Non‐linear hybrid approach for the scheduling of merchant underground pumped hydro energy storage

Toubeau, Jean‐François; Iassinovski, Sergei; Jean, Emmanuel; Parfait, Jean-Yves; Bottieau, Jérémie; Grève, Zacharie De; Vallée, François

doi:10.1049/iet-gtd.2019.0204

Cited by 10 publications

(8 citation statements)

References 35 publications

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“…The latter need to be in operation to provide reserves due to their minimum power level for ensuring the stability of the hydraulic machines. 40 Overall, these results highlight that sizing decisions can be driven by extreme scenarios, and depend thus on the risk-aversion of the investor.…”

Section: Robustness Of the Solutionmentioning

confidence: 83%

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Sizing of underwater gravity storage with solid weights participating in electricity markets

Toubeau

Ponsart

Stevens³

et al. 2020

Int Trans Electr Energ Syst

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This paper investigates the techno-economic feasibility of the innovative concept of gravity energy storage, where heavy weights are raised and lowered in a water environment. Such eco-friendly systems can be implemented in existing flooded pits or quarries, by leveraging the important depth of these cavities. Moreover, in addition to their long lifetime, they have no visual impact on the landscape, and offer a lot of flexibility to the power system. In this work, we firstly present an analytical study of the storage solution, which allows deriving tractable mathematical constraints describing its operation, such as its nonlinear speed-power curves in both charge and discharge modes. These constraints are then integrated into the investment strategy of a merchant unit that seeks to maximize its profit by jointly participating in the energy and secondary reserve markets. The model is formulated within a stochastic framework to ensure robustness of sizing decisions in view of future market uncertainties. Results from a practical case study (on a natural cavity of 200 m) show that underwater gravity storage is a cost-efficient technology that offers payback periods of less than 10 years, mainly due to its intrinsic low capital costs estimated at around 100 €/kWh. List of Symbols and Abbreviations: n blocks , Number of installed blocks; n gm , Number of installed geared induction machines; φ CAPEX , Total investment costs of the storage system, €; φ OPEX ω,t , Total profit from storage operation in scenario ω at time t, €; n blocks ω,t , Number of blocks stored within the storage system in scenario ω at time t; p dis,res ω,t , p ch,res ω,t , Actual output power in discharge (dis) and charge (ch) modes after the real-time activation of reserves in scenario ω at time t, MW; p dis ω,t , p ch ω,t , Output power in discharge (dis) and charge (ch) modes committed in the energy market in scenario ω at time t, MW; p single,Á,res ω,t , Output power per induction machine in discharge (dis) and charge (ch) modes after the real-time activation of reserves in scenario ω at time t, MW; res dis ω,t ,res ch ω,t , Reserve capacity allocated in the upward secondary reserve market in discharge (dis) and charge (ch) mode in scenario ω at time t, MW; v dis ω,t ,v ch ω,t , Aggregated block speed (at the UGES level) in discharge (dis) and charge (ch) mode in scenario ω at time t, m/s; v single,Á ω,t , Block speed per induction machine in discharge (dis) and charge (ch) mode in scenario ω at time t, m/s; z dis ω,t ,z ch ω,t , Binary variables indicating the discharge (dis) and charge (ch) status in scenario ω at time t; Δ t , Optimization step, 1 hour; η dis , η ch , Efficiency of the storage system in discharge (dis) and charge (ch) modes; κ ω,t ∈ [0,1], Activation rate of the upward reserve; λ act ω,t , Price for activation of balancing reserves in scenario ω at time t, €/MWh; λ EN ω,t , Electricity price in the energy-only market in scenario ω at time t, €/MWh; λ res ω,t , Price for availability of reserve capacity in scenario ω at time ...

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Section: Robustness Of the Solutionmentioning

confidence: 83%

“…This ability to offer upward reserve when the unit is at zero‐power (which occurs during most periods of the second day) is a strong advantage in comparison with pumped‐storage hydro units. The latter need to be in operation to provide reserves due to their minimum power level for ensuring the stability of the hydraulic machines 40 …”

Section: Case Studymentioning

confidence: 99%

Sizing of underwater gravity storage with solid weights participating in electricity markets

Toubeau

Ponsart

Stevens³

et al. 2020

Int Trans Electr Energ Syst

Self Cite

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“…Revenue from ancillary services for merchant-owned ES were considered in several studies for optimal scheduling [14]- [16]. One study included ancillary services for the scheduling of underground pumped hydro energy storage, considering the unique geometry and physical characteristics of the facility [14]. Another study scheduled ES for energy, reserve, and balancing with an objective to maximize profit [16].…”

Section: A Literature Reviewmentioning

confidence: 99%

Sizing Merchant Energy Storage for Maximum Revenues Considering Net Metering and Ancillary Services

Ma,

Venkatesh

2024

IEEE Access

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As prices for energy storage (ES) decline, merchant-owned ES units have an opportunity to be profitable if they earn revenue from multiple streams. Most papers in the literature provide a simplistic view, and do not capture practical tariff structure of commercial customers connected via load meters billed via netmetering scheme. In this paper, we present a flexible and comprehensive mathematical model to enable merchant-owned ES owners to maximize their profits by considering multiple revenue streams. The main contribution is a model that fully captures the economic picture by including displaced electricity costs, i.e., net-metering scheme, for behind-the-meter installations. It also includes operating costs, annual investment costs, and ES connected to the distribution system. The inclusion of net metering is novel, as well as simultaneously including all of ancillary services, energy costs, investment costs, net metering, and local generation. These elements can be crucial in building the business case for ES in Ontario to ensure profitability. We test our model on a large commercial customer. The load has a peak load of 1,500 kW and a solar generation capacity of 2,500 kW connected on a 13.8 kV feeder, with a limit of 5,000 kW capacity. The results show two cases. The first considers only energy arbitrage and costs $4,812,909, which is less than the cost without storage at $9,299,623. The second scenario allows for energy arbitrage and revenue via participation in local and bulk system ancillary services and yields a total benefit of $11,004,225. Both scenarios indicate benefits from purchase of storage. The second scenario is clearly more beneficial when storage investment is considered and opportunity is available. We also provide a stochastic implementation to consider uncertainty in any input parameter and demonstrate this method with energy prices.

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“…In our reference setting, we study a 250 MW -1200 MWh merchant storage unit competing in a power system inspired by the Belgian case [58]. The scheduling horizon is one day and the temporal resolution is one hour.…”

Section: Case Studymentioning

confidence: 99%

Data-Driven Scheduling of Energy Storage in Day-Ahead Energy and Reserve Markets With Probabilistic Guarantees on Real-Time Delivery

Toubeau

Bottieau

Greeve

et al. 2021

IEEE Trans. Power Syst.

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Energy storage systems (ESS) may provide the required flexibility to cost-effectively integrate weather-dependent renewable generation, in particular by offering operating reserves. However, since the real-time deployment of these services is uncertain, ensuring their availability requires merchant ESS to fully reserve the associated energy capacity in their day-ahead schedule. To improve such conservative policies, we propose a data-driven probabilistic characterization of the real-time balancing stage to inform the day-ahead scheduling problem of an ESS owner. This distributional information is used to enforce a tailored probabilistic guarantee on the availability of the scheduled reserve capacity via chance constrained programming, which allows a profit-maximizing participation in energy, reserve and balancing markets. The merit order-based competition with rival resources in reserve capacity and balancing markets is captured via a bi-level model, which is reformulated as a computationally efficient mixed-integer linear problem. Results show that a merchant ESS owner may leverage the competition effect to avoid violations of its energy capacity limits, and that the proposed risk-aware method allows sourcing more reserve capacity, and thus more value, from storage, without jeopardizing the real-time reliability of the power system. Index Terms-Chance-constrained programming, Data-driven optimization, Energy storage, Energy-operating reserve markets, Balancing markets. NOMENCLATUREA. Superscripts ch Charge mode of storage system. d Downward reserve. da Downward reserve activation. dis Discharge mode of storage system. u Upward reserve. ua Upward reserve activation. B. Sets and indices G Set of G conventional generators, index g. J Set of J demands, index j. L Set of L reserve activation levels, index l.

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Non‐linear hybrid approach for the scheduling of merchant underground pumped hydro energy storage

Cited by 10 publications

References 35 publications

Sizing of underwater gravity storage with solid weights participating in electricity markets

Sizing of underwater gravity storage with solid weights participating in electricity markets

Sizing Merchant Energy Storage for Maximum Revenues Considering Net Metering and Ancillary Services

Data-Driven Scheduling of Energy Storage in Day-Ahead Energy and Reserve Markets With Probabilistic Guarantees on Real-Time Delivery

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