User-comfort oriented optimal bidding strategy of an electric vehicle aggregator in day-ahead and reserve markets

Şengör, İbrahim; Çiçek, Alper; Erenoğlu, Ayşe Kübra; Erdinç, Ozan; Catalão, João P.S.

doi:10.1016/j.ijepes.2020.106194

Cited by 35 publications

(11 citation statements)

References 29 publications

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“…The modelling framework accounts for the individual objectives of the three sets of the involved players, and is shown to be able to yield a participation rate of 99% in EV load management programs. Şengör et al [52] go further by characterising the uncertainties associated with the EV charging behaviours, while optimising the strategic bidding strategy of an aggregator participating in day-ahead and secondary control reserve markets. Zhong et al [53] have also put forward a coupon incentive-based DR scheme, where third-party load-serving entities participate in the wholesale DSM market and offer a flat incentive rate to the small-scale customers subscribed to them.…”

Section: Game-theoretic Models Applied To Demand-side Management Studiesmentioning

confidence: 99%

Modelling utility-aggregator-customer interactions in interruptible load programmes using non-cooperative game theory

Mohseni

Brent

Kelly

et al. 2021

International Journal of Electrical Power & Energy Systems

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Aggregator-activated demand response (DR) is widely recognised as a viable means for increasing the flexibility of renewable and sustainable energy systems (RSESs) necessary to accommodate a high penetration of variable renewables. To this end, by acting as DR aggregators and offering energy trading capabilities to smaller customers, energy retailers unlock additional sources of demand-side flexibility to ensure the cost-optimal operation of RSESs. Accordingly, a growing body of literature has highlighted the ways in which non-cooperative game theory could be used to reduce the gaps between modelled and real-world results for aggregator-mediated DR schemes. This paper aims to contribute to the trends of giving a realistic grounding to research on distributed DR-integrated energy scheduling by using insights from non-cooperative game theory to determine: (1) the optimal trade-off between importing electricity and utilising DR capacity in grid-tied RSESs, (2) the impact of the price elasticity of DR supply of different customer classes -especially, new sources of electricity demand, such as e-mobilityon the system-level dispatch of DR resources, and (3) the financial implications of harnessing the flexibility potential of a large number of end-consumers across different sectors. Accordingly, the principal goal of the paper is to develop an operational planning optimisation model that can be directly applied to real-world aggregatormediated, market-based demand-side flexibility provisioning domains. To this end, this paper presents the first DR elasticity-aware, non-cooperative game-theoretic DR scheduling model that: (1) yields the best compromise solution between imported power and dispatched DR resources from the utility's perspective, (2) characterises the utility-aggregator-customer interactions during the market-based DR trade process with several customer categories involved, and (3) disaggregates the total sectoral load on the system to individual end-consumers, which has potential implications for pre-feasibility and business case assessments. The application of the model to a conceptual micro-grid for the town of Ohakune, in New Zealand, demonstrates its effectiveness in reducing the daily system operational cost by ~66% and ~47% on a representative summer and winter day, respectively. Importantly, the paper provides statistically significant evidence supporting that activating the flexibility potential of small-to medium-scale end-consumers through specifically defined third-party aggregators in a market-based approach -that is aware of strategic interactions among instrumentally rational economic agents involved in the dispatch and delivery of DR resources -plays a significant role in the cost-optimal transition to 100%-renewable electricity generation systems within the smart grid paradigm.

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Section: Game-theoretic Models Applied To Demand-side Management Studiesmentioning

confidence: 99%

Modelling utility-aggregator-customer interactions in interruptible load programmes using non-cooperative game theory

Mohseni

Brent

Kelly

et al. 2021

International Journal of Electrical Power & Energy Systems

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“…In [24], the capacity of energy storage to provide grid services by participating in energy and reserve markets is explored. Reference [25] proposes a minimization model of cost for electric vehicle parking lot aggregator, which take into account user comfort and market uncertainty. Based on multi-stage stochastic programming, reference [26] proposes the bidding strategies for virtual power plants in day-ahead and intraday markets.…”

Section: B Literature Reviewmentioning

confidence: 99%

Market Impact of Wind-Energy Storage Alliance Strategic Bidding Under Uncertainty

Li¹,

Wang

Jin

2021

IEEE Access

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“…The possession of new energy vehicles is step by step increasing, [1] and human beings are demanding greater and greater performance from the automobiles. [2] The main power source of pure electric vehicles (PEVs) is the battery, [3] and frequent start-stop generates huge peak torque, [4,5] which affects battery life and driving range. [6,7] Hence, the wide variety of hybrid drives realized through including different structures to PEVs is increasing.…”

Section: Introduction 1research Motivationmentioning

confidence: 99%

Electrohydraulic Power Switching Control for Mechatronics–Electrohydraulic Power Coupling Electric Vehicles Considering Optimal Speed Thresholds

Yang

Zhang²,

Hong

2023

Energy Tech

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Switching between different working modes customarily brings sudden changes in torque and speed, leading to energy wastage for mechatronics‐electro‐hydraulic power coupling electric vehicles. Investigating the effect of vehicle speed thresholds on operating mode switching when working in concert with compound energy sources is timely. Thus, under the constraint of a known reference path, the optimal threshold is determined by weighing the path tracking accuracy and economic performance with the vehicle speed and the accumulator pressure as control variables. Wherein the constraint relationship between the factors is fully elucidated by combining various typical and actual road conditions. The validation results indicate a positive correlation between the starting acceleration capacity and the threshold value for a certain accumulator volume. The optimal speed thresholds under new European driving cycle, China light‐duty vehicle test cycle‐passenger, and actual routes are 4.1, 3.81, and 3.66 m s−1, with state of charge consumption rates of 6.30%, 8.56%, and 4.25%, respectively. More frequent speed switching may lead to excessive hydraulic power wastage, thereby increasing dependence on electrical power. Appropriate threshold setting can effectively enhance path tracking accuracy and hydraulic utilization under unpredictable road conditions. This research may in the future provide theoretical support for the rational control and interconstraint mechanism of energy utilization in hybrid vehicles.

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User-comfort oriented optimal bidding strategy of an electric vehicle aggregator in day-ahead and reserve markets

Cited by 35 publications

References 29 publications

Modelling utility-aggregator-customer interactions in interruptible load programmes using non-cooperative game theory

Modelling utility-aggregator-customer interactions in interruptible load programmes using non-cooperative game theory

Market Impact of Wind-Energy Storage Alliance Strategic Bidding Under Uncertainty

Electrohydraulic Power Switching Control for Mechatronics–Electrohydraulic Power Coupling Electric Vehicles Considering Optimal Speed Thresholds

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