A hybrid storage-wind virtual power plant (VPP) participation in the electricity markets: A self-scheduling optimization considering price, renewable generation, and electric vehicles uncertainties

Alahyari, Arman; Ehsan, Mehdi; Mousavizadeh, MirSaeed

doi:10.1016/j.est.2019.100812

Cited by 96 publications

(43 citation statements)

References 33 publications

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“…The generators' minimum online/offline periods are considered by (3) and 4, and also upward/downward ramp rate limits are reflected by (5) and (6). Constraint 7calculates the total production of each generator, and generation limits are presented by (8) and (9). The hourly required reserves of generators in upward and downward are calculated by (10) and (11), while the corresponding upper bounds are limited by the ramp rates.…”

Section: E E En Nv VI Ir Ron Nm Men Ntal L I Issues S S Environmentalmentioning

confidence: 99%

Assessment of energy storage systems as a reserve provider in stochastic network constrained unit commitment

et al. 2021

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Recently, the provision of the reserve from energy storage systems (ESSs) is introduced as a source for ancillary services to address the uncertainties of renewable power generations. The performance of ESSs is analysed while they are applied as a provider of regulation reserves. It has been revealed that previous stochastic models neglect the impact of corrective dispatches, related to the provision of regulation reserves, on the energy level stored in the ESSs, which can lead to large deviations. This study coordinates the stored energy of ESSs to be feasible regarding the dispatches in the base schedule and rescheduling within scenarios. Also, the wind speed fluctuations are considered as the source of uncertainty, and scenarios of wind energy are generated using the Weibull distribution function. The IEEE 24-Bus standard test system is applied for the examination of the proposed model. The results show that the proposed model can manage the performance of ESSs in rescheduling within scenarios, while the coordinated reserve provision of ESSs can remove the concerns about insufficient stored energy of ESSs. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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Section: E E En Nv VI Ir Ron Nm Men Ntal L I Issues S S Environmentalmentioning

confidence: 99%

Assessment of energy storage systems as a reserve provider in stochastic network constrained unit commitment

et al. 2021

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“…However, [33,34] did not include BM, bilateral contracts, risk management, portfolio structure, and line capacities. Alahyari et al [35] suggested an approach for virtual power plants with a WPP and EVPL to participate in the DA market and reserve market. Moreover, it should be noted that BM, bilateral contracts, and line capacities were not considered in the mentioned study.…”

Section: Relevant Backgroundmentioning

confidence: 99%

“…(34) that the state-of-energy expression of EVs at each time period t is equal to the sum of the state-of-energy at the time (t − 1) and the energy charged at the time interval t and (t − 1) . The fact that the state-of-energy of EV batteries is equal to or less than the maximum allowed energy limits when charging batteries is ensured by (35)…”

Section: Armentioning

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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“…For the sake of reproducibility, detailed data for the test systems can be downloaded from [38]. Other necessary input data are reported in Table 1 where load shedding cost data is according to [39], wind curtailment is considered to be a small value in comparison with average electricity price as the wind generation belongs to VPP itself, and charging/discharging efficiencies are considered the same for all EVs [40]. Tests were run utilising general algebraic modelling system and Matlab software on a Xeon E5-2680 processor at 2.5 GHz and 128 GB of RAM.…”

Section: Numerical Studiesmentioning

confidence: 99%

Hybrid uncertainty‐based offering strategy for virtual power plants

Alahyari

Ehsan

Pozo

et al. 2020

IET Renewable Power Generation

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This study proposes an optimal day-ahead (DA) electricity market offering model for a virtual power plant (VPP) formed by a mix of renewable distributed energy resources along with energy storage, such as electric vehicles. Two sources of uncertainty are considered, namely, wind power generation, modelled by an uncertainty set, and DA market price, modelled by scenarios. Opposite to classical robust optimisation approaches, the authors model maps minimal (worst-case) profits to a conservativeness parameter, while the classical robust optimisation maps conservativeness parameter to worst-case profits. In this regard, by using their optimisation framework, a VPP operator only deals with setting a minimum-profit constraint, which is more sensible and easy for interpretation, while the required conservativeness is endogenously determined. The proposed mathematical model for constructing the offering curve is a hierarchical four-level robust optimisation problem. The first level represents the optimal decision on the price-quantity offer bids; the second-and third-level relate to the optimal identification of conservativeness parameter; and the fourth-level represents the optimal operation of the VPP managed assets. The four-level model is reformulated as a single-level mixed-integer linear programming problem. The proposed approach and its applicability are verified using numerical simulations.

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A hybrid storage-wind virtual power plant (VPP) participation in the electricity markets: A self-scheduling optimization considering price, renewable generation, and electric vehicles uncertainties

Cited by 96 publications

References 33 publications

Assessment of energy storage systems as a reserve provider in stochastic network constrained unit commitment

Assessment of energy storage systems as a reserve provider in stochastic network constrained unit commitment

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

Hybrid uncertainty‐based offering strategy for virtual power plants

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