An integrated approach to planning charging infrastructure for battery electric vehicles

PhD ThesisBattery electric vehicles (BEVs) could break our dependence on fossil fuels by facilitating the transition to low carbon and efficient transport and power systems. Yet, BEV market share is under 1% and there are several barriers to adoption including the lack of charging infrastructure. This work revealed insights that could inform planning an appropriate charging infrastructure to support the transition towards BEVs. The insights were based on analysis of a comprehensive dataset collected from three early, real world demonstrators in the UK on BEVs and smart grids. The BEV participants had access and used home, work and public charging infrastructure including fast chargers (50 kW). Probabilistic methods were used to combine and analyse the datasets to ensure robustness of findings. The findings confirm that it is essential to consider a new refuelling paradigm for BEV charging infrastructure and not replicate the liquid-fuel infrastructure where all demand is met at public fuelling stations in a very short period of time. BEVs could be charged where they are routinely parked for long periods of time (i.e. home, work) and meet most of the charging needs of drivers. Installing slow charging infrastructure at home and work would be less expensive and less complicated than rolling-out a ubiquitous fast charging infrastructure to meet all charging needs. In addition, ensuring that cars are connected most of the time to the electricity network allows proper management of BEV charging demand. This could support reliable and efficient operation of the power system to minimise network upgrade costs. Finally, when slow charging infrastructure is neither available nor practical to meet charging needs, fast chargers can be used to fill in this gap. Analysing data of BEV drivers with access to private charging locations, the findings show that fast chargers become more important than slow chargers for daily journeys above 240km and could help overcome perceived and actual range barriers. An appropriate infrastructure takes an integrated approach encompassing BEV drivers’ requirements and the characteristics of the distribution networks where BEV charging infrastructure is connected. A non-integrated approach to delivering a charging infrastructure could impede the transition towards BEVs. The findings of this work could support on-going policy development in the UK and are crucial to planning national charging infrastructure to support the adoption of BEVs in a cost-optimal manner

An integrated approach to planning charging infrastructure for battery electric vehicles

PhD ThesisBattery electric vehicles (BEVs) could break our dependence on fossil fuels by facilitating the transition to low carbon and efficient transport and power systems. Yet, BEV market share is under 1% and there are several barriers to adoption including the lack of charging infrastructure. This work revealed insights that could inform planning an appropriate charging infrastructure to support the transition towards BEVs. The insights were based on analysis of a comprehensive dataset collected from three early, real world demonstrators in the UK on BEVs and smart grids. The BEV participants had access and used home, work and public charging infrastructure including fast chargers (50 kW). Probabilistic methods were used to combine and analyse the datasets to ensure robustness of findings. The findings confirm that it is essential to consider a new refuelling paradigm for BEV charging infrastructure and not replicate the liquid-fuel infrastructure where all demand is met at public fuelling stations in a very short period of time. BEVs could be charged where they are routinely parked for long periods of time (i.e. home, work) and meet most of the charging needs of drivers. Installing slow charging infrastructure at home and work would be less expensive and less complicated than rolling-out a ubiquitous fast charging infrastructure to meet all charging needs. In addition, ensuring that cars are connected most of the time to the electricity network allows proper management of BEV charging demand. This could support reliable and efficient operation of the power system to minimise network upgrade costs. Finally, when slow charging infrastructure is neither available nor practical to meet charging needs, fast chargers can be used to fill in this gap. Analysing data of BEV drivers with access to private charging locations, the findings show that fast chargers become more important than slow chargers for daily journeys above 240km and could help overcome perceived and actual range barriers. An appropriate infrastructure takes an integrated approach encompassing BEV drivers’ requirements and the characteristics of the distribution networks where BEV charging infrastructure is connected. A non-integrated approach to delivering a charging infrastructure could impede the transition towards BEVs. The findings of this work could support on-going policy development in the UK and are crucial to planning national charging infrastructure to support the adoption of BEVs in a cost-optimal manner

Investigation of energy storage system and demand side response for distribution networks

PhD ThesisThe UK government has a target of achieving an 80% reduction in CO2 emissions with respect to the values from 1990 by 2050. Therefore, renewables based distributed generations (DGs) coupled with substantial electrification of the transport and heat sectors though low carbon technologies (LCTs), will be essential to achieve this target. The anticipated proliferation of these technologies will necessitate major opportunities and challenges to the operation and planning of future distribution networks. Smartgrid technologies and techniques, such as energy storage systems (ESSs), demand side response (DSR) and real time thermal ratings (RTTRs), provide flexible, economic and expandable solutions to these challenges without resorting to network reinforcement. This research investigates the use of ESS and DSR in future distribution networks to facilitate LCTs with a focus on the management and resolution of thermal constraints and steady state voltage limit violation problems. Firstly, two control schemes based on sensitivity factors and cost sensitivity factors are proposed. Next, the impacts of a range of sources of uncertainties, arising from existing and future elements of the electrical energy system, are studied. The impacts of electric vehicle charging are investigated with Monte Carlo simulation (MCS). Furthermore, to deal with uncertainties efficiently, a scheduling scheme based on robust optimization (RO) is developed. Two approaches have been introduced to estimate the trade-off between the cost and the probability of constraint violations. Finally, the performance of this scheme is evaluated. The results of this research show the importance of dealing with uncertainties appropriately. Simulation results demonstrate the capability and effectiveness of the proposed RO based scheduling scheme to facilitate DG and LCTs, in the presence of a range of source of uncertainties. The findings from this research provide valuable solution and guidance to facilitate DG and LCTs using ESS, DSR and RTTR in future distribution networks

Optimized charging control method for plug-in electric vehicles in LV distribution networks

207 p.Title: Optimized charging control method for plug-in electric vehicles in low voltage distributionnetworksKeywords: plug-in electric vehicles, smart charging, V2G, distribution networks, smart grids, multiobjectiveoptimization, demand side management, voltage unbalances, DIgSILENT PowerFactory[EN] This thesis proposes a new methodology to integrate plug-in electric vehicles in low voltagedistribution networks. Charging a significant number of plug-in electric vehicles will lead to severalimpacts in low voltage distribution networks such as increase of energy losses, overloads of linesand distribution transformers, voltage drops and unbalances, etc. These impacts will dependlargely on the charging control method used. Furthermore, there can be a conflict of interestsbetween electric vehicle users and electric utilities. In this context, this thesis proposes a newmethodology to efficiently integrate plug-in electric vehicles and, at the same time, it reducescharging costs for electric vehicle users. This new methodology is based on a multi-objectiveoptimization which objective functions are minimizing load variance and charging costs. Inaddition, an improvement has been proposed to coordinate the charging of multiple PEVs in orderto reduce voltage drops and unbalances. Furthermore, the proposed solution has beenimplemented in a decentralized architecture which provides several advantages. Aspects such asusers¿ privacy, reliability and scalability are improved compared to centralized controlarchitectures. A real distribution network located in Borup (Denmark) has been used as model totest the effectiveness of the proposed methodology. Simulation results show that the newmethodology improves load factor, limits energy losses, reduces charging costs and limits voltagedrops and unbalances. Considering all these aspects, the proposed methodology improves theintegration of plug-in electric vehicles in low voltage distribution networks.[SP] La presente tesis doctoral propone una nueva metodología para integrar los vehículoseléctricos enchufables en las redes de baja tensión. La carga de un número significativo devehículos eléctricos producirá varios impactos en las redes de baja tensión como son el aumentode pérdidas, la sobrecarga de líneas y transformadores, caídas de tensión, desequilibrios detensión, etc. Estos impactos dependerán en gran medida del método de control de carga utilizado.Además, puede existir un conflicto de intereses entre los usuarios de vehículos eléctricos y lascompañías distribuidores de electricidad. En este contexto, la presente tesis propone una nuevametodología para integrar eficientemente los vehículos eléctricos enchufables y, al mismo tiempo,reducir los costes de carga. Esta metodología está basada en una optimización multiobjetivo cuyasfunciones objetivo son la minimización de la varianza de la carga y de los costes de carga.Asimismo, se introduce una mejora para coordinar la carga de los vehículos eléctricos enchufablescon el objeto de reducir los desequilibrios y las caídas de tensión. Igualmente, la soluciónpropuesta ha sido implementada en una arquitectura descentralizada que proporciona una seriede mejoras adicionales. Aspectos como la privacidad de los usuarios, la fiabilidad y la modularidadson mejorados respecto a soluciones con arquitecturas centralizadas. Un modelo de una red dedistribución real, localizada en el municipio de Borup (Dinamarca), ha sido utilizado paracomprobar la eficacia de la metodología propuesta. Los resultados obtenidos en las simulacionesdemuestran que la nueva metodología mejora el factor de carga, limita las pérdidas de energía,reduce los costes de carga y limita los desequilibrios y caídas de tensión. Teniendo en cuenta todosestos aspectos, la metodología propuesta mejora la integración de los vehículos eléctricosenchufables en las redes de distribución de baja tensión

Optimized charging control method for plug-in electric vehicles in LV distribution networks

207 p.Title: Optimized charging control method for plug-in electric vehicles in low voltage distributionnetworksKeywords: plug-in electric vehicles, smart charging, V2G, distribution networks, smart grids, multiobjectiveoptimization, demand side management, voltage unbalances, DIgSILENT PowerFactory[EN] This thesis proposes a new methodology to integrate plug-in electric vehicles in low voltagedistribution networks. Charging a significant number of plug-in electric vehicles will lead to severalimpacts in low voltage distribution networks such as increase of energy losses, overloads of linesand distribution transformers, voltage drops and unbalances, etc. These impacts will dependlargely on the charging control method used. Furthermore, there can be a conflict of interestsbetween electric vehicle users and electric utilities. In this context, this thesis proposes a newmethodology to efficiently integrate plug-in electric vehicles and, at the same time, it reducescharging costs for electric vehicle users. This new methodology is based on a multi-objectiveoptimization which objective functions are minimizing load variance and charging costs. Inaddition, an improvement has been proposed to coordinate the charging of multiple PEVs in orderto reduce voltage drops and unbalances. Furthermore, the proposed solution has beenimplemented in a decentralized architecture which provides several advantages. Aspects such asusers¿ privacy, reliability and scalability are improved compared to centralized controlarchitectures. A real distribution network located in Borup (Denmark) has been used as model totest the effectiveness of the proposed methodology. Simulation results show that the newmethodology improves load factor, limits energy losses, reduces charging costs and limits voltagedrops and unbalances. Considering all these aspects, the proposed methodology improves theintegration of plug-in electric vehicles in low voltage distribution networks.[SP] La presente tesis doctoral propone una nueva metodología para integrar los vehículoseléctricos enchufables en las redes de baja tensión. La carga de un número significativo devehículos eléctricos producirá varios impactos en las redes de baja tensión como son el aumentode pérdidas, la sobrecarga de líneas y transformadores, caídas de tensión, desequilibrios detensión, etc. Estos impactos dependerán en gran medida del método de control de carga utilizado.Además, puede existir un conflicto de intereses entre los usuarios de vehículos eléctricos y lascompañías distribuidores de electricidad. En este contexto, la presente tesis propone una nuevametodología para integrar eficientemente los vehículos eléctricos enchufables y, al mismo tiempo,reducir los costes de carga. Esta metodología está basada en una optimización multiobjetivo cuyasfunciones objetivo son la minimización de la varianza de la carga y de los costes de carga.Asimismo, se introduce una mejora para coordinar la carga de los vehículos eléctricos enchufablescon el objeto de reducir los desequilibrios y las caídas de tensión. Igualmente, la soluciónpropuesta ha sido implementada en una arquitectura descentralizada que proporciona una seriede mejoras adicionales. Aspectos como la privacidad de los usuarios, la fiabilidad y la modularidadson mejorados respecto a soluciones con arquitecturas centralizadas. Un modelo de una red dedistribución real, localizada en el municipio de Borup (Dinamarca), ha sido utilizado paracomprobar la eficacia de la metodología propuesta. Los resultados obtenidos en las simulacionesdemuestran que la nueva metodología mejora el factor de carga, limita las pérdidas de energía,reduce los costes de carga y limita los desequilibrios y caídas de tensión. Teniendo en cuenta todosestos aspectos, la metodología propuesta mejora la integración de los vehículos eléctricosenchufables en las redes de distribución de baja tensión