Two-stage interval scheduling of virtual power plant in day-ahead and real-time markets considering compressed air energy storage wind turbine

Rahimi, Mahdi; Ardakani, Fatemeh Jahanbani; Olatujoye, Oluwaseyi; Ardakani, Ali Jahanbani

doi:10.1016/j.est.2021.103599

Cited by 29 publications

(3 citation statements)

References 39 publications

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“…China's first GPPCC industrialscale demonstration plant has been put into operation in Datang International Beijing Gaojing Thermal Power Plant successfully (Panah et al, 2020). Rahimi et al (2022) proposed a stochastic optimal dispatching model incorporating a carbon capture power plant. Budny et al (2015) proposed a coordinated model for peak shaving and valley filling through P2G and gas turbines.…”

Section: Literature Reviewmentioning

confidence: 99%

“…However, the proposed method can only be used for single-timescale uncertainty analysis. In reality, rural BECU-VPP scheduling is a multi-time-scale optimization problem, dispatching, and real-time deviation adjustment (Rahimi et al, 2022). Therefore, how to integrate the robust stochastic optimal methods into multi-timescale dispatching is a key issue.…”

Section: Literature Reviewmentioning

confidence: 99%

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Robust optimal dispatching model and a benefit allocation strategy for rural novel virtual power plants incorporating biomass waste energy conversion and carbon cycle utilization

Zhou

Pan

et al. 2023

Front. Energy Res.

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To optimize the utilization of rural biomass waste resources (e.g., straw and solid waste), biomass waste energy conversion (BWEC) and carbon cycle utilization (CCU) are integrated into a traditional virtual power plant, i.e., a rural BWEC-CCU-based virtual power plant. Furthermore, a fuzzy robust two-stage dispatching optimal model for the BWEC-CCU-based virtual power plant is established considering the non-determinacy from a wind power plant (WPP) and photovoltaic (PV) power. The scheduling model includes the day-ahead deterministic dispatching model and real-time uncertainty dispatching model. Among them, in the day-ahead dispatching phase, the dispatching plan is formulated with minimum operating cost and carbon emission targets. In the real-time dispatching phase, the optimal dispatching strategy is formulated aiming at minimum deviation adjustment cost by applying the Latin hypercube sampling method. The robust stochastic theory is used to describe the uncertainty. Third, in order to achieve optimal distribution of multi-agent cooperation benefits, a benefit distribution strategy based on Nash negotiation is designed considering the three-dimensional interfering factor of the marginal benefit contribution, carbon emission contribution, and deviation risk. Finally, a rural distribution network in Jiangsu province, China, is selected for case analysis, and the results show that 1) the synergistic optimal effect of BWEC and CCU is obvious, and the operation cost and deviation adjustment cost could decrease by 26.21% and 39.78%, respectively. While the capacity ratio of WPP + PV, BWEC, and CCU is 5:3:2, the dispatching scheme is optimum. 2) This scheduling model can be used to formulate the optimal scheduling scheme. Compared with the robust coefficient Γ = 0, when Γ = 1, the WPP and PV output decreased by 15.72% and 15.12%, and the output of BWEC and CCU increased by 30.7% and 188.19%, respectively. When Γ∈ (0.3, 0.9), the growth of Γ has the most direct impact on the dispatching scheme. 3) The proposed benefit equilibrium allocation strategy can formulate the most reasonable benefit allocation plan. Compared with the traditional benefit allocation strategy, when the proposed method is used, the benefit share of the WPP and PV reduces by 5.2%, and the benefit share of a small hydropower station, BWEC, and CCU increases by 1.7%, 9.7%, and 3.8%, respectively. Overall, the proposed optimal dispatching and benefit allocation strategy could improve the aggregated utilization of rural biomass waste resources and distributed energy resources while balancing the benefit appeal of different agents.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

Robust optimal dispatching model and a benefit allocation strategy for rural novel virtual power plants incorporating biomass waste energy conversion and carbon cycle utilization

Zhou

Pan

et al. 2023

Front. Energy Res.

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“…Furthermore, a proposal for the implementation of a small-scale CAES for energy storage purposes on a day-to-day basis in an active distribution system has been presented in Ghadi et al (2021). In addition, Rahimi et al (2022) discusses a virtual power plant that includes a thermal generator, solar PV panels, wind farm, energy storing device, and controllable loads in the real-time and day-ahead market. Finally, the author of Bhattarai et al (2019) elaborates on the usage and advantages of CAES in wind-integrated transmission-constrained systems, while Xie et al (2021) designed an optimization technique for the CAES system to minimize the uncertain constraints and to gain the bidding curve for contributing to the energy system.…”

Section: Introductionmentioning

confidence: 99%

Profit enhancement and grid frequency control by energy level scheduling of CAES system in wind-connected electrical system

Das,

Kumar

2023

Wind Engineering

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The maintenance of power balance poses significant challenges in renewable combined deregulated power systems due to the unpredictable nature of renewable energy sources. This situation leads to economic instability within the system. However, an energy storage system can help maintain energy supply and control system stability for renewable incorporated thermal power plants. Unlike in regulated markets, energy prices in deregulated markets are not fixed by any government body or particular company. Instead, the Independent System Operator (ISO) serves as the main entity in the electrical market, gathering tenders from Generation Companies (GENCOs), Distribution Companies (DISCOs), and Transmission Companies (TRANSCOs). The market controller regulates energy prices using Nodal Pricing (NP), which provides economic benefits to both GENCOs and DISCOs. However, the unpredictability of renewable sources often results in a decline in system profit due to the production of an imbalance price (CostIMC) caused by a mismatch in contracted power generation from the renewable power plant. To address these issues, this study proposes a novel combined system that utilizes a suitable scheduling technique for the optimum operation of a wind farm-compressed air energy storage (CAES) system to maximize profit and revenue while maintaining grid frequency. The CAES system’s energy level is divided into four different levels, and an optimal strategy has been developed to efficiently utilize the CAES system to maintain grid frequency. This work has been conducted in both regulated and deregulated environments using a modified IEEE 30-bus system. The proposed method has been compared with an existing approach and has yielded better results in all aspects.

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Trading Mechanism of Virtual Power Plants Participating in the Electricity Spot Market

Han

Wang

et al. 2023

Proceedings of the 7th PURPLE MOUNTAIN FORUM on Smart Grid Protection and Control (PMF2022)

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Two-stage interval scheduling of virtual power plant in day-ahead and real-time markets considering compressed air energy storage wind turbine

Cited by 29 publications

References 39 publications

Robust optimal dispatching model and a benefit allocation strategy for rural novel virtual power plants incorporating biomass waste energy conversion and carbon cycle utilization

Robust optimal dispatching model and a benefit allocation strategy for rural novel virtual power plants incorporating biomass waste energy conversion and carbon cycle utilization

Profit enhancement and grid frequency control by energy level scheduling of CAES system in wind-connected electrical system

Trading Mechanism of Virtual Power Plants Participating in the Electricity Spot Market

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