scholarly journals Local Electricity Markets for Electric Vehicles: An Application Study Using a Decentralized Iterative Approach

2021 ◽  
Vol 9 ◽  
Author(s):  
Ricardo Faia ◽  
João Soares ◽  
Mohammad Ali Fotouhi Ghazvini ◽  
John F. Franco ◽  
Zita Vale
Keyword(s):  
Electric Vehicles ◽  
Electricity Markets ◽  
Execution Time ◽  
Optimal Solution ◽  
Peer To Peer ◽  
Market Model ◽  
Mixed Integer ◽  
Local Energy ◽  
Low Carbon ◽  
Energy Community

Local electricity markets are emerging solutions to enable local energy trade for the end users and provide grid support services when required. Various models of local electricity markets (LEMs) have been proposed in the literature. The peer-to-peer market model appears as a promising structure among the proposed models. The peer-to-peer market structure enables electricity transactions between the players in a local energy system at a lower cost. It promotes the production from the small low–carbon generation technologies. Energy communities can be the ideal place to implement local electricity markets as they are designed to allow for larger growth of renewable energy and electric vehicles, while benefiting from local transactions. In this context, a LEM model is proposed considering an energy community with high penetration of electric vehicles in which prosumer-to-vehicle (P2V) transactions are possible. Each member of the energy community can buy electricity from the retailer or other members and sell electricity. The problem is modeled as a mixed-integer linear programing (MILP) formulation and solved within a decentralized and iterative process. The decentralized implementation provides acceptable solutions with a reasonable execution time, while the centralized implementation usually gives an optimal solution at the expense of reduced scalability. Preliminary results indicate that there are advantages for EVs as participants of the LEM, and the proposed implementation ensures an optimal solution in an acceptable execution time. Moreover, P2V transactions benefit the local distribution grid and the energy community.

scholarly journals An Optimization Model for Energy Community Costs Minimization Considering a Local Electricity Market between Prosumers and Electric Vehicles

Electronics ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 129
Author(s):  
Ricardo Faia ◽  
João Soares ◽  
Zita Vale ◽  
Juan Manuel Corchado
Keyword(s):  
Electric Vehicles ◽  
Electricity Market ◽  
Optimization Model ◽  
Local Community ◽  
Programming Model ◽  
Mixed Integer ◽  
Energy Costs ◽  
Local Energy ◽  
Distribution Grid ◽  
Energy Community

Electric vehicles have emerged as one of the most promising technologies, and their mass introduction may pose threats to the electricity grid. Several solutions have been proposed in an attempt to overcome this challenge in order to ease the integration of electric vehicles. A promising concept that can contribute to the proliferation of electric vehicles is the local electricity market. In this way, consumers and prosumers may transact electricity between peers at the local community level, reducing congestion, energy costs and the necessity of intermediary players such as retailers. Thus, this paper proposes an optimization model that simulates an electric energy market between prosumers and electric vehicles. An energy community with different types of prosumers is considered (household, commercial and industrial), and each of them is equipped with a photovoltaic panel and a battery system. This market is considered local because it takes place within a distribution grid and a local energy community. A mixed-integer linear programming model is proposed to solve the local energy transaction problem. The results suggest that our approach can provide a reduction between 1.6% to 3.5% in community energy costs.

A Peer-to-Peer energy trading market model based on time-driven prospect theory in a smart and sustainable energy community

2021 ◽  
Vol 28 ◽  
pp. 100542
Author(s):  
Sobhan Dorahaki ◽  
Masoud Rashidinejad ◽  
Seyed Farshad Fatemi Ardestani ◽  
Amir Abdollahi ◽  
Mohammad Reza Salehizadeh
Keyword(s):  
Prospect Theory ◽  
Sustainable Energy ◽  
Peer To Peer ◽  
Market Model ◽  
Energy Trading ◽  
Model Based ◽  
Trading Market ◽  
Energy Community

Optimal Number and Location of TCSC and Loadability Enhancement in Deregulated Electricity Markets Using MINLP

2006 ◽  
Vol 5 (1) ◽  
Author(s):  
Ashwani Kumar Sharma
Keyword(s):  
Linear Programming ◽  
Electricity Markets ◽  
Test System ◽  
Optimal Number ◽  
Market Model ◽  
Mixed Integer ◽  
Programming Approach ◽  
Reliability Test ◽  
Crucial Issue ◽  
Non Linear Programming

This paper proposes a new method of optimal number and location of TCSC using mixed integer non-linear programming approach in the deregulated electricity markets. Optimal number and location of TCSC controller can effectively enhance system loadability and their placement is a crucial issue due to their high cost. Since, in the competitive electricity environment more and more transactions are negotiated, which can compromise the system security. Therefore, it has become essential to determine secure transactions occurring in the new environment for better planning and management. The system loadability has been determined in a hybrid market model utilizing the secure transaction matrix. The proposed technique has been tested on IEEE 24-bus reliability test system (RTS).

scholarly journals Impacts of Low-Carbon Fuel Standards in Transportation on the Electricity Market

Energies ◽  
2018 ◽  
Vol 11 (8) ◽  
pp. 1943 ◽  
Author(s):  
Ahmad Karnama ◽  
João Peças Lopes ◽  
Mauro Augusto da Rosa
Keyword(s):  
Electric Vehicles ◽  
Electricity Market ◽  
Service Providers ◽  
Negative Impact ◽  
Policy Instrument ◽  
Electricity Price ◽  
Market Model ◽  
Carbon Intensity ◽  
Low Carbon ◽  
Banking Strategy

Electric Vehicles (EVs) are increasing the interdependence of transportation policies and the electricity market dimension. In this paper, an Electricity Market Model with Electric Vehicles (EMMEV) was developed, exploiting an agent-based model that analyzes how carbon reduction policy in transportation may increase the number of Electric Vehicles and how that would influence electricity price. Agents are Energy Service Providers (ESCOs) which can distribute fuels and their objective is to maximize their profit. In this paper, the EMMEV is used to analyze the impacts of the Low-Carbon Fuel Standard (LCFS), a performance-based policy instrument, on electricity prices and EV sales volume. The agents in EMMEV are regulated parties in LCFS should meet a certain Carbon Intensity (CI) target for their distributed fuel. In case they cannot meet the target, they should buy credits to compensate for their shortfall and if they exceed it, they can sell their excess. The results, considering the assumptions and limitations of the model, show that the banking strategy of the agents contributing in the LCFS might have negative impact on penetration of EVs, unless there is a regular Credit Clearance to trade credits. It is also shown that the electricity price, as a result of implementing the LCFS and increasing number of EVs, has increased between 2% and 3% depending on banking strategy.

scholarly journals Optimal Model for Local Energy Community Scheduling Considering Peer to Peer Electricity Transactions

IEEE Access ◽  
2021 ◽  
Vol 9 ◽  
pp. 12420-12430
Author(s):  
Ricardo Faia ◽  
Joao Soares ◽  
Tiago Pinto ◽  
Fernando Lezama ◽  
Zita Vale ◽  
...  
Keyword(s):  
Peer To Peer ◽  
Local Energy ◽  
Optimal Model ◽  
Energy Community

scholarly journals Impacts of Low Carbon Fuel Standards in Transportation on the Electricity Market

2018 ◽  
Author(s):  
Ahmad Karnama ◽  
João Abel Peças Lopes ◽  
Mauro Augusto da Rosa
Keyword(s):  
Electric Vehicles ◽  
Electricity Market ◽  
Service Providers ◽  
Negative Impact ◽  
Policy Instrument ◽  
Electricity Price ◽  
Market Model ◽  
Carbon Intensity ◽  
Low Carbon ◽  
Banking Strategy

Electric Vehicles (EVs) are increasing the interdependence of transportation policies and the electricity market. EMMEV (Electricity Market Model with Electric Vehicles) is an experimental agent-based model that analyses how carbon reduction policy in transportation may increase number of Electric Vehicles and how does that would influence on the electricity price. Agents are ESCOs (Energy Service Providers) which can distribute fuels and their objective is to maximize their profit. In this paper, EMMEV is used to analyze the impacts of the LCFS (Low Carbon Fuel Standard), a performance-based policy instrument, on electricity prices and EV sales. The agents in EMMEV/regulated parties in LCFS should meet a certain CI (Carbon Intensity) target for their distributed fuel. In case, they cannot meet the target, they should buy credit to compensate for their shortfall and if they exceed, they can sell their excess. The results, considering the assumptions and limitations of the model, show that the banking strategy of the agents contributing in the LCFS might have negative impact on penetration of EVs, unless there is a regular Credit Clearance to trade credits. It is also shown that the electricity price as result of implementing the LCFS and increasing number of EVs has increased between 2–3 percent depending on banking strategy.

scholarly journals Integrating Bidirectionally Chargeable Electric Vehicles into the Electricity Markets

Energies ◽  
2020 ◽  
Vol 13 (21) ◽  
pp. 5812
Author(s):  
Timo Kern ◽  
Patrick Dossow ◽  
Serafin von Roon
Keyword(s):  
Electric Vehicles ◽  
Electricity Markets ◽  
User Behavior ◽  
Combustion Engine ◽  
Energy System ◽  
Mixed Integer ◽  
Transport Sector ◽  
Market Prices ◽  
Vehicle To Grid ◽  
Average Size

Replacing traditional internal combustion engine vehicles with electric vehicles (EVs) proves to be challenging for the transport sector, particularly due to the higher initial investment. As EVs could be more profitable by participating in the electricity markets, the aim of this paper is to investigate revenue potentials when marketing bidirectionally chargeable electric vehicles in the spot market. To simulate a realistic marketing behavior of electric vehicles, a mixed integer linear, rolling horizon optimization model is formulated considering real trading times in the day-ahead and intraday market. Results suggest that revenue potentials are strongly dependent on the EV pool, the user behavior and the regulatory framework. Modeled potential revenues of EVs of current average size marketed with 2019 German day-ahead prices are found to be at around 200 €/EV/a, which is comparable to other findings in literature, and go up to 500 €/EV/a for consecutive trading in German day-ahead and intraday markets. For future EVs with larger batteries and higher efficiencies, potential revenues for current market prices can reach up to 1300 €/EV/a. This study finds that revenues differ widely for different European countries and future perspectives. The identified revenues give EV owners a clear incentive to participate in vehicle-to-grid use cases, thereby increasing much needed flexibility for the energy system of the future.

scholarly journals New variable neighbourhood search based 0-1 MIP heuristics

2015 ◽  
Vol 25 (3) ◽  
pp. 343-360 ◽  
Author(s):  
Saïd Hanafi ◽  
Jasmina Lazic ◽  
Nenad Mladenovic ◽  
Christophe Wilbaut ◽  
Igor Crévits
Keyword(s):  
Integer Programming ◽  
Mixed Integer Programming ◽  
Execution Time ◽  
State Of The Art ◽  
Optimal Solution ◽  
Mixed Integer ◽  
Variable Neighbourhood Search ◽  
Solution Quality ◽  
Current State ◽  
Neighbourhood Search

In recent years many so-called matheuristics have been proposed for solving Mixed Integer Programming (MIP) problems. Though most of them are very efficient, they do not all theoretically converge to an optimal solution. In this paper we suggest two matheuristics, based on the variable neighbourhood decomposition search (VNDS), and we prove their convergence. Our approach is computationally competitive with the current state-of-the-art heuristics, and on a standard benchmark of 59 0-1 MIP instances, our best heuristic achieves similar solution quality to that of a recently published VNDS heuristic for 0-1 MIPs within a shorter execution time.

scholarly journals How Smart Metering and Smart Charging may Help a Local Energy Community in Collective Self-Consumption in Presence of Electric Vehicles

Energies ◽  
2020 ◽  
Vol 13 (16) ◽  
pp. 4163
Author(s):  
Giuseppe Barone ◽  
Giovanni Brusco ◽  
Daniele Menniti ◽  
Anna Pinnarelli ◽  
Gaetano Polizzi ◽  
...  
Keyword(s):  
Renewable Energy ◽  
Electric Vehicles ◽  
Experimental Test ◽  
Local Community ◽  
Transition Process ◽  
Local Energy ◽  
Smart Metering ◽  
Smart Meters ◽  
Smart Charging ◽  
Energy Community

The 2018/2001/EU renewable energy directive (RED II) underlined the strategic role of energy communities in the EU transition process towards sustainable and renewable energy. In line with the path traced by RED II, this paper proposes a solution that may help local energy communities in increasing self-consumption. The proposed solution is based on the combination of smart metering and smart charging. A set of smart meters returns the profile of each member of the community with a time resolution of 5 s; the aggregator calculates the community profile and regulates the charging of electric vehicles accordingly. An experimental test is performed on a local community composed of four users, where the first is a consumer with a Nissan Leaf, whereas the remaining three users are prosumers with a photovoltaic generator mounted on the roof of their home. The results of the experimental test show the feasibility of the proposed solution and demonstrate its effectiveness in increasing self-consumption. The paper also calculates the subsidy that the community under investigation would receive if the current Italian incentive policies for renewables were extended to local energy communities; this subsidy is discussed in comparison with the subsidies that the three prosumers individually receive thanks to the net metering mechanism. This paper ends with an economic analysis and calculation of savings on bills when the four users create the local energy community and adopt the proposed combination of smart metering and smart charging.

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