Scenario-Wise Distributionally Robust Optimization for Collaborative Intermittent Resources and Electric Vehicle Aggregator Bidding Strategy

Hajebrahimi, Ali; Kamwa, Innocent; Abdelaziz, Morad; Moeini, Ali

doi:10.1109/tpwrs.2020.2985572

Cited by 42 publications

(15 citation statements)

References 34 publications

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“…Most existing studies [3,12,13,21,31] considered the EVA operation in day-ahead electricity market, as EVA should plan the charging scheduling for each EV beforehand. Specifically, [13] proposed an optimal operation strategy for an EVA, which performs energy arbitrage in the energy market and provides ancillary services from aggregated EVs, while providing charging services to EVs to maximize the profit in a future energy market.…”

Section: Vehicle-to-grid (V2g) 31 Energy Trading In the Electricity M...mentioning

confidence: 99%

A Holistic Review on Advanced Bi-directional EV Charging Control Algorithms

Tang

Sun

et al. 2022

Preprint

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The rapid growth of electric vehicles (EVs) has promised a next-generation transportation system with reduced carbon emission. The fast development of EVs and charging facilities is driving the evolution of Internet of Vehicles (IoV) to Internet of Electric Vehicles (IoEV). IoEV benefits from both smart grid and Internet of Things (IoT) technologies which provide advanced bi-directional charging services and real-time data processing capability, respectively. The major design challenges of the IoEV charging control lie in the randomness of charging events and the mobility of EVs. In this article, we present a holistic review on advanced bi-directional EV charging control algorithms. For Grid-to-Vehicle (G2V), we introduce the charging control problem in two scenarios: 1) Operation of a single charging station and 2) Operation of multiple charging stations in coupled transportation and power networks. For Vehicle-to-Grid (V2G), we discuss how EVs can perform energy trading in the electricity market and provide ancillary services to the power grid. Besides, a case study is provided to illustrate the economic benefit of the joint optimization of routing and charging scheduling of multiple EVs in the IoEV. Last but not the least, we will highlight some open problems and future research directions of charging scheduling problems for IoEVs.CCS Concepts: • General and reference → Surveys and overviews.

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Section: Vehicle-to-grid (V2g) 31 Energy Trading In the Electricity M...mentioning

confidence: 99%

A Holistic Review on Advanced Bi-directional EV Charging Control Algorithms

Tang

Sun

et al. 2022

Preprint

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“…DRO has relatively simple requirements on uncertainty with respect to stochastic programming, as well as a simple mathematical tractability. Recent applications refer to optimisation of energy hub operation (Zhao et al, 2020) and determination of bidding strategy models for aggregators (Hajebrahimi et al, 2020). 6) Model predictive control (MPC): for data-driven applications, new data may become available during time in dynamic processes.…”

Section: Certainty: Handling Uncertaintiesmentioning

confidence: 99%

Data Consistency for Data-Driven Smart Energy Assessment

Chicco

2021

Front. Big Data

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In the smart grid era, the number of data available for different applications has increased considerably. However, data could not perfectly represent the phenomenon or process under analysis, so their usability requires a preliminary validation carried out by experts of the specific domain. The process of data gathering and transmission over the communication channels has to be verified to ensure that data are provided in a useful format, and that no external effect has impacted on the correct data to be received. Consistency of the data coming from different sources (in terms of timings and data resolution) has to be ensured and managed appropriately. Suitable procedures are needed for transforming data into knowledge in an effective way. This contribution addresses the previous aspects by highlighting a number of potential issues and the solutions in place in different power and energy system, including the generation, grid and user sides. Recent references, as well as selected historical references, are listed to support the illustration of the conceptual aspects.

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“…Gong et al [27] developed the optimum bidding model in which the thermal-wind hybrid system signs bilateral contracts with the battery swapping station and participates in the DA market. [27][28][29][30][31], EVPLs and line capacities are not considered in these studies. Also, bilateral contracts were not included in studies other than [27].…”

Section: Relevant Backgroundmentioning

confidence: 99%

“…Also, bilateral contracts were not included in studies other than [27]. While risk management is covered only in [28,30], portfolio structure is only considered in [28,29,31] Aliasghari et al [33] proposed a structure where the renewable microgrid in the presence of plug-in EVs participates in the power market minimizing the operating cost. Aghajani and Kalantar [34] presented a bidding strategy for the DA market and reserve market participation, in the joint operation of WPP, EVPL, and load retailer.…”

Section: Relevant Backgroundmentioning

confidence: 99%

Risk-averse optimal bidding strategy for a wind energy portfolio manager including EV parking lots for imbalance mitigation

Çiçek¹,

Erdinç²

2021

Turk J Elec Eng & Comp Sci

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In this study, an optimal bidding strategy for a wind energy portfolio manager (WEPM) including electric vehicle parking lots (EVPLs) that aims to maximize profits by trading in the day-ahead (DA) market and balancing market (BM) and through bilateral contracts, taking into account line capacities and risk management is proposed. The mentioned structure is modeled in Mixed-Integer Linear Programming (MILP) framework, and the uncertainties regarding electric vehicle (EV) behavior, electricity market data, wind power generation are captured via a stochastic approach. To demonstrate the effectiveness of the model, several case studies are carried out considering Sweden and Turkey electricity market prices with different risk aversion factors and bilateral contract situations. In this manner, the important results as well as useful findings regarding the economic impacts of the proposed concept are analyzed in detail.

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Scenario-Wise Distributionally Robust Optimization for Collaborative Intermittent Resources and Electric Vehicle Aggregator Bidding Strategy

Cited by 42 publications

References 34 publications

A Holistic Review on Advanced Bi-directional EV Charging Control Algorithms

A Holistic Review on Advanced Bi-directional EV Charging Control Algorithms

Data Consistency for Data-Driven Smart Energy Assessment

Risk-averse optimal bidding strategy for a wind energy portfolio manager including EV parking lots for imbalance mitigation

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