scholarly journals Distributed Electric Vehicle Charging Scheduling with Transactive Energy Management

Energies ◽  
2021 ◽  
Vol 15 (1) ◽  
pp. 163
Author(s):  
Zhouquan Wu ◽  
Bo Chen
Keyword(s):  
Electric Vehicle ◽  
Energy Management ◽  
Distribution System ◽  
Optimal Power Flow ◽  
Distribution Network ◽  
Economic Benefits ◽  
Negotiation Process ◽  
Electricity Price ◽  
Transactive Energy ◽  
Ev Charging

A distributed electric vehicle (EV) charging scheduling strategy with transactive energy (TE) management is presented in this paper to deal with technical issues in distribution network operation and discuss the economic benefits of EV charging. At an individual EV level, EV owners propose bids to actively participate in the distribution system operation. At the node level, an electric vehicle aggregator (EVA) optimally allocates the available charging power to meet EV charging requirements and cost benefits. At the distribution network level, a distribution system operator (DSO) integrates an electricity price market clearing mechanism with the optimal power flow (OPF) technique to ensure the reliability of the distribution network. Moreover, a distributed algorithm is discussed for solving the EV charging problem with transactive energy management (TEM). The clearing electricity price is achieved through a negotiation process between the DSO and EVAs using the alternating direction method of multipliers (ADMM). The presented EV charging scheduling with TEM is tested on a modified IEEE 33-bus distribution network scenario with 230 EV charging loads. The simulation results demonstrate the effectiveness of the TE-based EV charging scheduling system.

scholarly journals Smart charging for electric vehicles to minimise charging cost

2017 ◽  
Vol 231 (6) ◽  
pp. 526-534 ◽  
Author(s):  
Yue Wang ◽  
David Infield ◽  
Simon Gill
Keyword(s):  
Electric Vehicle ◽  
Electric Vehicles ◽  
Distribution System ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Low Voltage ◽  
Wholesale Price ◽  
Heuristic Method ◽  
Domain Model ◽  
Smart Charging

This paper assumes a smart grid framework where the driving patterns for electric vehicles are known, time variations in electricity prices are communicated to householders, and data on voltage variation throughout the distribution system are available. Based on this information, an aggregator with access to this data can be employed to minimise electric vehicles charging costs to the owner whilst maintaining acceptable distribution system voltages. In this study, electric vehicle charging is assumed to take place only in the home. A single-phase Low Voltage (LV) distribution network is investigated where the local electric vehicles penetration level is assumed to be 100%. Electric vehicle use patterns have been extracted from the UK Time of Use Survey data with a 10-min resolution and the domestic base load is generated from an existing public domain model. Apart from the so-called real time price signal, which is derived from the electricity system wholesale price, the cost of battery degradation is also considered in the optimal scheduling of electric vehicles charging. A simple and effective heuristic method is proposed to minimise the electric vehicles’ charging cost whilst satisfying the requirement of state of charge for the electric vehicles’ battery. A simulation in OpenDSS over a period of 24 h has been implemented, taking care of the network constraints for voltage level at the customer connection points. The optimisation results are compared with those obtained using dynamic optimal power flow.

scholarly journals Sustainable Electric Vehicle Transportation

2021 ◽  
Vol 13 (22) ◽  
pp. 12379
Author(s):  
Raymond Kene ◽  
Thomas Olwal ◽  
Barend J. van Wyk
Keyword(s):  
Electric Vehicle ◽  
Energy Demand ◽  
Large Scale ◽  
Common Knowledge ◽  
Distribution Network ◽  
Electricity Grid ◽  
Current State ◽  
The World ◽  
The Impact ◽  
Ev Charging

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.

Fast Service Restoration of Multi-Source Active Distribution Network with Microgrids and Electric Vehicles

2014 ◽  
Vol 672-674 ◽  
pp. 1175-1178
Author(s):  
Guang Min Fan ◽  
Ling Xu Guo ◽  
Wei Liang ◽  
Hong Tao Qie
Keyword(s):  
Electric Vehicles ◽  
Distribution System ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Large Scale ◽  
Distribution Network ◽  
Active Distribution Network ◽  
Optimal Power ◽  
Service Restoration ◽  
Restoration Method

The increasingly serious energy crisis and environmental pollution problems promote the large-scale application of microgrids (MGs) and electric vehicles (EVs). As the main carrier of MGs and EVs, distribution network is gradually presenting multi-source and active characteristics. A fast service restoration method of multi-source active distribution network with MGs and EVs is proposed in this paper for service restoration of distribution network, which takes effectiveness, rapidity, economy and reliability into consideration. Then, different optimal power flow (OPF) models for the service restoration strategy are constructed separately to minimize the network loss after service restoration. In addition, a genetic algorithm was introduced to solve the OPF model. The analysis of the service restoration strategy is carried out on an IEEE distribution system with three-feeder and eighteen nodes containing MGs and EVs, and the feasibility and effectiveness are verified

scholarly journals Reactive Power Management Considering Stochastic Optimization under the Portuguese Reactive Power Policy Applied to DER in Distribution Networks

Energies ◽  
2019 ◽  
Vol 12 (21) ◽  
pp. 4028 ◽  
Author(s):  
Abreu ◽  
Soares ◽  
Carvalho ◽  
Morais ◽  
Simão ◽  
...  
Keyword(s):  
Power Management ◽  
Distribution System ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Reactive Power ◽  
Renewable Energy Sources ◽  
Distribution Network ◽  
Real Data ◽  
Distribution Networks ◽  
System Operator

Challenges in the coordination between the transmission system operator (TSO) and the distribution system operator (DSO) have risen continuously with the integration of distributed energy resources (DER). These technologies have the possibility to provide reactive power support for system operators. Considering the Portuguese reactive power policy as an example of the regulatory framework, this paper proposes a methodology for proactive reactive power management of the DSO using the renewable energy sources (RES) considering forecast uncertainty available in the distribution system. The proposed method applies a stochastic sequential alternative current (AC)-optimal power flow (SOPF) that returns trustworthy solutions for the DSO and optimizes the use of reactive power between the DSO and DER. The method is validated using a 37-bus distribution network considering real data. Results proved that the method improves the reactive power management by taking advantage of the full capabilities of the DER and by reducing the injection of reactive power by the TSO in the distribution network and, therefore, reducing losses.

scholarly journals A Mathematical Model for the Scheduling of Virtual Microgrids Topology into an Active Distribution Network

2020 ◽  
Vol 10 (20) ◽  
pp. 7199
Author(s):  
Fernando García-Muñoz ◽  
Francisco Díaz-González ◽  
Cristina Corchero
Keyword(s):  
Distribution System ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Distribution Network ◽  
Mathematical Optimization ◽  
Renewable Resource ◽  
Total Load ◽  
Load Response ◽  
Load Curtailment ◽  
Battery Energy

This article presents a method based on a mathematical optimization model for the scheduling operation of a distribution network (DN). The contribution of the proposed method is that it permits the configuration and operation of a DN as a set of virtual microgrids with a high penetration level of distributed generation (DG) and battery energy storage systems (BESS). The topology of such virtual microgrids are modulated in time in response to grid failures, thus minimizing load curtailment, and maximizing local renewable resource and storage utilization as well. The formulation provides the load reduced by bus to balance the system at every hour and the global probability to present energy not supplied (ENS). Furthermore, for every bus, a flexibility load response range is considered to avoid its total load curtailment for small load reductions. The model has been constructed considering a linear version of the AC optimal power flow (OPF) constraints extended for multiple periods, and it has been tested in a modified version of the IEEE 33-bus radial distribution system considering four different scenarios of 72 h, where the global energy curtailment has been 27.9% without demand-side response (DSR) and 10.4% considering a 30% of flexibility load response. Every scenario execution takes less than a minute, making it appropriate for distribution system operational planning.

scholarly journals Distribution Optimal Power Flow With Energy Sharing Via a Peer-To-Peer Transactive Market

2021 ◽  
Vol 9 ◽  
Author(s):  
Boshen Zheng ◽  
Yue Fan ◽  
Wei Wei ◽  
Yourui Xu ◽  
Shaowei Huang ◽  
...  
Keyword(s):  
Equilibrium Condition ◽  
Power Flow ◽  
Distribution Systems ◽  
Optimal Power Flow ◽  
Distribution Network ◽  
Market Equilibrium ◽  
Peer To Peer ◽  
Mixed Integer ◽  
Optimal Power ◽  
Transactive Energy

The technology advancement and cost decline of renewable and sustainable energy increase the penetration of distributed energy resources (DERs) in distribution systems. Transactive energy helps balance the local generation and demand. Peer-to-peer (P2P) energy trading is a promising business model for transactive energy. Such a market scheme can increase the revenue of DER owners and reduce the waste of renewable energy. This article proposes an equilibrium model of a P2P transactive energy market. Every participant seeks the maximum personal interest, with the options of importing or providing energy from/to any other peer across different buses of the distribution network. The market equilibrium condition is obtained by combining the Karush–Kuhn–Tucker conditions of all problems of individual participants together. The energy transaction price is endogenously determined from the market equilibrium condition, which is cast as a mixed-integer linear program and solved by a commercial solver. The transactive energy flow is further embedded in the optimal power flow problem to ensure operating constraints of the distribution network. We propose a remedy to recover a near optimal solution when the second-order cone relaxation is inexact. Finally, a case study demonstrates that the proposed P2P market benefits all participants.

Fault location in distribution network using travelling waves

2019 ◽  
Vol 13 (3) ◽  
pp. 651-669
Author(s):  
Ranjeet Kumar ◽  
D. Saxena
Keyword(s):  
Fault Detection ◽  
Electric Vehicle ◽  
Distributed Generation ◽  
Power Supply ◽  
Fault Location ◽  
Travelling Waves ◽  
Distribution Network ◽  
Travelling Wave ◽  
Content Type ◽  
Ev Charging

Purpose An electrical power distribution network is expected to deliver uninterrupted power supply to the customers. The disruption in power supply occurs whenever there is a fault in the system. Therefore, fast fault detection and its precise location are necessary to restore the power supply. Several techniques are proposed in the past for fault location in distribution network but they have limitations as their fault location accuracy depends on system conditions. The purpose of this paper is to present a travelling wave-based fault location method, which is fast, accurate and independent of system conditions. Design/methodology/approach This paper proposes an effective method for fault detection, classification and location using wavelet analysis of travelling waves for a multilateral distribution network embedded with distributed generation (DG) and electric vehicle (EV) charging load. The wavelet energy entropy (WEE) is used for fault detection and classification purpose, and wavelet modulus maxima (WMM) of aerial mode component is used for faulted lateral identification and exact fault location. Findings The proposed method effectively detects and classifies the faults, and accurately determines the exact fault location in a multilateral distribution network. It is also found that the proposed method is robust and its accuracy is not affected by the presence of distributed generation and electric vehicle charging load in the system. Originality/value Travelling wave based method for fault location is implemented for a multilateral distribution network containing distributed generation and electric vehicle load. For the first time, a fault location method is tested in the presence of EV charging load in distribution network.

scholarly journals Energy Flexometer: Transactive Energy-Based Internet of Things Technology

Energies ◽  
2018 ◽  
Vol 11 (3) ◽  
pp. 568 ◽  
Author(s):  
Muhammad Babar ◽  
Jakub Grela ◽  
Andrzej Ożadowicz ◽  
Phuong Nguyen ◽  
Zbigniew Hanzelka ◽  
...  
Keyword(s):  
Internet Of Things ◽  
Energy Management ◽  
Power Distribution ◽  
Distribution System ◽  
Energy System ◽  
Evaluation Study ◽  
New Paradigm ◽  
Power Distribution System ◽  
Transactive Energy ◽  
Internet Of Things Technology

Effective Energy Management with an active Demand Response (DR) is crucial for future smart energy system. Increasing number of Distributed Energy Resources (DER), local microgrids and prosumers have an essential and real influence on present power distribution system and generate new challenges in power, energy and demand management. A relatively new paradigm in this field is transactive energy (TE), with its value and market-based economic and technical mechanisms to control energy flows. Due to a distributed structure of present and future power system, the Internet of Things (IoT) environment is needed to fully explore flexibility potential from the end-users and prosumers, to offer a bid to involved actors of the smart energy system. In this paper, new approach to connect the market-driven (bottom-up) DR program with current demand-driven (top-down) energy management system (EMS) is presented. Authors consider multi-agent system (MAS) to realize the approach and introduce a concept and standardize the design of new Energy Flexometer. It is proposed as a fundamental agent in the method. Three different functional blocks have been designed and presented as an IoT platform logical interface according to the LonWorks technology. An evaluation study has been performed as well. Results presented in the paper prove the proposed concept and design.

scholarly journals Evaluating the Economic Benefits of a Smart-Community Microgrid with Centralized Electrical Storage and Photovoltaic Systems

Energies ◽  
2020 ◽  
Vol 13 (7) ◽  
pp. 1764 ◽  
Author(s):  
Jura Arkhangelski ◽  
Pierluigi Siano ◽  
Abdou-Tankari Mahamadou ◽  
Gilles Lefebvre
Keyword(s):  
Distribution System ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Short Term Memory ◽  
Storage System ◽  
Economic Benefits ◽  
Mixed Integer ◽  
Forecast Errors ◽  
Smart Community ◽  
The Impact

In this paper, an innovative method for managing a smart-community microgrid (SCM) with a centralized electrical storage system (CESS) is proposed. The method consists of day-ahead optimal power flow (DA–OPF) for day-ahead SCM managing and its subsequent evaluation, considering forecast uncertainties. The DA–OPF is based on a data forecast system that uses a deep learning (DL) long short-term memory (LSTM) network. The OPF problem is formulated as a mathematical mixed-integer nonlinear programming (MINLP) model. Following this, the developed DA–OPF strategy was evaluated under possible operations, using a Monte Carlo simulation (MCS). The MCS allowed us to obtain potential deviations of forecasted data during possible day-ahead operations and to evaluate the impact of the data forecast errors on the SCM, and that of unit limitation and the emergence of critical situations. Simulation results on a real existing rural conventional community endowed with a centralized community renewable generation (CCRG) and CESS, confirmed the effectiveness of the proposed operation method. The economic analysis showed significant benefits and an electricity price reduction for the considered community if compared to a conventional distribution system, as well as the easy applicability of the proposed method due to the CESS and the developed operating systems.

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