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

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

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

Optimal battery storage operation for PV systems with tariff incentives

Many efforts are recently being dedicated to developing models that seek to provide insights into the techno-economic benefits of battery storage coupled to photovoltaic (PV) generation system. However, not all models consider the operation of the PV – battery storage system with a feed-in tariff (FiT) incentive, different electricity rates and battery storage unit cost. An electricity customer whose electricity demand is supplied by a grid connected PV generation system benefiting from a FiT incentive is simulated in this paper. The system is simulated with the PV modelled as an existing system and the PV modelled as a new system. For a better understanding of the existing PV system with battery storage operation, an optimisation problem was formulated which resulted in a mixed integer linear programming (MILP) problem. The optimisation model was developed to solve the MILP problem and to analyse the benefits considering different electricity tariffs and battery storage in maximising FiT revenue streams for the existing PV generating system. Real data from a typical residential solar PV owner is used to study the benefit of the battery storage system using half-hourly dataset for a complete year. A sensitivity analysis of the MILP optimisation model was simulated to evaluate the impact of battery storage capacity (kWh) on the objective function. In the second case study, the electricity demand data, solar irradiance, tariff and battery unit cost were used to analyse the effect of battery storage unit cost on the adoption of electricity storage in maximising FiT revenue. In this case, the PV is simulated as a new system using Distributed Energy Resources Customer Adoption Model (DER-CAM) software tool while modifying the optimisation formulation to include the PV onsite generation and export tariff incentive. The results provide insights on the benefit of battery storage for existing and new PV system benefiting from FiT incentives and under time-varying electricity tariffs

Voltage analysis on MV/LV distribution networks with the integration of DC fast chargers

The development of ultra-low carbon emission electric vehicles (EVs) has been grown rapidly over the last years in response to the large share of greenhouse gas emissions contributed by the transportation sector. One of the main issues among EV drivers is range anxiety, which mainly results from the long charging battery durations. DC fast charging, the latest charging technology, aims to shorten charging duration; however, the success of e-mobility will be also related to the capacity of the distribution network to integrate the new EVs and their chargers. Specifically, the integration of EVs and DC fast chargers will increase the peak demand and may pose significant challenges for MV and LV distribution networks if adequate control measures are not implemented. This paper introduces a topology for the modelling and connection of a DC fast charger on a real MV/LV distribution network and ensures that the network operates within acceptable limits and that consumers connected to it are minimally affected. Simulation results show that DC fast chargers stress the LV distribution network by causing grid congestions; however, local voltage control measures and a vehicle-to-grid technology can improve some of the grid-side challenges

A cloud-based energy management system for building managers

A Local Energy Management System (LEMS) is described to control Electric Vehicle charging and Energy Storage Units within built environments. To this end, the LEMS predicts the most probable half hours for a triad peak, and forecasts the electricity demand of a building facility at those times. Three operational algorithms were designed, enabling the LEMS to (i) flatten the demand profile of the building facility and reduce its peak, (ii) reduce the demand of the building facility during triad peaks in order to reduce the Transmission Network Use of System (TNUoS) charges, and (iii) enable the participation of the building manager in the grid balancing services market through demand side response. The LEMS was deployed on over a cloud-based system and demonstrated on a real building facility in Manchester, UK

Black Start Capability from Large Industrial Consumers

The way of control and operation of an electrical power system has been changing rapidly with the integration of renewable energy sources (RES). One of the emerging issues that require addressing is the capability of RES to participate in the restoration process upon a total or partial system failure. However, with the continuous shutdown of large-centralised generators, which traditionally provided the black start support together with the variability of RES, the restoration process becomes much more complex. Primarily, the RES should have enough capacity to energise the load at the time of the restoration. Nonetheless, due to significant advantages, there is an increasing trend to use RES to meet the local energy demand by large industrial customers. The flexibility of shifting loads together with the surplus of RE generation could support the system operator during the system energisation process after a blackout. This paper mainly focuses on identifying the capabilities and factors that should be accounted for to participate in the system restoration process by large industrial consumers. The case study conducted on a large-scale steel factory in the UK reveals the possibility of supporting the restoration process under the bottom-up approac