An official website of the United States government
Abstract Green hydrogen produced using renewable electricity could play an important role in a clean energy future. This paper seeks to analyze the techno-economic performance of integrated wind and hydrogen systems under different conditions. A co-located wind and hydrogen hybrid system is optimized to reduce the total system cost. We have adopted and improved a state-of-the-art techno-economic tool REopt, developed by the National Renewable Energy Laboratory (NREL), for optimal planning of the integrate energy system (IES). In addition to wind and electrolyzer components, we have also considered battery energy storage, hydrogen tank, and hydrogen fuel cell in the IES. The results show that (i) adding electrolyzers to the grid-connected wind energy system could reduce the total system cost by approximately 8.9%, and (ii) adding electrolyzers, hydrogen tank, and hydrogen fuel cells could reduce the total system cost by approximately 30%.
more »
« less
Trade-offs between Battery Energy Storage and Hydrogen Storage in Off-Grid Green Hydrogen Systems
Green hydrogen, produced using renewables through electrolysis, can be used to reduce emissions in the hard-to-abate industrial sector. Efficient production and large-scale deployment require storage to mitigate electrolyzer degradation and ensure stable hydrogen supply. This paper explores the impacts and trade-offs of battery and hydrogen storage in off-grid wind-to-hydrogen systems, considering degradation of batteries and electrolyzers. Utilizing an optimization model, we examine system performance and costs over a wide range of storage capacities and wind profiles. Our results show that batteries smooth short-term fluctuations and minimize electrolyzer degradation but can experience significant degradation resulting from frequent charge/discharge cycles. Conversely, hydrogen storage provides long-term energy buffering, essential for sustained hydrogen production, but can increase electrolyzer cycling and degradation. Combining battery and hydrogen storage enhances system reliability, reduces component degradation, and reduces operational costs. This highlights the importance of strategic storage investments to improve the performance and costs of green hydrogen systems.
more »
« less
- Award ID(s):
- 1845093
- PAR ID:
- 10573588
- Publisher / Repository:
- Hawaii International Conference on System Sciences (HICSS)
- Date Published:
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
This paper presents a practical framework that integrates wind speed forecasting with proton exchange membrane (PEM) electrolyzer design to optimize hydrogen production. Due to wind speed fluctuations, excess electrical energy is sometimes produced and left unused. A wind-to-hydrogen system addresses this challenge by converting surplus energy into storable hydrogen using a PEM electrolyzer. The proposed approach employs a multivariate supervisory control and data acquisition (SCADA) dataset and applies a convolutional neural network with bi-directional long short-term memory (CNN-Bi-LSTM) for multivariate wind speed temporal forecasting, enabling more efficient PEM operations. Compared to standard deep learning models, the CNN-Bi-LSTM architecture reduces the root mean square error by 52.5% and the mean absolute error by 56%, thereby enhancing hydrogen production forecasting. Simulation results show that a membrane thickness of 0.0252 mm and an operating temperature of 70% achieve the highest overall PEM efficiency of 63.611%. This study demonstrates the integration of deep learning-based forecasting with electrochemical modeling and SCADA datasets as a novel approach for wind-to-hydrogen production systems.more » « less
-
Abstract The transition to carbon-neutral energy has increased the reliance upon renewable sources of energy, e.g., wind power, placing added demands on resilience and stability of the power grid. Wind-to-hydrogen production systems can be a solution for addressing these demands. By converting excess wind energy into hydrogen via electrolysis, these systems can effectively store the intermittent energy generated by wind turbines. This study discusses the application of two time-series prediction models, i.e., long short-term memory (LSTM) and bidirectional long short-term memory (Bi-LSTM), in forecasting the energy of wind farms, subsequently used for an assessment of hydrogen production means of a proton exchange membrane (PEM) electrolyzer. Using a dataset comprising wind speed, active power, and wind direction, inputs were normalized, and wind direction was transformed into sine and cosine components to retain circular characteristics. Bi-LSTM demonstrated superior accuracy with lower testing RMSE than LSTM. Integrating wind forecasts with a PEM electrolyzer model, incorporating critical electro-chemical parameters, revealed an optimal efficiency of 63.611% at a membrane thickness of 0.00254 cm and a temperature of 70°C. Bi-LSTM forecasts boosted hydrogen production by 5% to 8% compared to LSTM.more » « less
-
Abstract This article presents a comprehensive study that focuses on the techno-economic analysis of co-located wind and hydrogen energy integration within an integrated energy system (IES). The research investigates four distinct cases, each exploring various configurations of wind farms, electrolyzers, batteries, hydrogen storage tanks, and fuel cells. To obtain optimal results, the study employs a sophisticated mathematical optimization model formulated as a mixed-integer linear program. This model helps determine the most suitable component sizes and hourly energy scheduling patterns. The research utilizes historical meteorological data and wholesale market prices from diverse regions as inputs, enhancing the study’s applicability and relevance across different geographical locations. Moreover, sensitivity analyses are conducted to assess the impact of hydrogen prices, regional wind profiles, and potential future fluctuations in component prices. These analyses provide valuable insights into the robustness and flexibility of the proposed IES configurations under varying market conditions and uncertainties. The findings reveal cost-effective system configurations, strategic component selections, and implications of future energy scenarios. Specifically comparing to configurations that only have wind and battery combinations, we find that incorporating an electrolyzer results in a 7% reduction in the total cost of the IES, and utilizing hydrogen as the storage medium for fuel cells leads to a 26% cost reduction. Additionally, the IES with hybrid hydrogen and battery energy storage achieves even higher and stable power output. This research facilitates decision-making, risk mitigation, and optimized investment strategies, fostering sustainable planning for a resilient and environmentally friendly energy future.more » « less
-
With increasing concerns about climate change, there is a transition from high-carbon-emitting fuels to green energy resources in various applications including household, commercial, transportation, and electric grid applications. Even though renewable energy resources are receiving traction for being carbon-neutral, their availability is intermittent. To address this issue to achieve extensive application, the integration of energy storage systems in conjunction with these resources is becoming a recommended practice. Additionally, in the transportation sector, the increased demand for EVs requires the development of energy storage systems that can deliver energy for rigorous driving cycles, with lithium-ion-based batteries emerging as the superior choice for energy storage due to their high power and energy densities, length of their life cycle, low self-discharge rates, and reasonable cost. As a result, battery energy storage systems (BESSs) are becoming a primary energy storage system. The high-performance demand on these BESS can have severe negative effects on their internal operations such as heating and catching on fire when operating in overcharge or undercharge states. Reduced efficiency and poor charge storage result in the battery operating at higher temperatures. To mitigate early battery degradation, battery management systems (BMSs) have been devised to enhance battery life and ensure normal operation under safe operating conditions. Some BMSs are capable of determining precise state estimations to ensure safe battery operation and reduce hazards. Precise estimation of battery health is computed by evaluating several metrics and is a central factor in effective battery management systems. In this scenario, the accurate estimation of the health indicators (HIs) of the battery becomes even more important within the framework of a BMS. This paper provides a comprehensive review and discussion of battery management systems and different health indicators for BESSs, with suitable classification based on key characteristics.more » « less
- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Conference Proceeding:
- The DOI is not currently available.
