8,661 research outputs found
Comparison of intelligent charging algorithms for electric vehicles to reduce peak load and demand variability in a distribution grid
A potential breakthrough of the electrification of the vehicle fleet will incur a steep rise in the load on the electrical power grid. To avoid huge grid investments, coordinated charging of those vehicles is a must. In this paper, we assess algorithms to schedule charging of plug-in (hybrid) electric vehicles as to minimize the additional peak load they might cause. We first introduce two approaches, one based on a classical optimization approach using quadratic programming, and a second one, market based coordination, which is a multi-agent system that uses bidding on a virtual market to reach an equilibrium, price that matches demand and supply. We benchmark these two methods against each other, as well as to a baseline scenario of uncontrolled charging. Our simulation results covering a residential area with 63 households show that controlled charging reduces peak load, load variability, and deviations from the nominal grid voltage
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Open-Source, Open-Architecture SoftwarePlatform for Plug-InElectric Vehicle SmartCharging in California
This interdisciplinary eXtensible Building Operating System–Vehicles project focuses on controlling plug-in electric vehicle charging at residential and small commercial settings using a novel and flexible open-source, open-architecture charge communication and control platform. The platform provides smart charging functionalities and benefits to the utility, homes, and businesses.This project investigates four important areas of vehicle-grid integration research, integrating technical as well as social and behavioral dimensions: smart charging user needs assessment, advanced load control platform development and testing, smart charging impacts, benefits to the power grid, and smart charging ratepayer benefits
Power quality and electromagnetic compatibility: special report, session 2
The scope of Session 2 (S2) has been defined as follows by the Session Advisory Group and the Technical Committee: Power Quality (PQ), with the more general concept of electromagnetic compatibility (EMC) and with some related safety problems in electricity distribution systems.
Special focus is put on voltage continuity (supply reliability, problem of outages) and voltage quality (voltage level, flicker, unbalance, harmonics). This session will also look at electromagnetic compatibility (mains frequency to 150 kHz), electromagnetic interferences and electric and magnetic fields issues. Also addressed in this session are electrical safety and immunity concerns (lightning issues, step, touch and transferred voltages).
The aim of this special report is to present a synthesis of the present concerns in PQ&EMC, based on all selected papers of session 2 and related papers from other sessions, (152 papers in total). The report is divided in the following 4 blocks:
Block 1: Electric and Magnetic Fields, EMC, Earthing systems
Block 2: Harmonics
Block 3: Voltage Variation
Block 4: Power Quality Monitoring
Two Round Tables will be organised:
- Power quality and EMC in the Future Grid (CIGRE/CIRED WG C4.24, RT 13)
- Reliability Benchmarking - why we should do it? What should be done in future? (RT 15
Catching Cheats: Detecting Strategic Manipulation in Distributed Optimisation of Electric Vehicle Aggregators
Given the rapid rise of electric vehicles (EVs) worldwide, and the ambitious
targets set for the near future, the management of large EV fleets must be seen
as a priority. Specifically, we study a scenario where EV charging is managed
through self-interested EV aggregators who compete in the day-ahead market in
order to purchase the electricity needed to meet their clients' requirements.
With the aim of reducing electricity costs and lowering the impact on
electricity markets, a centralised bidding coordination framework has been
proposed in the literature employing a coordinator. In order to improve privacy
and limit the need for the coordinator, we propose a reformulation of the
coordination framework as a decentralised algorithm, employing the Alternating
Direction Method of Multipliers (ADMM). However, given the self-interested
nature of the aggregators, they can deviate from the algorithm in order to
reduce their energy costs. Hence, we study the strategic manipulation of the
ADMM algorithm and, in doing so, describe and analyse different possible attack
vectors and propose a mathematical framework to quantify and detect
manipulation. Importantly, this detection framework is not limited the
considered EV scenario and can be applied to general ADMM algorithms. Finally,
we test the proposed decentralised coordination and manipulation detection
algorithms in realistic scenarios using real market and driver data from Spain.
Our empirical results show that the decentralised algorithm's convergence to
the optimal solution can be effectively disrupted by manipulative attacks
achieving convergence to a different non-optimal solution which benefits the
attacker. With respect to the detection algorithm, results indicate that it
achieves very high accuracies and significantly outperforms a naive benchmark
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Corrective receding horizon EV charge scheduling using short-term solar forecasting
Forecast errors can cause sub-optimal solutions in resource planning optimization, yet they are usually modeled simplistically by statistical models, causing unrealistic impacts on the optimal solutions. In this paper, realistic forecast errors are prescribed, and a corrective approach is proposed to mitigate the negative effects of day-ahead persistence forecast error by short-term forecasts from a state-of-the-art sky imager system. These forecasts preserve the spatiotemporal dependence structure of forecast errors avoiding statistical approximations. The performance of the proposed algorithm is tested on a receding horizon quadratic program developed for valley filling the midday net load depression through electric vehicle charging. Throughout one month of simulations the ability to flatten net load is assessed under practical forecast accuracy levels achievable from persistence, sky imager and perfect forecasts. Compared to using day-ahead persistence solar forecasts, the proposed corrective approach using sky imager forecasts delivers a 25% reduction in the standard deviation of the daily net load. It is demonstrated that correcting day-ahead forecasts in real time with more accurate short-term forecasts benefits the valley filling solution
Ancillary Services in Hybrid AC/DC Low Voltage Distribution Networks
In the last decade, distribution systems are experiencing a drastic transformation
with the advent of new technologies. In fact, distribution networks are no longer passive
systems, considering the current integration rates of new agents such as distributed generation,
electrical vehicles and energy storage, which are greatly influencing the way these systems are
operated. In addition, the intrinsic DC nature of these components, interfaced to the AC system
through power electronics converters, is unlocking the possibility for new distribution topologies
based on AC/DC networks. This paper analyzes the evolution of AC distribution systems,
the advantages of AC/DC hybrid arrangements and the active role that the new distributed agents
may play in the upcoming decarbonized paradigm by providing different ancillary services.Ministerio de Economía y Competitividad ENE2017-84813-RUnión Europea (Programa Horizonte 2020) 76409
Transforming Energy Networks via Peer to Peer Energy Trading: Potential of Game Theoretic Approaches
Peer-to-peer (P2P) energy trading has emerged as a next-generation energy
management mechanism for the smart grid that enables each prosumer of the
network to participate in energy trading with one another and the grid. This
poses a significant challenge in terms of modeling the decision-making process
of each participant with conflicting interest and motivating prosumers to
participate in energy trading and to cooperate, if necessary, for achieving
different energy management goals. Therefore, such decision-making process
needs to be built on solid mathematical and signal processing tools that can
ensure an efficient operation of the smart grid. This paper provides an
overview of the use of game theoretic approaches for P2P energy trading as a
feasible and effective means of energy management. As such, we discuss various
games and auction theoretic approaches by following a systematic classification
to provide information on the importance of game theory for smart energy
research. Then, the paper focuses on the P2P energy trading describing its key
features and giving an introduction to an existing P2P testbed. Further, the
paper zooms into the detail of some specific game and auction theoretic models
that have recently been used in P2P energy trading and discusses some important
finding of these schemes.Comment: 38 pages, single column, double spac
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