Reallocating charging loads of electric vehicles in distribution networks

In this paper, the charging loads of electric vehicles were controlled to avoid their impact on distribution networks. A centralized control algorithm was developed using unbalanced optimal power flow calculations with a time resolution of one minute. The charging loads were optimally reallocated using a central controller based on non-linear programming. Electric vehicles were recharged using the proposed control algorithm considering the network constraints of voltage magnitudes, voltage unbalances, and limitations of the network components (transformers and cables). Simulation results showed that network components at the medium voltage level can tolerate high uptakes of uncontrolled recharged electric vehicles. However, at the low voltage level, network components exceeded their limits with these high uptakes of uncontrolled charging loads. Using the proposed centralized control algorithm, these high uptakes of electric vehicles were accommodated in the network under study without the need of upgrading the network components

The impacts of electric vehicles and heat pumps load profiles on low voltage distribution networks in Great Britain by 2050

The impacts of uptake and electricity load profiles of Electric Vehicles (EVs) and Heat Pumps (HPs) on the low voltage (LV) distribution networks were analyzed. The United Kingdom (UK) has a legally mandated policy concerning reduction of greenhouse gasses (GHGs) emissions. Therefore, the integration of low carbon technologies (LCTs) especially EVs and HPs at the LV networks is expected to increase in the drive to reducing the GHGs emissions. Future uptake scenarios, adapted from the National Grid studies, of EVs and HPs were developed for a real and typical urban LV distribution network in Great Britain (GB). Gridlab-D, an agent-based power system simulation software, was used to model the LV distribution network. The model was run for four different scenarios considering seasonal load profiles and projected EVs and HPs uptakes for each of the year 2020, 2030, 2040 and 2050 respectively. The results were analyzed in terms of transformer loading, voltage profiles of the feeders, and the ampacity loading of the cables for the different scenarios of the years

Simulation of electric vehicle driver behaviour in road transport and electric power networks

The integration of electric vehicles (EVs) will affect both electricity and transport systems and research is needed on finding possible ways to make a smooth transition to the electrification of the road transport. To fully understand the EV integration consequences, the behaviour of the EV drivers and its impact on these two systems should be studied. This paper describes an integrated simulation-based approach, modelling the EV and its interactions in both road transport and electric power systems. The main components of both systems have been considered, and the EV driver behaviour was modelled using a multi-agent simulation platform. Considering a fleet of 1000 EV agents, two behavioural profiles were studied (Unaware/Aware) to model EV driver behaviour. The two behavioural profiles represent the EV driver in different stages of EV adoption starting with Unaware EV drivers when the public acceptance of EVs is limited, and developing to Aware EV drivers as the electrification of road transport is promoted in an overall context. The EV agents were modelled to follow a realistic activity-based trip pattern, and the impact of EV driver behaviour was simulated on a road transport and electricity grid. It was found that the EV agents’ behaviour has direct and indirect impact on both the road transport network and the electricity grid, affecting the traffic of the roads, the stress of the distribution network and the utilization of the charging infrastructure

Airport electrified ground support equipment for providing ancillary services to the grid

The ground handling operations are used in airports for handling activities and processing passengers with the help of specially designed vehicles known as ground support equipment. The ground support equipment (GSE) is being parked after serving a flight until the next flight. The GSE idle duration between flights is depending on the flight schedule and can be turned into a profit source. This paper is presenting a methodology for electrified ground support equipment (EGSE) for providing frequency regulation ancillary services to the grid through an aggregator. The passengers flight schedule is considered to increase the vehicles’ availability to participate in the frequency regulation ancillary services market. The optimization model is formulated to maximize the airport profitability by using aggregation of EGSE in frequency regulation market. The results show that the EGSE provides a significant profit by participating in frequency regulation ancillary service with the use of V2G mode

A multi-agent based scheduling algorithm for adaptive electric vehicles charging

This paper presents a decentralized scheduling algorithm for electric vehicles charging. The charging control model follows the architecture of a Multi-Agent System (MAS). The MAS consists of an Electric Vehicle (EV)/Distributed Generation (DG) aggregator agent and “Responsive” or “Unresponsive” EV agents. The EV/DG aggregator agent is responsible to maximize the aggregator’s profit by designing the appropriate virtual pricing policy according to accurate power demand and generation forecasts. “Responsive” EV agents are the ones that respond rationally to the virtual pricing signals, whereas “Unresponsive” EV agents define their charging schedule regardless the virtual cost. The performance of the control model is experimentally demonstrated through different case studies at the micro-grid laboratory of the National Technical University of Athens (NTUA) using Real Time Digital Simulator. The results highlighted the adaptive behaviour of “Responsive” EV agents and proved their ability to charge preferentially from renewable energy sources

Virtual power plants with electric vehicles

The benefits of integrating aggregated Electric Vehicles (EV) within the Virtual Power Plant (VPP) concept, are addressed. Two types of EV aggregators are identified: i) Electric Vehicle Residential Aggregator (EVRA), which is responsible for the management of dispersed and clustered EVs in a residential area and ii) Electric Vehicle Commercial Aggregator (EVCA), which is responsible for the management of EVs clustered in a single car park. A case study of a workplace EVCA is presented, providing an insight on its operation and service capabilities

Impact of optimised distributed energy resources on local grid constraints

Optimisation models have been extensively used for finding optimal configuration and operation of distributed energy technologies. The main objective in most of these models is to find the optimal configuration of distributed energy technologies that will meet a certain energy demand with the least cost and emissions. Local grid constraints are not considered in the optimisation of distributed energy resources in most of these models. This implies that some optimal solutions from these models may not be possible to integrate due to a violation of steady state voltage and thermal limits which are important to Distribution Network Operators (DNO). In some cases, where a joint optimisation approach is utilised and local grid constraints are considered, it becomes computationally complex due to the nonlinear nature of Alternating Current (AC) power flow equations for electricity networks. In this paper, the impact of optimised Distributed Energy Resources (DER) on a modelled microgrid was evaluated with an AC time series power flow using a soft-linking method. The soft-linking method avoids the computationally complex nature of joint optimisation methods. Different scenarios of the optimised DER were simulated and evaluated based on voltage excursions and energy losses. The results provide insights into the impact of local grid constraints on the adoption of different scenarios of optimised DER

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Optimal annual operational cost of a hybrid renewable-based microgrid to increase the power resilience of a critical facility

With the rapid increment of power outages related to extreme natural disasters such as wildfires and severe storms, microgrids have the potential to enhance resilience locally. Traditionally, grid-connected microgrids are investigated from an economic perspective only, without focusing on resilience solutions benefits during grid interruptions. Hence, the presented work proposes a technical and economic evaluation of an airport grid-connected microgrid consisting of solar photovoltaic (PV), energy storage system, and diesel generator to enhance airport power resilience under different power interruption scenarios. A modified mixed-integer linear programming scheme was introduced to minimize the total annual operating cost of the proposed resilient system. The optimal resilient microgrid components sizing and dispatching were investigated with and without a monetary assigned value for resilience as a service. Moreover, the microgrid survivability during solar performance change was investigated. The possible load increment from electric ground support equipment deployment was considered. The results show that the proposed microgrid can achieve an annual operational cost reduction while ensuring a continuous power supply for all considered outage scenarios. The operational cost saving varies between 20% and 22%. The duration of the outage and critical load level have a higher impact on microgrid sizing and dispatching