Optimal Bidding Strategy for Offshore Wind Farms Equipped with Energy Storage in the Electricity Markets

Kordkheili, Ramin Ahmadi; Pourakbari‐Kasmaei, Mahdi; Lehtonen, Matti; Pouresmaeil, Edris

doi:10.1109/isgt-europe47291.2020.9248814

Cited by 5 publications

(5 citation statements)

References 10 publications

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“…The investments of WFO on the EES, P2H, and H2P facilities are limited by ( 2), (3), and (4), respectively. The quantity of electrical power that wind farms will commit to the day-ahead electricity market has an upper cap equal to the forecast of its generation, (5). The deviation between the real generation of the wind farm and the amount committed to the day-ahead electricity market defines the unbalance power, (6).…”

Section: B Problem Formulationmentioning

confidence: 99%

“…A risk analysis was performed in [4] to survey the investmentoperation decisions of wind producers and different assets participating in the energy markets. A stochastic method was implemented in [5] to model the uncertainties related to the wind and electricity markets, namely day-ahead and balancing, with the aim of alleviating deviations in renewable energy production. The focus of these papers was mainly on the electricity markets, and specifically, the balancing market showed as a fruitful tool to decrease the deviations of the WFO.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Wind Farm-based Green Hydrogen: A Virtual Power Plant Case Study

Kordkheili

Pourakbari‐Kasmaei

Lehtonen

et al. 2022

2022 18th International Conference on the European Energy Market (EEM)

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Decarbonization of the energy sector requires further wind farms for electricity generation. Green hydrogen can assist in many aspects, such as overcoming the uncertainty of wind generation. In this study, the concept of a virtual power plant (VPP), including a wind farm, electrical energy storage, powerto-hydrogen, hydrogen-to-power, and gas network, is investigated to exploit the full potential of wind farms. The gas network will play the role of virtual green hydrogen storage for the wind farm operator (WFO). The WFO interacts with two main electricity markets, namely the day-ahead electricity market, to sell the major share of production, and the balancing electricity market, to handle the deviations. The simulation results show the effectiveness of the proposed model in decreasing the deviations of WFOs to deliver the required electrical power committed to the electricity market, thus increasing their profit. Moreover, sensitivity analyses performed on the conversion ratio of the power-to-hydrogen show that the profit of WFO will increase with improvement in this parameter.

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Section: B Problem Formulationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Wind Farm-based Green Hydrogen: A Virtual Power Plant Case Study

Kordkheili

Pourakbari‐Kasmaei

Lehtonen

et al. 2022

2022 18th International Conference on the European Energy Market (EEM)

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“…The net present value coefficient for operation costs is hourly and can be calculated as 𝛼 𝑁𝑃𝑉,𝑂 =m(1+𝑚) 𝑛 /[((1+𝑚) 𝑛 -1)×D×H] where m is the annual discount rate considered 5%, n is the lifetime of the facility assumed to be 10 years, D is the number of days in the one year of planning, and H is the number of hours in a day. 𝛼 𝑁𝑃𝑉,𝐼 is the net present value coefficient for investment costs and considered yearly obtained by multiplying 𝛼 𝑁𝑃𝑉,𝑂 , D, and H. Table II present parameters of the wind farm, EES, gas storage, P2G and G2P facilities [27], [28].…”

Section: A Datamentioning

confidence: 99%

Multi-Alternative Operation-Planning Problem of Wind Farms Participating in Gas and Electricity Markets

et al. 2021

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By taking subsidies out of the picture, wind farm operators (WFO) face new challenges to participate in electricity markets. While conventional producers benefit from dispatchable generation, wind farms with stochastic nature have a challenging job to compete with these players in the market and need to come up with alternative solutions. To this end, energy storage has a great potential in managing the volatile generation and thereby increasing the profit of WFOs. Moreover, the gas market opens new opportunities to improve the flexibilities of WFOs in addressing the incurred penalties due to deviation between prediction and generation. For the sake of practicality, this paper proposes a joint operation-planning model. The WFO bids in both the day-ahead electricity market and gas market while also investing in alternative facilities, including electrical energy storage, gas storage, power-to-gas (P2G), and gas-to-power (G2P). The proposed framework is formulated as a mixed-integer nonlinear programming (MINLP) model. To guarantee to find the global solution, the original MINLP model is recast into a mixed-integer linear programming (MILP) model. Several case studies are defined to capture the potential of the proposed framework on the profit of the WFO, scrutinizing the performance of different facilities and interactions with the aforementioned markets. The modeling provides a tool for the WFOs for considering different alternative approaches to deal with the uncertainty of generation. This includes storing the wind farm surplus generation directly into electrical energy storage or by converting this surplus into gas via P2G and either storing it in gas storage or selling it in the gas market. Moreover, under the lack of generation condition, the electrical energy storage can provide electricity, or the gas from the gas market and gas storage can turn to electricity through G2P to assist WFOs. Results show the effectiveness of the proposed framework in enhancing the profitability of wind farms via different alternatives while highlighting the role of the gas market as a promising solution.INDEX TERMS Electricity market, electrical energy storage, gas storage, gas-to-power, gas market, operation and planning, power-to-gas, wind farm. NOMENCLATUREA. Indexes

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“…Kirli and Kiprakis [17] compare the technical cost and economic benefit of battery employment in dynamic frequency and balancing mechanism actions. In [18], a bidding strategy is proposed to address the challenges of offshore wind farm owners with energy storage participating in the electricity market, aiming to maximize their profits. The stochastic programming approach is used to deal with the uncertainties in output power and market prices.…”

Section: Introductionmentioning

confidence: 99%

Rolling‐horizon optimization strategy for wind‐storage system in electricity market

Chen,

Gao,

Ming

2024

IET Renewable Power Gen

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China's electricity spot market is undergoing rapid development. With the increasing integration of new energy sources, it has become imperative for new energy power plants to participate in the market actively. Simultaneously, new energy power facilities are equipped with energy storage to cope with the randomness of power generation. In order to address the optimization and control challenges of wind‐storage combined systems in the market environment, a charging and discharging strategy is proposed. Considering system parameters as variables, an online rolling‐horizon optimization model for wind‐storage systems is constructed to maximize revenue. Case studies demonstrate that this strategy effectively improves the overall revenue of wind power plants. After optimization, the return on investment (ROI) of the system increases by 2.29%. The selection of system parameters can significantly impact the outcomes. The optimal values of the capacity configuration and step size are 25 MWh and 45 min.

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Optimal Bidding Strategy for Offshore Wind Farms Equipped with Energy Storage in the Electricity Markets

Cited by 5 publications

References 10 publications

Wind Farm-based Green Hydrogen: A Virtual Power Plant Case Study

Wind Farm-based Green Hydrogen: A Virtual Power Plant Case Study

Multi-Alternative Operation-Planning Problem of Wind Farms Participating in Gas and Electricity Markets

Rolling‐horizon optimization strategy for wind‐storage system in electricity market

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