A simulative framework for a multi-regional assessment of local energy markets – A case of large-scale electric vehicle deployment in Germany

The future direction of electric vehicle (EV) transportation in relation to the energy demand for charging EVs needs a more sustainable roadmap, compared to the current reliance on the centralised electricity grid system. It is common knowledge that the current state of electricity grids in the biggest economies of the world today suffer a perennial problem of power losses; and were not designed for the uptake and integration of the growing number of large-scale EV charging power demands from the grids. To promote sustainable EV transportation, this study aims to review the current state of research and development around this field. This study is significant to the effect that it accomplishes four major objectives. (1) First, the implication of large-scale EV integration to the electricity grid is assessed by looking at the impact on the distribution network. (2) Secondly, it provides energy management strategies for optimizing plug-in EVs load demand on the electricity distribution network. (3) It provides a clear direction and an overview on sustainable EV charging infrastructure, which is highlighted as one of the key factors that enables the promotion and sustainability of the EV market and transportation sector, re-engineered to support the United Nations Climate Change Agenda. Finally, a conclusion is made with some policy recommendations provided for the promotion of the electric vehicle market and widespread adoption in any economy of the world.

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Intelligent Bidding in Smart Electricity Markets

Renewable and Alternative Energy ◽

10.4018/978-1-5225-1671-2.ch021 ◽

2017 ◽

pp. 712-734

Author(s):

Magda Foti ◽

Manolis Vavalis

Keyword(s):

Electricity Markets ◽

Large Scale ◽

Electric Energy ◽

Energy Markets ◽

Simulation System ◽

Theoretical Studies ◽

The Social ◽

Early Proof ◽

Simulation Results ◽

Large Scale Simulations

This paper has two aims. Firstly, to briefly present overall objectives and expected outcome of an on-going effort concerning design, implementation and the analysis of next generation energy systems based on anticipatory control and a set of ICT emerging technologies and innovations. Secondly, to describe an early proof-of-concept implementation and the associated experimentation of a simulation platform focused on holistic detailed studies of electric energy markets. The proposed platform allows us to elucidate issues related to the open and smart participation of producers and consumers on large-scale e-markets. Based on an existing simulation system, the authors present the required theoretical studies, the enabling technologies, and the practical tools that contribute to the development of such a platform capable of truly large scale simulations. Elements of game theory are utilized to solve the optimization problem related to the maximization of the social welfare of producers and consumers. Selected simulation results associated with the basic required characteristics are presented.

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Load profiling revisited: prosumer profiling for local energy markets

Local Electricity Markets ◽

10.1016/b978-0-12-820074-2.00004-6 ◽

2021 ◽

pp. 215-242

Author(s):

Gianfranco Chicco ◽

Andrea Mazza

Keyword(s):

Energy Markets ◽

Local Energy

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A framework for designing and evaluating realistic blockchain-based local energy markets

Applied Energy ◽

10.1016/j.apenergy.2020.115963 ◽

2021 ◽

Vol 281 ◽

pp. 115963 ◽

Cited By ~ 1

Author(s):

Konstantinos Christidis ◽

Dimitrios Sikeridis ◽

Yun Wang ◽

Michael Devetsikiotis

Keyword(s):

Energy Markets ◽

Local Energy

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Load Forecasting of Charging and Swapping in Large-Scale Electric Vehicle

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.568-570.1969 ◽

2014 ◽

Vol 568-570 ◽

pp. 1969-1977 ◽

Cited By ~ 1

Author(s):

Jian Cheng Ye ◽

Yu Ling Li ◽

Dong Liang Zhang ◽

Xiang Jing Zhu ◽

Jin Da Zhu

Keyword(s):

Electric Vehicle ◽

Large Scale ◽

Access Network ◽

Calculation Model ◽

Simulation Algorithm ◽

Charging Time ◽

Load Calculation ◽

Other Information ◽

Charging Mode ◽

Ev Charging

This article combs the charging mode of electric vehicle,and analyzes different charging ways for buses,taxis and sedans,thereby drawing their appropriate charging time and characteristics of the interaction with grid. The paper establishes the load calculation model for the charging and swapping in Evs respectively. The load calculation model divides one day into 1440 minutes, and use the Monte Carlo simulation algorithm to extract the initial SOC, the initial charging time and other information for load calculation and analyze the EV charging load. The results show that the charging load of electric vehicle has obvious difference between peak and vally,and provide reference for the management and policy oriented electric vhicle access network.

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Automated Negotiation for Peer-to-Peer Electricity Trading in Local Energy Markets

Energies ◽

10.3390/en13040920 ◽

2020 ◽

Vol 13 (4) ◽

pp. 920 ◽

Cited By ~ 8

Author(s):

Christie Etukudor ◽

Benoit Couraud ◽

Valentin Robu ◽

Wolf-Gerrit Früh ◽

David Flynn ◽

...

Keyword(s):

Developing Countries ◽

Low Cost ◽

Energy Markets ◽

Peer To Peer ◽

Sub Saharan Africa ◽

Local Energy ◽

Automated Negotiation ◽

Solar Pv ◽

Negotiation Strategies ◽

Alternating Offers

Reliable access to electricity is still a challenge in many developing countries. Indeed, rural areas in sub-Saharan Africa and developing countries such as India still encounter frequent power outages. Local energy markets (LEMs) have emerged as a low-cost solution enabling prosumers with power supply systems such as solar PV to sell their surplus of energy to other members of the local community. This paper proposes a one-to-one automated negotiation framework for peer-to-peer (P2P) local trading of electricity. Our framework uses an autonomous agent model to capture the preferences of both an electricity seller (consumer) and buyer (small local generator or prosumer), in terms of price and electricity quantities to be traded in different periods throughout a day. We develop a bilateral negotiation framework based on the well-known Rubinstein alternating offers protocol, in which the quantity of electricity and the price for different periods are aggregated into daily packages and negotiated between the buyer and seller agent. The framework is then implemented experimentally, with buyers and sellers adopting different negotiation strategies based on negotiation concession algorithms, such as linear heuristic or Boulware. Results show that this framework and agents modelling allow prosumers to increase their revenue while providing electricity access to the community at low cost.

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