J. Iori
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1
Batteries in hybrid power plants lose capacity at a rate that depends on how they are dispatched. Design studies often omit this coupling or represent it through energy throughput, which treats shallow and deep cycles alike. This thesis quantifies how accounting for cycle-based degradation changes the operation and sizing of a wind-battery plant at the IEA Wind Task 50 site in western Denmark, trading in the DK1 day-ahead market. Dispatch is solved as a linear program for each year of a 20-year horizon, with capacity updated annually and replacement at 70% state of health. Three approaches of increasing integration are examined: a parameter sweep, a single nonlinear program, and a nested architecture linked by a degradation sub-gradient. Calendar aging accounts for 53 to 54% of first-year degradation. Cycle amplitude produces the largest change in degradation but cannot be reduced without giving up revenue, whereas lowering the center of the state-of-charge window reduces degradation at no revenue cost. Accounting for degradation lowers the optimal storage size by about 30%, to near 550 MWh and 175 MW. The nonlinear program does not improve on the linear program, and it fails to converge on 48% of active days, which indicates that a smooth-gradient solver is not suited to a rainflow objective. The sub-gradient was implemented and verified at fixed dispatch; the outer loop remains open. Results are conditioned on one price year and perfect price foresight.
...
Batteries in hybrid power plants lose capacity at a rate that depends on how they are dispatched. Design studies often omit this coupling or represent it through energy throughput, which treats shallow and deep cycles alike. This thesis quantifies how accounting for cycle-based degradation changes the operation and sizing of a wind-battery plant at the IEA Wind Task 50 site in western Denmark, trading in the DK1 day-ahead market. Dispatch is solved as a linear program for each year of a 20-year horizon, with capacity updated annually and replacement at 70% state of health. Three approaches of increasing integration are examined: a parameter sweep, a single nonlinear program, and a nested architecture linked by a degradation sub-gradient. Calendar aging accounts for 53 to 54% of first-year degradation. Cycle amplitude produces the largest change in degradation but cannot be reduced without giving up revenue, whereas lowering the center of the state-of-charge window reduces degradation at no revenue cost. Accounting for degradation lowers the optimal storage size by about 30%, to near 550 MWh and 175 MW. The nonlinear program does not improve on the linear program, and it fails to converge on 48% of active days, which indicates that a smooth-gradient solver is not suited to a rainflow objective. The sub-gradient was implemented and verified at fixed dispatch; the outer loop remains open. Results are conditioned on one price year and perfect price foresight.
Forecast Uncertainty Propagation in Wind-Storage Hybrid Power Plant Dispatch
From wind forecast error to operational and economic performance
Hybrid power plants (HPPs) with storage can support renewable integration and capture electricity-market arbitrage revenue by shifting stored energy towards higher-value hours, but this flexibility depends on uncertain forecasts of future wind generation. This thesis investigates how wind-power forecast errors propagate into revenue losses in a wind–storage HPP operated with rolling-horizon dispatch. Forecast uncertainty is represented through a SARIMAX-based scenario ensemble fitted to historical wind-power output, and the uncertainty-induced losses are obtained by comparing forecast-based outcomes with a perfect-information benchmark across four one-week periods covering different wind regimes.
The results show a traceable propagation sequence: forecast errors change dispatch decisions, cause the battery SoC to diverge from its perfect-information trajectory, and become costly when the battery reaches a high-value or export-constrained period in the wrong state. Forecast error magnitude alone is therefore a poor predictor of revenue loss; errors are harmful mainly when they affect battery positioning before such critical events. Losses are concentrated in a small number of hours and are only partly recovered later. Four recurring mechanisms are identified, explaining how forecast errors create overcharged or undercharged battery states. In the studied weeks, undercharge mechanisms dominate, indicating that insufficient battery preparation before price peaks is the dominant loss mechanism. The thesis contributes a diagnostic framework for interpreting forecast uncertainty at the level of individual dispatch decisions, suggesting that forecast evaluation for storage operation should prioritise the timing and operational context of errors rather than average forecast accuracy alone. ...
The results show a traceable propagation sequence: forecast errors change dispatch decisions, cause the battery SoC to diverge from its perfect-information trajectory, and become costly when the battery reaches a high-value or export-constrained period in the wrong state. Forecast error magnitude alone is therefore a poor predictor of revenue loss; errors are harmful mainly when they affect battery positioning before such critical events. Losses are concentrated in a small number of hours and are only partly recovered later. Four recurring mechanisms are identified, explaining how forecast errors create overcharged or undercharged battery states. In the studied weeks, undercharge mechanisms dominate, indicating that insufficient battery preparation before price peaks is the dominant loss mechanism. The thesis contributes a diagnostic framework for interpreting forecast uncertainty at the level of individual dispatch decisions, suggesting that forecast evaluation for storage operation should prioritise the timing and operational context of errors rather than average forecast accuracy alone. ...
Hybrid power plants (HPPs) with storage can support renewable integration and capture electricity-market arbitrage revenue by shifting stored energy towards higher-value hours, but this flexibility depends on uncertain forecasts of future wind generation. This thesis investigates how wind-power forecast errors propagate into revenue losses in a wind–storage HPP operated with rolling-horizon dispatch. Forecast uncertainty is represented through a SARIMAX-based scenario ensemble fitted to historical wind-power output, and the uncertainty-induced losses are obtained by comparing forecast-based outcomes with a perfect-information benchmark across four one-week periods covering different wind regimes.
The results show a traceable propagation sequence: forecast errors change dispatch decisions, cause the battery SoC to diverge from its perfect-information trajectory, and become costly when the battery reaches a high-value or export-constrained period in the wrong state. Forecast error magnitude alone is therefore a poor predictor of revenue loss; errors are harmful mainly when they affect battery positioning before such critical events. Losses are concentrated in a small number of hours and are only partly recovered later. Four recurring mechanisms are identified, explaining how forecast errors create overcharged or undercharged battery states. In the studied weeks, undercharge mechanisms dominate, indicating that insufficient battery preparation before price peaks is the dominant loss mechanism. The thesis contributes a diagnostic framework for interpreting forecast uncertainty at the level of individual dispatch decisions, suggesting that forecast evaluation for storage operation should prioritise the timing and operational context of errors rather than average forecast accuracy alone.
The results show a traceable propagation sequence: forecast errors change dispatch decisions, cause the battery SoC to diverge from its perfect-information trajectory, and become costly when the battery reaches a high-value or export-constrained period in the wrong state. Forecast error magnitude alone is therefore a poor predictor of revenue loss; errors are harmful mainly when they affect battery positioning before such critical events. Losses are concentrated in a small number of hours and are only partly recovered later. Four recurring mechanisms are identified, explaining how forecast errors create overcharged or undercharged battery states. In the studied weeks, undercharge mechanisms dominate, indicating that insufficient battery preparation before price peaks is the dominant loss mechanism. The thesis contributes a diagnostic framework for interpreting forecast uncertainty at the level of individual dispatch decisions, suggesting that forecast evaluation for storage operation should prioritise the timing and operational context of errors rather than average forecast accuracy alone.
Powering Flexible Data Centers with Off-Grid Renewable Hybrid Power Plants
The Value of Demand-Side Flexibility through Workload Scheduling
Global data center demand is growing rapidly, but grid congestion can delay new projects for several years. Supplying data centers with on-site renewable generation offers a potential alternative, but the variability of wind and solar power makes it difficult to supply constant demand reliably. This thesis investigates whether an off-grid renewable hybrid power plant (HPP), combining wind, solar PV, and battery storage, can supply a data center reliably and cost-effectively when part of the demand is flexible.A case study is developed using a fixed HPP design, while varying the installed data center capacity and workload mix. Firm, daily flexible, weekly flexible, and opportunistic workloads are coupled to the HPP through an energy management system (EMS), which simulates renewable power use, battery operation, curtailment, and workload scheduling. Feasibility is assessed using a reliability target, while economic performance is evaluated using the levelized cost of electricity delivered (LCOED).Results show that firm load operation is technically possible, but inefficient. Since firm demand must be supplied continuously, only limited capacity can be served reliably. Flexible workloads improve this by shifting part of the demand to periods of higher wind and solar output. This increases useful energy delivery, reduces curtailment, and lowers the cost of delivered electricity. Overall, the results show that off-grid renewable data centers become more feasible when data center capacity and workload flexibility are designed around the variability of HPP power supply.
...
Global data center demand is growing rapidly, but grid congestion can delay new projects for several years. Supplying data centers with on-site renewable generation offers a potential alternative, but the variability of wind and solar power makes it difficult to supply constant demand reliably. This thesis investigates whether an off-grid renewable hybrid power plant (HPP), combining wind, solar PV, and battery storage, can supply a data center reliably and cost-effectively when part of the demand is flexible.
A case study is developed using a fixed HPP design, while varying the installed data center capacity and workload mix. Firm, daily flexible, weekly flexible, and opportunistic workloads are coupled to the HPP through an energy management system (EMS), which simulates renewable power use, battery operation, curtailment, and workload scheduling. Feasibility is assessed using a reliability target, while economic performance is evaluated using the levelized cost of electricity delivered (LCOED).
Results show that firm load operation is technically possible, but inefficient. Since firm demand must be supplied continuously, only limited capacity can be served reliably. Flexible workloads improve this by shifting part of the demand to periods of higher wind and solar output. This increases useful energy delivery, reduces curtailment, and lowers the cost of delivered electricity. Overall, the results show that off-grid renewable data centers become more feasible when data center capacity and workload flexibility are designed around the variability of HPP power supply.
High-speed Unmanned General-purpose Observatory (HUGO)
Reusable test platform for high-speed aeroelastic research
Bachelor thesis
(2026)
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A. Arends Martinez, V. Byreddy, G. Castro Lima da Silva, T. Čokonaj, P. Dimitrova, A. Gheorghiu, M. Gryszka, A. Janeček, H.M. Skrobanek, C.G.M. Vistisen, S. Giovani Pereira Castro, J. Iori, M. Radaelli
This report details the design, engineering, and commercial feasibility of the High-speed Unmanned General-purpose Observatory (HUGO), a 50 kg modular transonic flying laboratory. HUGO aims to address the gap between scale wind-tunnel testing and full-scale flight validation. Operating primarily at Mach 0.75, HUGO bypasses the wall-interference limitations of conventional transonic wind tunnels and the severe safety risks associated with manned flight testing. To meet its experimental objectives, the finalized airframe features a high-wing, T-tail configuration with a modular wing, canard and empennage ports and retractable steel landing gear. A defining feature of the platform is its customizable "Planform Envelope," which allows clients to interchange main wing configurations with aspect ratios ranging from 5 to 27, as well as various sweeps, chords and thickness profiles. To cost-effectively produce in low volumes, while maximizing structural efficiency, the airframe utilizes a composite monocoque structure capable of safely withstanding ultimate load factors of up to 9g. Propulsion is provided by twin fuselage-mounted JetCat P100-RX-BL micro-turbines, enabling HUGO to execute a 30-minute nominal mission that includes a five-minute Mach 0.75 test segment at FL270. Because high-fidelity data collection is the core value proposition of a flying laboratory, the aircraft is equipped with a comprehensive payload suite, including dual LIDAR wing deflection sensors, 16 surface-mounted strain gauges, and 6-axis load cells, to isolate and measure aerodynamic forces. Commercially, HUGO targets a €14.2 million Serviceable Obtainable Market within the Dutch wind tunnel testing ecosystem and is projected to operate profitably at a rate of €25,000 per flight day. Operations will be based out of Den Helder Airport under the EASA SC-Light-UAS High-risk classification, with regulatory compliance maintained through the simultaneous acquisition of a Type Certificate and Design Organisation Approval (DOA), which allows internal certification of modifications made to the aircraft on a per experiment basis.
...
This report details the design, engineering, and commercial feasibility of the High-speed Unmanned General-purpose Observatory (HUGO), a 50 kg modular transonic flying laboratory. HUGO aims to address the gap between scale wind-tunnel testing and full-scale flight validation. Operating primarily at Mach 0.75, HUGO bypasses the wall-interference limitations of conventional transonic wind tunnels and the severe safety risks associated with manned flight testing. To meet its experimental objectives, the finalized airframe features a high-wing, T-tail configuration with a modular wing, canard and empennage ports and retractable steel landing gear. A defining feature of the platform is its customizable "Planform Envelope," which allows clients to interchange main wing configurations with aspect ratios ranging from 5 to 27, as well as various sweeps, chords and thickness profiles. To cost-effectively produce in low volumes, while maximizing structural efficiency, the airframe utilizes a composite monocoque structure capable of safely withstanding ultimate load factors of up to 9g. Propulsion is provided by twin fuselage-mounted JetCat P100-RX-BL micro-turbines, enabling HUGO to execute a 30-minute nominal mission that includes a five-minute Mach 0.75 test segment at FL270. Because high-fidelity data collection is the core value proposition of a flying laboratory, the aircraft is equipped with a comprehensive payload suite, including dual LIDAR wing deflection sensors, 16 surface-mounted strain gauges, and 6-axis load cells, to isolate and measure aerodynamic forces. Commercially, HUGO targets a €14.2 million Serviceable Obtainable Market within the Dutch wind tunnel testing ecosystem and is projected to operate profitably at a rate of €25,000 per flight day. Operations will be based out of Den Helder Airport under the EASA SC-Light-UAS High-risk classification, with regulatory compliance maintained through the simultaneous acquisition of a Type Certificate and Design Organisation Approval (DOA), which allows internal certification of modifications made to the aircraft on a per experiment basis.
Comparing Storage Duration in Hybrid Power Plants
Multi-Market Participation of Wind Power with Li-Ion Batteries and Liquid Piston CAES Considering Degradation
Master thesis
(2026)
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W.L. Kastelein, M.B. Zaayer, J. Iori, A. Jarquin Laguna, Max Houwing, B.J. Klootwijk
Offshore wind is expected to become the largest energy source in the Netherlands. However, its economic viability has come under increasing pressure. Integrating energy storage with wind generation offers a potential solution by enhancing system flexibility and enabling additional revenues through multi-market participation. Hybrid Power Plants (HPPs) combine generation and storage technologies within a single system. This study investigates how the integration of short- and long-duration energy storage affects the profitability of wind-based HPPs operating across multiple electricity markets.
Short-duration lithium-ion (Li-ion) battery storage was compared with long-duration Liquid Piston Compressed Air Energy Storage (LPCAES). Lithium-ion batteries were evaluated while explicitly accounting for degradation, whereas LPCAES represents an emerging near-isothermal CAES technology with improved compression efficiency. Both technologies are evaluated across different energy capacities and charge/discharge rates within a multi-market framework, including participation in the day-ahead and automatic Frequency Restoration Reserve (aFRR) markets. Profitability is assessed using operational revenues and a Net Present Value analysis.
Results show that economic performance strongly depends on market conditions, storage sizing, degradation effects, and investment assumptions. Without degradation, Li-ion batteries generally outperform LPCAES in terms of profit due to higher efficiency and power capability. When degradation is considered, outcomes become year-dependent: LPCAES can achieve higher profitability under moderate price conditions and larger storage sizes, whereas Li-ion remains superior in high-price years. Overall, no single technology is universally optimal; the economically preferred option depends on the specific market environment and system configuration. ...
Short-duration lithium-ion (Li-ion) battery storage was compared with long-duration Liquid Piston Compressed Air Energy Storage (LPCAES). Lithium-ion batteries were evaluated while explicitly accounting for degradation, whereas LPCAES represents an emerging near-isothermal CAES technology with improved compression efficiency. Both technologies are evaluated across different energy capacities and charge/discharge rates within a multi-market framework, including participation in the day-ahead and automatic Frequency Restoration Reserve (aFRR) markets. Profitability is assessed using operational revenues and a Net Present Value analysis.
Results show that economic performance strongly depends on market conditions, storage sizing, degradation effects, and investment assumptions. Without degradation, Li-ion batteries generally outperform LPCAES in terms of profit due to higher efficiency and power capability. When degradation is considered, outcomes become year-dependent: LPCAES can achieve higher profitability under moderate price conditions and larger storage sizes, whereas Li-ion remains superior in high-price years. Overall, no single technology is universally optimal; the economically preferred option depends on the specific market environment and system configuration. ...
Offshore wind is expected to become the largest energy source in the Netherlands. However, its economic viability has come under increasing pressure. Integrating energy storage with wind generation offers a potential solution by enhancing system flexibility and enabling additional revenues through multi-market participation. Hybrid Power Plants (HPPs) combine generation and storage technologies within a single system. This study investigates how the integration of short- and long-duration energy storage affects the profitability of wind-based HPPs operating across multiple electricity markets.
Short-duration lithium-ion (Li-ion) battery storage was compared with long-duration Liquid Piston Compressed Air Energy Storage (LPCAES). Lithium-ion batteries were evaluated while explicitly accounting for degradation, whereas LPCAES represents an emerging near-isothermal CAES technology with improved compression efficiency. Both technologies are evaluated across different energy capacities and charge/discharge rates within a multi-market framework, including participation in the day-ahead and automatic Frequency Restoration Reserve (aFRR) markets. Profitability is assessed using operational revenues and a Net Present Value analysis.
Results show that economic performance strongly depends on market conditions, storage sizing, degradation effects, and investment assumptions. Without degradation, Li-ion batteries generally outperform LPCAES in terms of profit due to higher efficiency and power capability. When degradation is considered, outcomes become year-dependent: LPCAES can achieve higher profitability under moderate price conditions and larger storage sizes, whereas Li-ion remains superior in high-price years. Overall, no single technology is universally optimal; the economically preferred option depends on the specific market environment and system configuration.
Short-duration lithium-ion (Li-ion) battery storage was compared with long-duration Liquid Piston Compressed Air Energy Storage (LPCAES). Lithium-ion batteries were evaluated while explicitly accounting for degradation, whereas LPCAES represents an emerging near-isothermal CAES technology with improved compression efficiency. Both technologies are evaluated across different energy capacities and charge/discharge rates within a multi-market framework, including participation in the day-ahead and automatic Frequency Restoration Reserve (aFRR) markets. Profitability is assessed using operational revenues and a Net Present Value analysis.
Results show that economic performance strongly depends on market conditions, storage sizing, degradation effects, and investment assumptions. Without degradation, Li-ion batteries generally outperform LPCAES in terms of profit due to higher efficiency and power capability. When degradation is considered, outcomes become year-dependent: LPCAES can achieve higher profitability under moderate price conditions and larger storage sizes, whereas Li-ion remains superior in high-price years. Overall, no single technology is universally optimal; the economically preferred option depends on the specific market environment and system configuration.
Offshore wind projects require high upfront capital investment and have long payback periods. This makes revenue uncertainty a key issue for financing and investment decisions. Support mechanisms such as Contracts for Difference are widely used to reduce exposure to electricity price risk. However, conventional production based designs do not fully remove project level revenue variability or protect against downside financial risk, especially when electricity prices are volatile.
This thesis evaluates the financial risk mitigation performance of capability based Contracts for Difference for offshore wind projects. The analysis uses a project level cash flow perspective and compares capability based settlement with conventional support mechanisms and full merchant market exposure. A reference offshore wind project based on the IEA 740 MW offshore wind farm is applied consistently to the Dutch and Danish electricity markets under multiple electricity price scenarios.
The evaluation focuses on revenue stability, downside risk, bankability indicators, consumer outcomes, and price based basis risk. Monthly cash flow modelling is used to assess revenue volatility and tail risk. Alternative reference price constructions are also tested to examine how reference price design affects settlement outcomes and basis risk.
The results show that capability based settlement can significantly improve revenue stability and reduce downside risk relative to production based mechanisms. These effects are strongest in scenarios with lower average electricity prices and higher price volatility, where negative price periods and curtailment incentives occur more often. However, improved stability alone does not ensure project profitability or bankability. These outcomes remain mainly driven by the strike price level. Reference price construction plays a key role in shaping basis risk, while consumer outcomes depend strongly on strike price assumptions and market conditions.
Overall, this thesis provides quantitative evidence on the risk mitigation properties of capability based Contracts for Difference and clarifies the trade off involved. It shows why revenue stability, profitability, and bankability should be assessed separately when evaluating offshore wind support mechanisms. The findings highlight that settlement design, strike price calibration, and market context are critical for the performance of future support schemes. ...
This thesis evaluates the financial risk mitigation performance of capability based Contracts for Difference for offshore wind projects. The analysis uses a project level cash flow perspective and compares capability based settlement with conventional support mechanisms and full merchant market exposure. A reference offshore wind project based on the IEA 740 MW offshore wind farm is applied consistently to the Dutch and Danish electricity markets under multiple electricity price scenarios.
The evaluation focuses on revenue stability, downside risk, bankability indicators, consumer outcomes, and price based basis risk. Monthly cash flow modelling is used to assess revenue volatility and tail risk. Alternative reference price constructions are also tested to examine how reference price design affects settlement outcomes and basis risk.
The results show that capability based settlement can significantly improve revenue stability and reduce downside risk relative to production based mechanisms. These effects are strongest in scenarios with lower average electricity prices and higher price volatility, where negative price periods and curtailment incentives occur more often. However, improved stability alone does not ensure project profitability or bankability. These outcomes remain mainly driven by the strike price level. Reference price construction plays a key role in shaping basis risk, while consumer outcomes depend strongly on strike price assumptions and market conditions.
Overall, this thesis provides quantitative evidence on the risk mitigation properties of capability based Contracts for Difference and clarifies the trade off involved. It shows why revenue stability, profitability, and bankability should be assessed separately when evaluating offshore wind support mechanisms. The findings highlight that settlement design, strike price calibration, and market context are critical for the performance of future support schemes. ...
Offshore wind projects require high upfront capital investment and have long payback periods. This makes revenue uncertainty a key issue for financing and investment decisions. Support mechanisms such as Contracts for Difference are widely used to reduce exposure to electricity price risk. However, conventional production based designs do not fully remove project level revenue variability or protect against downside financial risk, especially when electricity prices are volatile.
This thesis evaluates the financial risk mitigation performance of capability based Contracts for Difference for offshore wind projects. The analysis uses a project level cash flow perspective and compares capability based settlement with conventional support mechanisms and full merchant market exposure. A reference offshore wind project based on the IEA 740 MW offshore wind farm is applied consistently to the Dutch and Danish electricity markets under multiple electricity price scenarios.
The evaluation focuses on revenue stability, downside risk, bankability indicators, consumer outcomes, and price based basis risk. Monthly cash flow modelling is used to assess revenue volatility and tail risk. Alternative reference price constructions are also tested to examine how reference price design affects settlement outcomes and basis risk.
The results show that capability based settlement can significantly improve revenue stability and reduce downside risk relative to production based mechanisms. These effects are strongest in scenarios with lower average electricity prices and higher price volatility, where negative price periods and curtailment incentives occur more often. However, improved stability alone does not ensure project profitability or bankability. These outcomes remain mainly driven by the strike price level. Reference price construction plays a key role in shaping basis risk, while consumer outcomes depend strongly on strike price assumptions and market conditions.
Overall, this thesis provides quantitative evidence on the risk mitigation properties of capability based Contracts for Difference and clarifies the trade off involved. It shows why revenue stability, profitability, and bankability should be assessed separately when evaluating offshore wind support mechanisms. The findings highlight that settlement design, strike price calibration, and market context are critical for the performance of future support schemes.
This thesis evaluates the financial risk mitigation performance of capability based Contracts for Difference for offshore wind projects. The analysis uses a project level cash flow perspective and compares capability based settlement with conventional support mechanisms and full merchant market exposure. A reference offshore wind project based on the IEA 740 MW offshore wind farm is applied consistently to the Dutch and Danish electricity markets under multiple electricity price scenarios.
The evaluation focuses on revenue stability, downside risk, bankability indicators, consumer outcomes, and price based basis risk. Monthly cash flow modelling is used to assess revenue volatility and tail risk. Alternative reference price constructions are also tested to examine how reference price design affects settlement outcomes and basis risk.
The results show that capability based settlement can significantly improve revenue stability and reduce downside risk relative to production based mechanisms. These effects are strongest in scenarios with lower average electricity prices and higher price volatility, where negative price periods and curtailment incentives occur more often. However, improved stability alone does not ensure project profitability or bankability. These outcomes remain mainly driven by the strike price level. Reference price construction plays a key role in shaping basis risk, while consumer outcomes depend strongly on strike price assumptions and market conditions.
Overall, this thesis provides quantitative evidence on the risk mitigation properties of capability based Contracts for Difference and clarifies the trade off involved. It shows why revenue stability, profitability, and bankability should be assessed separately when evaluating offshore wind support mechanisms. The findings highlight that settlement design, strike price calibration, and market context are critical for the performance of future support schemes.
Demand-Responsive Hybrid Power Plants
A techno-economic evaluation of hybrid power plant designs tailored to diverse demand profiles
Hybrid Power Plants (HPPs) combining wind, solar, and storage offer a promising solution to renewable variability. This thesis presents a techno-economic analysis using DTU’s HyDesign tool to quantify how demand–generation alignment, compared to baseload operation, influences reliability and costs. On the economic side, an indicative Power Purchase Agreement (PPA) valuation framework is introduced, tailored to demand-responsive HPPs and designed to capture operational risks and uncertainties. Results show that well-aligned demand profiles achieve high reliability at lower cost, while baseload operation drives overbuilding, curtailment, and higher PPA premiums. These findings position demand-responsive HPPs as a cost-effective alternative to baseload strategies.
...
Hybrid Power Plants (HPPs) combining wind, solar, and storage offer a promising solution to renewable variability. This thesis presents a techno-economic analysis using DTU’s HyDesign tool to quantify how demand–generation alignment, compared to baseload operation, influences reliability and costs. On the economic side, an indicative Power Purchase Agreement (PPA) valuation framework is introduced, tailored to demand-responsive HPPs and designed to capture operational risks and uncertainties. Results show that well-aligned demand profiles achieve high reliability at lower cost, while baseload operation drives overbuilding, curtailment, and higher PPA premiums. These findings position demand-responsive HPPs as a cost-effective alternative to baseload strategies.
Dispatch Optimization of Hybrid Power Plants for Short-Term Electricity Markets
A comparative analysis between stand-alone and co-located assets
The transition to a sustainable energy system has accelerated the integration of renewable energy sources (RES), such as wind and solar power, into electricity markets and infrastructures. While these sources contribute significantly to the decarbonization of the energy sector, their inherent variability and limited predictability introduce operational challenges for maintaining system balance and ensuring cost-effective grid utilization. Additionally, the geographic distribution of RES, often located in remote areas, has exacerbated issues of grid congestion, leading to limitations in grid access, rising curtailment levels, and deferred renewable projects. In response to these challenges, Hybrid Power Plants (HPPs), which co-locate RES with Battery Energy Storage Systems (BESS), have emerged as a viable solution offering increased operational flexibility, improved forecast error mitigation, and enhanced economic performance, while utilizing one grid connection point.
This study evaluates the added economic and energetic value of co-locating a BESS with a RES under the Dutch electricity market structure. A multi-stage stochastic optimization framework is developed to simulate HPP participation across the day-ahead, intraday, and imbalance markets. The model incorporates power forecast uncertainty through scenario generation and reduction techniques, and captures the physical constraints of energy systems, including battery operations and capacity, RES capacity, and restricted grid connection capacity. Optimization is conducted on a rolling horizon to reflect the sequential nature of market decision-making.
Three configurations are analyzed: a standalone RES system, a standalone BESS, and a co-located HPP. These systems are evaluated based on simulated operations over four weeks each representing a season using real market prices and wind power data. The co-located HPP demonstrates superior performance in terms of both economic return and renewable energy utilization. By enabling time-shifting of generation, reducing curtailment, and participating more effectively in short-term markets, the HPP captures additional value that standalone systems cannot access. Moreover, the ability to operate flexibly within a fixed grid export limit allows the HPP to relieve grid congestion, using storage to shift energy dispatch in line with the needs of the electricity system, indicated by price signals, thereby reducing strain on network infrastructure.
A comprehensive analysis investigates the impact of key assumptions regarding price and power forecasts and operational parameters, such as battery size, technology characteristics, grid connection capacity, and reoptimization frequency. Results indicate that system performance is highly dependent on the quality of imbalance price forecasts and the ability to respond dynamically to power forecast updates and market prices. This has been demonstrated by a comparison between no foresight, perfect foresight and using the day-ahead clearing price as imbalance forecast. Moreover, allowing the HPP to withdraw energy from the grid, results in signficant economic gains, however, this comes at the cost of renewable energy utilization. Although the study excludes capital and degradation costs, the findings underscore the operational advantages of co-locating RES and BESS under uncertainty and grid limitations.
Overall, this research contributes to a deeper understanding of how flexible, market-responsive HPPs can support the transition to a resilient and economically efficient low-carbon power system. It highlights the importance of integrated modeling approaches for optimizing renewable dispatch strategies in evolving electricity markets, while also demonstrating how HPPs can contribute to better utilizing grid connection capacity and enabling greater renewable integration.
...
This study evaluates the added economic and energetic value of co-locating a BESS with a RES under the Dutch electricity market structure. A multi-stage stochastic optimization framework is developed to simulate HPP participation across the day-ahead, intraday, and imbalance markets. The model incorporates power forecast uncertainty through scenario generation and reduction techniques, and captures the physical constraints of energy systems, including battery operations and capacity, RES capacity, and restricted grid connection capacity. Optimization is conducted on a rolling horizon to reflect the sequential nature of market decision-making.
Three configurations are analyzed: a standalone RES system, a standalone BESS, and a co-located HPP. These systems are evaluated based on simulated operations over four weeks each representing a season using real market prices and wind power data. The co-located HPP demonstrates superior performance in terms of both economic return and renewable energy utilization. By enabling time-shifting of generation, reducing curtailment, and participating more effectively in short-term markets, the HPP captures additional value that standalone systems cannot access. Moreover, the ability to operate flexibly within a fixed grid export limit allows the HPP to relieve grid congestion, using storage to shift energy dispatch in line with the needs of the electricity system, indicated by price signals, thereby reducing strain on network infrastructure.
A comprehensive analysis investigates the impact of key assumptions regarding price and power forecasts and operational parameters, such as battery size, technology characteristics, grid connection capacity, and reoptimization frequency. Results indicate that system performance is highly dependent on the quality of imbalance price forecasts and the ability to respond dynamically to power forecast updates and market prices. This has been demonstrated by a comparison between no foresight, perfect foresight and using the day-ahead clearing price as imbalance forecast. Moreover, allowing the HPP to withdraw energy from the grid, results in signficant economic gains, however, this comes at the cost of renewable energy utilization. Although the study excludes capital and degradation costs, the findings underscore the operational advantages of co-locating RES and BESS under uncertainty and grid limitations.
Overall, this research contributes to a deeper understanding of how flexible, market-responsive HPPs can support the transition to a resilient and economically efficient low-carbon power system. It highlights the importance of integrated modeling approaches for optimizing renewable dispatch strategies in evolving electricity markets, while also demonstrating how HPPs can contribute to better utilizing grid connection capacity and enabling greater renewable integration.
...
The transition to a sustainable energy system has accelerated the integration of renewable energy sources (RES), such as wind and solar power, into electricity markets and infrastructures. While these sources contribute significantly to the decarbonization of the energy sector, their inherent variability and limited predictability introduce operational challenges for maintaining system balance and ensuring cost-effective grid utilization. Additionally, the geographic distribution of RES, often located in remote areas, has exacerbated issues of grid congestion, leading to limitations in grid access, rising curtailment levels, and deferred renewable projects. In response to these challenges, Hybrid Power Plants (HPPs), which co-locate RES with Battery Energy Storage Systems (BESS), have emerged as a viable solution offering increased operational flexibility, improved forecast error mitigation, and enhanced economic performance, while utilizing one grid connection point.
This study evaluates the added economic and energetic value of co-locating a BESS with a RES under the Dutch electricity market structure. A multi-stage stochastic optimization framework is developed to simulate HPP participation across the day-ahead, intraday, and imbalance markets. The model incorporates power forecast uncertainty through scenario generation and reduction techniques, and captures the physical constraints of energy systems, including battery operations and capacity, RES capacity, and restricted grid connection capacity. Optimization is conducted on a rolling horizon to reflect the sequential nature of market decision-making.
Three configurations are analyzed: a standalone RES system, a standalone BESS, and a co-located HPP. These systems are evaluated based on simulated operations over four weeks each representing a season using real market prices and wind power data. The co-located HPP demonstrates superior performance in terms of both economic return and renewable energy utilization. By enabling time-shifting of generation, reducing curtailment, and participating more effectively in short-term markets, the HPP captures additional value that standalone systems cannot access. Moreover, the ability to operate flexibly within a fixed grid export limit allows the HPP to relieve grid congestion, using storage to shift energy dispatch in line with the needs of the electricity system, indicated by price signals, thereby reducing strain on network infrastructure.
A comprehensive analysis investigates the impact of key assumptions regarding price and power forecasts and operational parameters, such as battery size, technology characteristics, grid connection capacity, and reoptimization frequency. Results indicate that system performance is highly dependent on the quality of imbalance price forecasts and the ability to respond dynamically to power forecast updates and market prices. This has been demonstrated by a comparison between no foresight, perfect foresight and using the day-ahead clearing price as imbalance forecast. Moreover, allowing the HPP to withdraw energy from the grid, results in signficant economic gains, however, this comes at the cost of renewable energy utilization. Although the study excludes capital and degradation costs, the findings underscore the operational advantages of co-locating RES and BESS under uncertainty and grid limitations.
Overall, this research contributes to a deeper understanding of how flexible, market-responsive HPPs can support the transition to a resilient and economically efficient low-carbon power system. It highlights the importance of integrated modeling approaches for optimizing renewable dispatch strategies in evolving electricity markets, while also demonstrating how HPPs can contribute to better utilizing grid connection capacity and enabling greater renewable integration.
This study evaluates the added economic and energetic value of co-locating a BESS with a RES under the Dutch electricity market structure. A multi-stage stochastic optimization framework is developed to simulate HPP participation across the day-ahead, intraday, and imbalance markets. The model incorporates power forecast uncertainty through scenario generation and reduction techniques, and captures the physical constraints of energy systems, including battery operations and capacity, RES capacity, and restricted grid connection capacity. Optimization is conducted on a rolling horizon to reflect the sequential nature of market decision-making.
Three configurations are analyzed: a standalone RES system, a standalone BESS, and a co-located HPP. These systems are evaluated based on simulated operations over four weeks each representing a season using real market prices and wind power data. The co-located HPP demonstrates superior performance in terms of both economic return and renewable energy utilization. By enabling time-shifting of generation, reducing curtailment, and participating more effectively in short-term markets, the HPP captures additional value that standalone systems cannot access. Moreover, the ability to operate flexibly within a fixed grid export limit allows the HPP to relieve grid congestion, using storage to shift energy dispatch in line with the needs of the electricity system, indicated by price signals, thereby reducing strain on network infrastructure.
A comprehensive analysis investigates the impact of key assumptions regarding price and power forecasts and operational parameters, such as battery size, technology characteristics, grid connection capacity, and reoptimization frequency. Results indicate that system performance is highly dependent on the quality of imbalance price forecasts and the ability to respond dynamically to power forecast updates and market prices. This has been demonstrated by a comparison between no foresight, perfect foresight and using the day-ahead clearing price as imbalance forecast. Moreover, allowing the HPP to withdraw energy from the grid, results in signficant economic gains, however, this comes at the cost of renewable energy utilization. Although the study excludes capital and degradation costs, the findings underscore the operational advantages of co-locating RES and BESS under uncertainty and grid limitations.
Overall, this research contributes to a deeper understanding of how flexible, market-responsive HPPs can support the transition to a resilient and economically efficient low-carbon power system. It highlights the importance of integrated modeling approaches for optimizing renewable dispatch strategies in evolving electricity markets, while also demonstrating how HPPs can contribute to better utilizing grid connection capacity and enabling greater renewable integration.
market revenue rather than the conventional Annual Energy Production (AEP) objective affects technical and economic performance. Using historical hourly wind and day-ahead price data, wake and power models, and a layout optimization framework, the study compares layouts optimized for AEP with layouts optimized for expected revenue across several locations and three case studies.
Key findings show that revenue-optimized layouts deliver small but consistent improvements in projected revenues while keeping reasonable AEP performance. Site-dependent examples illustrate this trade-off: at one site, the revenue-optimized layout increases revenue by 0.22% while reducing AEP by 0.44%, and at another site, revenue increases by 0.20% with a negligible change in AEP (0.03%). Layouts optimized on an earlier period (2015–2020) retain performance when evaluated on later data (2022–2024), with objective-function losses remaining below 0.12%. Scenario experiments further show that long-term market structure predictions matter: changing the assumed correlation between wind speed and electricity prices in future scenarios can impact revenue substantially.
Overall, the study concludes that incorporating price information into layout optimization yields economic benefits and enhances robustness to realistic market variability. The results recommend that developers consider revenue-based objectives alongside traditional energy metrics when designing offshore wind farms operating in merchant electricity markets. ...
Key findings show that revenue-optimized layouts deliver small but consistent improvements in projected revenues while keeping reasonable AEP performance. Site-dependent examples illustrate this trade-off: at one site, the revenue-optimized layout increases revenue by 0.22% while reducing AEP by 0.44%, and at another site, revenue increases by 0.20% with a negligible change in AEP (0.03%). Layouts optimized on an earlier period (2015–2020) retain performance when evaluated on later data (2022–2024), with objective-function losses remaining below 0.12%. Scenario experiments further show that long-term market structure predictions matter: changing the assumed correlation between wind speed and electricity prices in future scenarios can impact revenue substantially.
Overall, the study concludes that incorporating price information into layout optimization yields economic benefits and enhances robustness to realistic market variability. The results recommend that developers consider revenue-based objectives alongside traditional energy metrics when designing offshore wind farms operating in merchant electricity markets. ...
market revenue rather than the conventional Annual Energy Production (AEP) objective affects technical and economic performance. Using historical hourly wind and day-ahead price data, wake and power models, and a layout optimization framework, the study compares layouts optimized for AEP with layouts optimized for expected revenue across several locations and three case studies.
Key findings show that revenue-optimized layouts deliver small but consistent improvements in projected revenues while keeping reasonable AEP performance. Site-dependent examples illustrate this trade-off: at one site, the revenue-optimized layout increases revenue by 0.22% while reducing AEP by 0.44%, and at another site, revenue increases by 0.20% with a negligible change in AEP (0.03%). Layouts optimized on an earlier period (2015–2020) retain performance when evaluated on later data (2022–2024), with objective-function losses remaining below 0.12%. Scenario experiments further show that long-term market structure predictions matter: changing the assumed correlation between wind speed and electricity prices in future scenarios can impact revenue substantially.
Overall, the study concludes that incorporating price information into layout optimization yields economic benefits and enhances robustness to realistic market variability. The results recommend that developers consider revenue-based objectives alongside traditional energy metrics when designing offshore wind farms operating in merchant electricity markets.
Key findings show that revenue-optimized layouts deliver small but consistent improvements in projected revenues while keeping reasonable AEP performance. Site-dependent examples illustrate this trade-off: at one site, the revenue-optimized layout increases revenue by 0.22% while reducing AEP by 0.44%, and at another site, revenue increases by 0.20% with a negligible change in AEP (0.03%). Layouts optimized on an earlier period (2015–2020) retain performance when evaluated on later data (2022–2024), with objective-function losses remaining below 0.12%. Scenario experiments further show that long-term market structure predictions matter: changing the assumed correlation between wind speed and electricity prices in future scenarios can impact revenue substantially.
Overall, the study concludes that incorporating price information into layout optimization yields economic benefits and enhances robustness to realistic market variability. The results recommend that developers consider revenue-based objectives alongside traditional energy metrics when designing offshore wind farms operating in merchant electricity markets.
This research evaluates the economic feasibility of adding offshore solar farms (OSFs) to planned offshore wind farms (OWFs) in Europe, identifying feasible ranges of OSF and subsidy levels to reach economic feasible projects. Ultimately, this leads to conditions to reach economically feasible projects for adding OSFs to OWFs. Using shared infrastructure, such as the power export infrastructure (PEI), it reduces the need for offshore grid expansion and lowers initial OSF investment costs. This study addresses a gap by examining the economic feasibility of this integration, specifically through an economic added value (EAV) analysis, combined with various OSF cost scenarios through a net present value (NPV) assessment.
First, a literature review explores the economic and technical benefits, focusing on shared OWF infrastructure and identifying relevant stakeholders, when adding an OSF. A techno-economic model is developed to calculate the economic added value based on increased OSF revenues and the added value subsidy (AVS), which reflects cost savings from using shared infrastructure. Subsequently, the model is applied to two OWF case studies, a wind farm site in the Netherlands and wind farm site in Italy, where economic feasibility is evaluated.
This study concludes that the addition of an OSF to an OWF at the Italian site is economically feasible, when an optimistic OSF cost scenario is used. With less optimistic OSF cost scenarios, the the addition of an OSF to an OWF would require higher AVS from increasing shared infrastructure costs to become feasible. The integration of OSFs shows greater economic potential in southern Europe, particularly in regions such as Italy, where abundant solar resources and a lower wind potential contribute to a higher EAV per unit of OSF capacity because of substantial growth of the PEI capacity factor. Locations with lower initial OWF capacity factors, greater increases in additional OSF capacity factors, and high shared infrastructure costs lead to faster NPV improvement and reduced dependence on subsidies, representing economically favourable conditions for adding OSFs to OWFs. ...
First, a literature review explores the economic and technical benefits, focusing on shared OWF infrastructure and identifying relevant stakeholders, when adding an OSF. A techno-economic model is developed to calculate the economic added value based on increased OSF revenues and the added value subsidy (AVS), which reflects cost savings from using shared infrastructure. Subsequently, the model is applied to two OWF case studies, a wind farm site in the Netherlands and wind farm site in Italy, where economic feasibility is evaluated.
This study concludes that the addition of an OSF to an OWF at the Italian site is economically feasible, when an optimistic OSF cost scenario is used. With less optimistic OSF cost scenarios, the the addition of an OSF to an OWF would require higher AVS from increasing shared infrastructure costs to become feasible. The integration of OSFs shows greater economic potential in southern Europe, particularly in regions such as Italy, where abundant solar resources and a lower wind potential contribute to a higher EAV per unit of OSF capacity because of substantial growth of the PEI capacity factor. Locations with lower initial OWF capacity factors, greater increases in additional OSF capacity factors, and high shared infrastructure costs lead to faster NPV improvement and reduced dependence on subsidies, representing economically favourable conditions for adding OSFs to OWFs. ...
This research evaluates the economic feasibility of adding offshore solar farms (OSFs) to planned offshore wind farms (OWFs) in Europe, identifying feasible ranges of OSF and subsidy levels to reach economic feasible projects. Ultimately, this leads to conditions to reach economically feasible projects for adding OSFs to OWFs. Using shared infrastructure, such as the power export infrastructure (PEI), it reduces the need for offshore grid expansion and lowers initial OSF investment costs. This study addresses a gap by examining the economic feasibility of this integration, specifically through an economic added value (EAV) analysis, combined with various OSF cost scenarios through a net present value (NPV) assessment.
First, a literature review explores the economic and technical benefits, focusing on shared OWF infrastructure and identifying relevant stakeholders, when adding an OSF. A techno-economic model is developed to calculate the economic added value based on increased OSF revenues and the added value subsidy (AVS), which reflects cost savings from using shared infrastructure. Subsequently, the model is applied to two OWF case studies, a wind farm site in the Netherlands and wind farm site in Italy, where economic feasibility is evaluated.
This study concludes that the addition of an OSF to an OWF at the Italian site is economically feasible, when an optimistic OSF cost scenario is used. With less optimistic OSF cost scenarios, the the addition of an OSF to an OWF would require higher AVS from increasing shared infrastructure costs to become feasible. The integration of OSFs shows greater economic potential in southern Europe, particularly in regions such as Italy, where abundant solar resources and a lower wind potential contribute to a higher EAV per unit of OSF capacity because of substantial growth of the PEI capacity factor. Locations with lower initial OWF capacity factors, greater increases in additional OSF capacity factors, and high shared infrastructure costs lead to faster NPV improvement and reduced dependence on subsidies, representing economically favourable conditions for adding OSFs to OWFs.
First, a literature review explores the economic and technical benefits, focusing on shared OWF infrastructure and identifying relevant stakeholders, when adding an OSF. A techno-economic model is developed to calculate the economic added value based on increased OSF revenues and the added value subsidy (AVS), which reflects cost savings from using shared infrastructure. Subsequently, the model is applied to two OWF case studies, a wind farm site in the Netherlands and wind farm site in Italy, where economic feasibility is evaluated.
This study concludes that the addition of an OSF to an OWF at the Italian site is economically feasible, when an optimistic OSF cost scenario is used. With less optimistic OSF cost scenarios, the the addition of an OSF to an OWF would require higher AVS from increasing shared infrastructure costs to become feasible. The integration of OSFs shows greater economic potential in southern Europe, particularly in regions such as Italy, where abundant solar resources and a lower wind potential contribute to a higher EAV per unit of OSF capacity because of substantial growth of the PEI capacity factor. Locations with lower initial OWF capacity factors, greater increases in additional OSF capacity factors, and high shared infrastructure costs lead to faster NPV improvement and reduced dependence on subsidies, representing economically favourable conditions for adding OSFs to OWFs.