474 research outputs found
Numerical Analysis of National Travel Data to Assess the Impact of UK Fleet Electrification
Accurately predicting the future power demand of electric vehicles is
important for developing policy and industrial strategy. Here we propose a
method to create a representative set of electricity demand profiles using
survey data from conventional vehicles. This is achieved by developing a model
which maps journey and vehicle parameters to an energy consumption, and
applying it individually to the entire data set. As a case study the National
Travel Survey was used to create a set of profiles representing an entirely
electric UK fleet of vehicles. This allowed prediction of the required
electricity demand and sizing of the necessary vehicle batteries. Also, by
inferring location information from the data, the effectiveness of various
charging strategies was assessed. These results will be useful in both National
planning, and as the inputs to further research on the impact of electric
vehicles
Improving the Scalability of a Prosumer Cooperative Game with K-Means Clustering
Among the various market structures under peer-to-peer energy sharing, one
model based on cooperative game theory provides clear incentives for prosumers
to collaboratively schedule their energy resources. The computational
complexity of this model, however, increases exponentially with the number of
participants. To address this issue, this paper proposes the application of
K-means clustering to the energy profiles following the grand coalition
optimization. The cooperative model is run with the "clustered players" to
compute their payoff allocations, which are then further distributed among the
prosumers within each cluster. Case studies show that the proposed method can
significantly improve the scalability of the cooperative scheme while
maintaining a high level of financial incentives for the prosumers.Comment: 6 pages, 4 figures, 2 tables. Accepted to the 13th IEEE PES PowerTech
Conference, 23-27 June 2019, Milano, Ital
Towards a synthesis of naphthalene derived natural products
Dieckmann-type cyclization reactions have been employed in the synthesis of the alkyl substituted naphthoquinone 11 and the naphthalenes 10 and 12. Various conditions for the benzylic oxidation of these compounds have been investigated with a view towards the synthesis of some naphthalene based natural products
A novel topology of high-speed SRM for high-performance traction applications
A novel topology of high-speed Switched Reluctance Machine (SRM) for high-performance traction applications is presented in this article. The target application, a Hybrid Electric Vehicle (HEV) in the sport segment poses very demanding specifications on the power and torque density of the electric traction machine. After evaluating multiple alternatives, the topology proposed is a 2-phase axial flux machine featuring both segmented twin rotors and a segmented stator core. Electromagnetic, thermal and mechanical models of the proposed topology are developed and subsequently integrated in an overall optimisation algorithm in order to find the optimal geometry for the application. Special focus is laid on the thermal management of the machine, due to the tough thermal conditions resulting from the high frequency, high current and highly saturated operation. Some experimental results are also included in order to validate the modelling and simulation results
Distributionally Robust Joint Chance-Constrained Optimization for Networked Microgrids Considering Contingencies and Renewable Uncertainty
In light of a reliable and resilient power system under extreme weather and
natural disasters, networked microgrids integrating local renewable resources
have been adopted extensively to supply demands when the main utility
experiences blackouts. However, the stochastic nature of renewables and
unpredictable contingencies are difficult to address with the deterministic
energy management framework. The paper proposes a comprehensive
distributionally robust joint chance-constrained (DR-JCC) framework that
incorporates microgrid island, power flow, distributed batteries and voltage
control constraints. All chance constraints are solved jointly and each one is
assigned to an optimized violation rate. To highlight, the JCC problem with the
optimized violation rates has been recognized to be NP-hard and challenging to
be solved. This paper proposes a novel evolutionary algorithm that successfully
tackles the problem and reduces the solution conservativeness (i.e. operation
cost) by around 50% comparing with the baseline Bonferroni Approximation.
Considering the imperfect solar power forecast, we construct three data-driven
ambiguity sets to model uncertain forecast error distributions. The solution is
thus robust for any distribution in sets with the shared moment and shape
assumptions. The proposed method is validated by robustness tests based on
those sets and firmly secures the solution robustness.Comment: Accepted by IEEE Transactions on Smart Gri
Impact of spatiotemporal heterogeneity in heat pump loads on generation and storage requirements
This paper investigates how spatiotemporal heterogeneity in inflexible
residential heat pump loads affects the need for storage and generation in the
electricity system under business-as-usual and low-carbon emissions budgets.
Homogeneous and heterogeneous heat pump loads are generated using
population-weighted average and local temperature, respectively, assuming
complete residential heat pump penetration. The results of a storage and
generation optimal expansion model with network effects for spatiotemporally
homogeneous and heterogeneous load profiles are compared. A case study is
performed using a 3-bus network of London, Manchester, and Glasgow in Britain
for load and weather data for representative weeks. Using heterogeneous heating
demand data changes storage sizing: under a business-as-usual budget, 26% more
total storage is built on an energy and power basis, and this storage is
distributed among all of the buses in the heterogeneous case. Under a
low-carbon budget, total energy storage at all buses increases 2 times on an
energy basis and 40% on a power basis. The energy to power ratio of storage at
each bus also increases when accounting for heterogeneity; this change suggests
that storage will be needed to provide energy support in addition to power
support for electric heating in high-renewable power systems. Accounting for
heterogeneity also increases modeled systems costs, particularly capital costs,
because of the need for higher generation capacity in the largest load center
and coincidence of local peak demand at different buses. These results show the
importance of accounting for heat pump load heterogeneity in power system
planning.Comment: 6 pages, 4 figures, to be published in the proceedings of the IEEE
Power and Energy Society General Meeting 202
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