequate shelter and other sources of human insecurity. What housing can deliver is as important as what housing itself is.

Examples of the ways in which Habitat for Humanity projects engage with the MDG framework include the incorporation of sustainable livelihoods strategies, up-grading of basic infrastructure and promotion of models of good governance. This includes housing projects that have also offered training to young people in skills used in the construction industry, microfinanced loans for women to start up their own home-based businesses, and the provision of food gardens. These play an important role in lifting families out of poverty and ensuring the sustainability of HFH projects. Studies of the impact of improved shelter and security of livelihood upon family life and the welfare of children evidence higher rates of participation in education, more time dedicated to study and greater individual achievement. Habitat for Humanity projects also typically incorporate measures to up-grade the provision of basic sanitation facilities and supplies of safe, potable drinking water. These measures not only directly help reduce mortality rates (e.g. diarrheal diseases account for around 2 million deaths annually in children under 5), but also, when delivered through HFH project-related ‘community funds’, empower the poor to mobilise community resources, develop local leadership capacities and even secure de facto security of tenure from government authorities.

In the process of translating its mission and values into practical measures, HFH has developed a range of innovative practices that deliver much more than housing alone. The organisation’s participatory model enables both direct beneficiaries and the wider community to tackle the insecurities they face, unlocking latent skills and enterprise, building sustainable livelihood capabilities. HFH plays an important role as a catalyst for change, delivering through the vehicle of housing the means to address the primary causes of poverty itself. Its contribution to wider development priorities deserves better recognition. In calibrating the success of HFH projects in terms of units completed or renovated alone, the significance of the process by which HFH realises these outcomes is often not sufficiently acknowledged, both within the organisation and externally. As the case studies developed in the report illustrate, the methodologies Habitat for Humanity employs to address the issue of poverty housing within the developing world, place the organisation at the centre of a global strategic agenda to address the root causes of poverty through community empowerment and the transformation of structures of governance.

Given this, the global network of HFH affiliates constitutes a unique organisational framework to faciliate sharing resources, ideas and practical experience across a diverse range of cultural, political and institutional environments. This said, it is apparent that work needs to be done to better to faciliate the pooling of experience and lessons learnt from across its affiliates. Much is to be gained from learning from less successful projects, sharing innovative practices, identifying strategic partnerships with donors, other NGOs and CBOs, and engaging with the international development community on how housing fits within a broader agenda to alleviate poverty and promote good governance.

Enhanced AIMD based decentralized residential charging of EVs

Moving from combustion engine to electric vehicle (EV)-based transport is recognized as having a major role to play in reducing pollution, combating climate change and improving energy security. However, the introduction of EVs poses major challenges for power system operation. With increasing penetration of EVs, uncontrolled coincident charging may overload the grid and substantially increase peak power requirements. Developing smart grid technologies and appropriate charging strategies to support the role out of EVs is therefore a high priority. In this paper, we investigate the effectiveness of distributed additive increase and multiplicative decrease (AIMD) charging algorithms, as proposed by Stu¨dli et al. in 2012, at mitigating the impact of domestic charging of EVs on low-voltage distribution networks. In particular, a number of enhancements to the basic AIMD implementation are introduced to enable local power system infrastructure and voltage level constraints to be taken into account and to reduce peak power requirements. The enhanced AIMD EV charging strategies are evaluated using power system simulations for a typical low-voltage residential feeder network in Ireland. Results show that by using the proposed AIMD-based smart charging algorithms, 50% EV penetration can be accommodated, compared with only 10% with uncontrolled charging, without exceeding network infrastructure constraints.