Hybrid Stochastic/Robust Offering Strategy for Coordinated Wind Power and Compressed Air Energy Storage in Multielectricity Markets

Nourollahi, Ramin; Mohammadi‐Ivatloo, Behnam; Zare, Kazem

doi:10.1109/jsyst.2020.3047672

Cited by 25 publications

(9 citation statements)

References 22 publications

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“…As mentioned, wind uncertainty is modeled by Weibull PDF (29). In (30), 𝑘 and 𝑐 are shape and scale indices, respectively.…”

Section: B Scenario Generation and Reduction Methodsmentioning

confidence: 99%

“…These works have used the stochastic method to model uncertain parameters. Reference [30] has presented an offering strategy for the participation of coordinated CAES and the WPP in different electricity markets considering uncertain parameters. Moreover, the work has modeled the uncertainty of DA price via a robust approach while it has used the stochastic method to model uncertainties related to intra-day and balancing market prices as well as wind power.…”

Section: B Literature Reviewmentioning

confidence: 99%

“…• References [27], [28], [30]- [32] have studied the participation of integrated WPP and CAES units in the electricity market and they have not considered solar energy. However, wind power and solar energy have complementary characteristics and joint bidding of these energy resources is more profitable.…”

Section: Novelties and Contributionsmentioning

confidence: 99%

“…The general mathematical model of robust optimization approach introduced by ( 37)-(42). According to the proposed model in [30], the minimization problem of a robust optimization can convert to a maximization problem. So for modeling price uncertainty using the robust optimization approach, the proposed stochastic based model in ( 1)-( 26) can be reformulate by ( 43…”

Section: Stochastic-robust Based Model Of Integrated Rpps and Caes Sy...mentioning

confidence: 99%

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Optimal Look-Ahead Strategic Bidding/Offering of Integrated Renewable Power Plants and CAES With Stochastic-Robust Approach

et al. 2022

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Today, due to the high penetration of renewable energy resources and restructuring of power systems, photovoltaic power plants (PVPPs) and wind power plants (WPPs) as renewable power plants (RPPs) can participate in the electricity markets. However, the intermittent power generation of RPPs may be challenging for the owners of these power plants. In order to mitigate the unpredictable and intermittent power generation of RPPs, energy storage systems like compressed air energy storage (CAES) can be an appropriate solution. In this paper, the optimal day-ahead and look-ahead strategic offering and bidding of integrated RPPs and CAES in the electricity market are investigated. Also, a stochastic-robust approach is proposed for modeling renewable generation and electricity price uncertainty. The proposed mixed-integer linear program (MILP) is formulated in GAMS software under the CPLEX solver. Three case studies are investigated to validate the proposed method. According to numerical results, in the optimistic strategy, the coordinator of RPPs and CAES has more opportunities to participate in the electricity market. But in This article has been accepted for publication in IEEE Access.

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“…As mentioned, wind uncertainty is modeled by Weibull PDF (29). In (30), 𝑘 and 𝑐 are shape and scale indices, respectively.…”

Section: B Scenario Generation and Reduction Methodsmentioning

confidence: 99%

Section: B Literature Reviewmentioning

confidence: 99%

Section: Novelties and Contributionsmentioning

confidence: 99%

Section: Stochastic-robust Based Model Of Integrated Rpps and Caes Sy...mentioning

confidence: 99%

See 2 more Smart Citations

Optimal Look-Ahead Strategic Bidding/Offering of Integrated Renewable Power Plants and CAES With Stochastic-Robust Approach

et al. 2022

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“…At present, the emergency material reserve mode of the headquarters of State Grid Corporation of The State Grid operator and all directly connected units are responsible for storing emergency energy in their territory, building their storage network, comprehensively coordinating emergency resources and ensuring emergency supply. The piece-by-piece standby model is the emergency equipment standby model implemented by the provincial network company, which is used to solve the early supply problem of emergency equipment in the region [13][14].…”

Section: Power Emergency Supplies Reservementioning

confidence: 99%

Construction of electric emergency materials storage system based on BP neural network

Song

Chen

Liu

et al. 2023

International Conference on Intelligent Systems, Communications, and Computer Networks (ISCCN 2023)

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The demand forecasting of power supply is an indispensable part of China's energy production and consumption. The scale of power grid construction in China has been expanding and the load growth rate has accelerated. Accidents, equipment failures and personnel unemployment often occur in the power system. BP neural network has certain algorithm advantages. Therefore, in order to ensure the safety and demand of residents and buildings, it is necessary to study the emergency materials storage system of power grid based on BP neural network. This paper mainly uses experimental testing and quantitative analysis methods to study the advantages and methods of BP neural network algorithm in the construction and application of electric emergency materials storage system. The experimental data shows that the learning rate of 0.06 selected by BP neural network is the most appropriate in the construction of storage system.

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Economic enhancement and grid‐frequency control of a wind farm‐CAES‐fuel cell‐based hybrid system

Das,

Kumar

2024

Energy Storage

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In the present era, the electrical network faces difficulty owing to the restricted supply of conventional energy resources. Solar and wind power are supremely acceptable renewable energy around the globe due to their cheap availability, zero fuel costs, and environmental safety features. Maintaining power balance in a renewable combined day‐ahead power network becomes challenging owing to the uncertainty of renewable sources, resulting in economic instability. An energy‐storing device is essential for combining renewable sources with existing thermal power plants to control the energy supply and maintain system stability. Any government agency in the deregulated market does not set up energy pricing. The ISO (independent system operator) is the primary organization in the day‐ahead power network that is responsible for collecting energy bids from DISCOs (distribution companies), TRANSCOs (transmission companies), and GENCOs (generation companies). The energy pricing is set by the market regulator at a rate known as Location‐based marginal pricing (LBMP), which provides benefits to GENCOs, and DISCOs as well as the customers. In a deregulated market, the unpredictability of renewable sources affects system profit owing to the creation of instability cost (ISC), induced by mismatching the bidding power production from the renewable plant. To lessen these concerns, the presented approach has proposed an innovative model that employs ideal scheduling of the WF (wind‐farm)‐CAES (compressed‐air‐energy‐storage)‐fuel cell (FC) hybrid systems to enhance system economic profitability while keeping the grid frequency (GF) in the safe zone. The fuel cell acts as the energy‐storing device that can be utilized during high‐demand times on the grid, with the ultimate goal of maximizing profits for the overall system. The CAES system's energy level is separated into four dissimilar points, and this study presents an optimum approach for efficiently using it to maintain grid frequency. The new strategy outperformed the previous methods in all categories. The study was performed using the IEEE 30 bus test system.

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Hybrid Stochastic/Robust Offering Strategy for Coordinated Wind Power and Compressed Air Energy Storage in Multielectricity Markets

Cited by 25 publications

References 22 publications

Optimal Look-Ahead Strategic Bidding/Offering of Integrated Renewable Power Plants and CAES With Stochastic-Robust Approach

Optimal Look-Ahead Strategic Bidding/Offering of Integrated Renewable Power Plants and CAES With Stochastic-Robust Approach

Construction of electric emergency materials storage system based on BP neural network

Economic enhancement and grid‐frequency control of a wind farm‐CAES‐fuel cell‐based hybrid system

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