Variable Renewable Energy Sources Research Articles

The Potential for the Use of Hydrogen Storage in Energy Cooperatives

According to the European Hydrogen Strategy, hydrogen will solve many of the problems with energy storage for balancing variable renewable energy sources (RES) supply and demand. At the same time, we can see increasing popularity of the so-called energy communities (e.g., cooperatives) which (i) enable groups of entities to invest in, manage, and benefit from shared RES energy infrastructure; (ii) are expected to increase the energy independence of local communities from large energy corporations and increase the share of RES. Analyses were conducted on 2000 randomly selected energy cooperatives and four energy cooperatives formed on the basis of actual data. The hypotheses assumed in the research and positively verified in this paper are as follows: (i) there is a relationship between hydrogen storage capacity and the power of RES, which allows an energy community to build energy independence; (ii) the type of RES generating source is meaningful when optimizing hydrogen storage capacity. The paper proves it is possible to build “island energy independence” at the local level using hydrogen storage and the efficiency of the power-to-power chain. The results presented are based on simulations carried out using a dedicated optimization model implemented by mixed integer programming. The authors’ next research projects will focus on optimizing capital expenditures and operating costs using the Levelized Cost of Electricity and Levelized Cost of Hydrogen methodologies.

Enhanced composite controller for PV/PMSG/PEMFC and BESS‐based DC microgrids voltage regulation: Integrating integral terminal sliding mode controller and recursive backstepping controller

AbstractThe variability of renewable energy sources due to weather patterns often leads to a mismatch between power generation and consumption within microgrids (MGs). This challenge is exacerbated when integrating bio‐renewable units, complicating stability maintenance in MGs. This research work introduces a novel solution to address this issue: a composite controller merging an integral terminal sliding mode controller with a recursive backstepping controller for direct current MGs (DCMGs). The proposed DCMG incorporates solar photovoltaic units, wind farms based on permanent magnet synchronous generators, proton exchange membrane fuel cells fuelled by hydrogen gas, an electrolyser, battery energy storage systems, and DC loads. First, a comprehensive mathematical model for the components within the DCMG is developed to design the proposed composite controller. This controller not only overcomes the inherent limitations and convergence issues of conventional SMCs but also ensures stable DC‐bus voltage and maintains power balance across various operational conditions. Moreover, a fuzzy logic‐based energy management system is introduced to regulate power flow, considering factors like battery state of charge and renewable energy sources' total power output. The control Lyapunov function confirms the DCMG system's asymptotic stability. Finally, the proposed controller's effectiveness is validated through simulations on both MATLAB/Simulink and Arduino Mega 2650 processor‐in‐the‐loop platforms under various operational conditions. In both platforms, the proposed controller surpasses an existing controller in terms of settling time, overshoot, and tracking error of the DC‐bus voltage.

Optimization of renewable energy-based integrated energy systems: A three-stage stochastic robust model

The integration of renewable energy into an integrated energy system (REIES) represents a promising approach to achieving clean and low-carbon energy consumption. However, the inherent uncertainty and variability of renewable energy sources and load demands present significant challenges to the operational efficiency and stability of REIES. To address these challenges, we propose a three-stage stochastic robust optimization (TRSRO) model. This model accounts for market electricity prices, source-load scenario probabilities, and output uncertainties to optimize system configurations in REIES. It also includes the optimization of power exchanges with the regional grid and strategic operational scheduling. Initial scenarios of uncertainty variables are generated using the spectral normalized conditional Wasserstein generative adversarial network (SNCWGAN), forming polyhedral uncertainty sets. Comprehensive norm constraints are then applied to capture probability distribution uncertainties within these sets. To improve the efficiency of solving the model, we introduce a two-layer column constraint generation algorithm, considering variable alternate iterations (TLCCG-VAI). The results demonstrate that the proposed method can achieve a 12.16 % reduction in total cost compared to the baseline method. Furthermore, the TLCCG-VAI algorithm reduces runtime by 82.97 % while maintaining the same level of solution accuracy.

Additional revenues estimation in a market-based redispatch: An opportunity for flexibility

The technical constraints in the transmission networks are exerting significant strain on the functioning of electricity markets as the share of variable renewable energy sources is increasing. To manage this issue, the transition to a nodal pricing market has been proposed in the literature. Given that the current structure of the European Union electricity market corresponds to a zonal pricing, the transition to nodal pricing would imply fundamental changes in its market structure. In order to avoid the latter, this study develops a method to identify locational price signals in a decentralized market with zonal pricing and subsequent market-based redispatch. To this end, first, nodes with structural technical constraints are identified –using energy programmes–. Then, the additional revenues of physical units located at these nodes are estimated –using electricity prices–. Finally, this strategic information will guide the development of flexibility solutions –manageable generation capacity and demand response– in these geographic locations, mimicking the main advantage of nodal pricing. Our methodology has been empirically tested on the Spanish power system, using hourly data from the System Operator and Market Operator for four full years, from 2019 to 2022. The results show a higher and constant economic revenue in certain nodes of this system –upward redispatch price is 74.90% higher than day-ahead market price–. Thus, this method can be used by market participants to evaluate publicly available data from a decentralized market with zonal pricing and subsequent market-based redispatch, and obtain essential information to make the best investment decisions.

Robust [formula omitted] control for LFC of discrete T–S fuzzy MAPS with DFIG and time-varying delays

The H∞ LFC control problem for a class of nonlinear power systems with time-varying delays is under study. Considering uncertainties arising from nonlinear issues such as the generation rate constraint (GRC) and governor dead band (GDB), as well as the high variability of renewable energy sources like wind power, the model is transformed into a discrete-time Takagi–Sugeno (T–S) fuzzy model with parameter uncertainty. By constructing a Lyapunov–Krasovskii functional, and employing difference inequalities and generalized cross-convex matrix inequalities, sufficient conditions for the asymptotic stability of power systems are provided. Based on the obtained conditions, a controller is designed to ensure the asymptotic stability of Multi-Area Power Systems (MAPS), with the performance index being H∞. Finally, simulation results demonstrate the correctness and effectiveness of the theorem.

Toward Methanol Production by CO2 Hydrogenation beyond Formic Acid Formation.

ConspectusThe Paradigm shift in considering CO2 as an alternative carbon feedstock as opposed to a waste product has recently prompted intense research activities. The implementation of CO2 utilization may be achieved by designing highly efficient catalysts, exploring processes that minimize energy consumption and simplifying product purification and separation. Among possible target products derived from CO2, methanol is highly valuable because it can be used in various chemical feedstocks and as a fuel. Although it is currently produced on a plant scale by heterogeneous catalysis using a Cu/ZnO-based catalyst, a limited theoretical conversion ratio at high reaction temperatures remains an issue. In addition, a catalytic system that can be adjusted to accommodate a variable renewable energy source for the synthesis of methanol is more desirable than current continuous-operation systems, which require a reliable energy supply. Recently, significant progress has been made in the field of homogeneous catalysis, which primarily relies on an indirect route to synthesize methanol via the hydrogenation of carbonate or formate derivatives in the presence of additives and solvents. However, homogeneous catalysis is inappropriate for industrial-scale methanol production because of the inefficient separation and purification processes involved.In this Account, we demonstrate a novel approach for methanol production under mild reaction conditions by CO2 hydrogenation catalyzed by multinuclear iridium complexes under heterogeneous gas-solid phase conditions without any additives and solvents. One of the aims of this Account provides insights for overcoming the barriers for efficient CO2 hydrogenation by focusing on catalyst design, specifically by incorporating varying functionalities into the ligand. The fundamental strategy entails activating hydrogen molecule and enhancing the hydricity of the resulting metal-hydride species, which is based on the following two concepts of catalyst design: (i) Activating a metal-hydride by electronic effects; and (ii) accelerating H2 heterolysis. We have elucidated the mechanism for accelerating H2 heterolysis using a state-of-the-art catalyst that contains an actor-ligand that responds to or participates in catalysis as opposed to a classical spectator-ligand.We have also demonstrated a novel heterogeneous catalysis using a molecular catalyst as a key step for the hydrogenation of CO2 to methanol beyond formic acid formation. The dehydrogenation of formic acid as a reverse reaction of formic acid hydrogenation is strongly favored in acidic aqueous solution. To circumvent the equilibrium limitation, we have envisioned an alternative route that both prevents the liberation of formic acid into the reaction medium, and develops a multinuclear complex to facilitate the transfer of multiple reactive hydrides. The unconventional gas-solid phase catalysis is capable of preventing the liberation of formate species and promoting further hydrogenation of formic acid through multihydride transfer.This novel catalytic system, which is the fusion of a molecular catalyst in heterogeneous catalysis, provides high performance for methanol synthesis through a sophisticated catalyst design and straightforward separation processes. A detailed mechanistic analysis of molecular catalysts in the gas phase would lead to significant progress in the field of Surface Organometallic Chemistry (SOMC).

Dynamic model of integrated electricity and district heating for remote communities

District heating networks offer promising solutions for remote communities, providing centralized heat supply, improved efficiency, and diverse energy sources, especially with existing diesel generation. Hence, this paper bridges gaps in the existing literature by developing comprehensive dynamic models of combined district heating networks within existing electric power networks in remote communities, which allows identifying challenges and benefits of district heating networks for these communities. It is shown that district heating networks allow utilizing waste energy to enable energy exchanges between the electricity and heating systems, enabling the provision of necessary ancillary services for remote microgrids with renewable energy sources. The presented dynamic district heating network model incorporates particular considerations in remote, northern communities such as soil limitations, extreme cold conditions, and piping insulation to minimize heat loss. It also addresses accurate sizing of heat pumps based on realistic thermal load requirements, weather conditions, and consumer profiles, proposing demand management controls to enhance frequency regulation for the integration of variable renewable energy sources. The main contributions of the paper include detailed dynamic modeling for district heating network operation, heat pump demand response control system design, and a comparative analysis between centralized district heating networks and decentralized electric thermal storage units that have been deployed for thermal supply in remote areas. The presented dynamic models are applied, tested, and validated in an existing electric microgrid at Kasabonika Lake First Nation in Northern Ontario, showcasing the role of a potential district heating network in facilitating renewable energy sources integration in isolated microgrids.

Electric vehicle aggregator as demand dispatch resources: Exploring the impact of real-time market performance on day-ahead market

As the integration of variable renewable energy sources (VREs) into power grids escalates, effectively managing the unpredictability of VRE generation becomes crucial. Electric vehicles, utilized as distributed energy storage, emerge as a potential solution. However, it remains unclear whether electric vehicle aggregators (EVAs), acting as demand dispatch resources, have a favorable impact on the overall electricity market, especially when considering their performance in real-time markets during day-ahead energy allocations. Therefore, this paper proposes a decentralized clearing mechanism (DCM) relying on an multi-attribute evaluation model of EVAs for optimal bidding strategies in the day-ahead market. The EVAs multi-attribute evaluation model employs an integration of the Entropy-Analytic Hierarchy Process, allowing for the simultaneous consideration of real-time performance and day-ahead bidding prices of EVAs. Consequently, the decentralized clearing mechanism supports strategic electricity planning in the day-ahead market by incorporating the actual market performance of EVAs. Furthermore, a real-time market bidding model is developed to balance dynamic mismatches between VRE generation and demand, aiming to maximize profits through optimized real-time commitment and real-time dispatch. System simulations on the IEEE39 bus system demonstrate that the DCM enhances overall profits by 18.69% compared to the centralized clearing mechanism.

Modelling long-term operational dynamics of grid-connected hydro- photovoltaic hybrid systems

The development of variable renewable energy sources (VRESs), such as wind and solar photovoltaic (PV), has become a strategic choice for ensuring the security of electricity supplies and the decarbonization of power systems. The hybridization of hydropower with VRESs is an important measure for guaranteeing the smooth and cost-effective integration of VRESs into the power system. However, the highly variable weather- and climate-driven spatial and temporal fluctuations in VRES performance have significant potential to affect the optimal trajectory of hydropower operations. Therefore, it is essential to understand how hydropower responds to VRESs over long-term horizons, thereby allowing informed operation decisions to be made for hybrid generation systems (HGSs). In this study, a long- and short-term nested operation model is developed for hydropower operations considering PV integration. Specifically, the long-term model determines the day-by-day hydropower production over many years, and the short-term model simulates the day-ahead generation scheduling and real-time operation processes of the HGS. Performance metrics are established for evaluating the complementary operation in comparison with separate operation of hydropower and PV plants. China's two representative hydro-PV HGSs (Zhongyu and Longyangxia) are selected as case studies. The results indicate that the hybrid generation of hydropower and PV could, on average, increase total electricity generation by 11.33 %, reduce the load loss rate by 9.31 %, and decrease the PV curtailment rate by 36.60 %. However, hydro-PV hybridization may lead to an increase of 9.22 % in the water spillage rate and a decrease of 0.094 kWh/m3 in the water–electricity conversion coefficient. Therefore, hybrid generation of hydropower and PV could further enhance energy yield and supply reliability. Also, the importance of improving hydropower flexibility is highlighted.

Measuring the Dunkelflaute: how (not) to analyze variable renewable energy shortage

Abstract As variable renewable energy sources increasingly gain importance in global energy systems, there is a growing interest in understanding periods of variable renewable energy shortage ("Dunkelflauten''). Defining, quantifying, and comparing such shortage events across different renewable generation technologies and locations presents a surprisingly intricate challenge. Various methodological approaches exist in different bodies of literature, which have been applied to single technologies in specific locations or technology portfolios across multiple regions. We provide an overview of various methods for quantifying variable renewable energy shortage, focusing either on supply from variable renewables or its mismatch with electricity demand. We explain and critically discuss the merits and challenges of different approaches for defining and identifying shortage events and propose further methodological improvements for more accurate shortage determination. Additionally, we elaborate on comparability requirements for multi-technological and multi-regional energy shortage analysis. In doing so, we aim to contribute to unifying disparate methodologies, harmonizing terminologies, and providing guidance for future research.

Stochastic Optimization and Uncertainty Quantification of Natrium-based Nuclear-Renewable Energy Systems for Flexible Power Applications in Deregulated Markets

Rapid integration of variable renewable energy sources (VRES) has made modeling and stochastic optimization of hybrid energy systems crucial for studying their long-term performance and viability. However, most studies have focused on just historical data, which may be unreliable for capturing short-term fluctuations, rare events, and long-term patterns of energy demand, price, and the variability of renewable energy sources. For this study, optimal synthetic time series models were developed using Wasserstein distance. The models were validated by comparing the key statistical measures against those of the historical data. They were then used to optimize the integrated Natrium-style advanced energy systems and their long-term (30 years) economics. The stochastic model performs bi-level optimization to find the optimal sizes for the balance of plant and thermal energy storage, while also optimizing energy dispatch to achieve the maximum net present value.In studies of two deregulated markets (California ISO and the Electric Reliability Council of Texas), the integrated Natrium-style system performed better in CAISO than in ERCOT, given higher and more consistent electricity prices during peak-demand periods. The potentially enlarged cost associated with the variable operation and maintenance of the TES system also plays a significant role in driving the system sizing, thus its impacts on the system are investigated in detail through comparison against a baseline case. The study also finds that the bi-level optimization results based on stochastic gradient descent closely match the grid search results. The uncertainty quantification of the stochastic signals provides further NPV-related insights and probability distributions for the case studies. The normal standard error of the mean of NPV for the case with and without TES VOM for CAISO were found to be 7.73M ± 1.09M USD and 104.99M ± 1.25M USD, respectively based on a 95% confidence. Given the relatively small NPV variance based on 150 samples, the analysis affords the most robust possible prediction of the techno-economic performance of the integrated Natrium-style energy systems.

Aspects of Reduced Performance of Proton-Exchange-Membrane Water Electrolysis Via Continuum Modeling

Proton-exchange-membrane water electrolysis (PEMWE) is a technology, where hydrogen is electrochemically produced from water. Efficient industrial-scale production of hydrogen via PEMWE is contingent upon developing systems that are sufficiently resilient to operate under non-ideal operating conditions. Mathematical models can provide insight into the underlying physical mechanisms and inform the development of mitigating strategies. In the current work, a cell-level non-isothermal continuum model that is based on concentrated-solution theory that accounts for multiple ionic mobile species in the membrane and ionomer, energy transport, and fluid flow through porous media, was used to investigate two challenges to PEMWE becoming a viable technology, specifically contamination and hydrogen crossover. In cationic contamination, dissolved salts in the reactant water supplant protons in the membrane and ionomer and significantly increase the applied potentials required for operation. Hydrogen crossover is a concern especially in low-current operational modes, which can arise due to PEMWE powered by variable and cyclical renewable energy sources and can result in the production of combustible gas mixtures.For cation-contaminated cells, simulation results suggest that the uptake of the contaminant cation increased as a function of current density until local conditions in the cathode catalyst layer (cCL) allowed the contaminant desorption to occur. The model suggests that the increased cell potential is primarily due to proton activity losses in the hydrogen evolution reaction within the cCL and that ionic conductivity losses are insufficient to cause the performance losses observed experimentally. Agreement with experimental data lends the model as a possible method or predictive models for PEMWE cell recovery methods. Observations of hydrogen crossover simulations suggest several aspects of hydrogen crossover, which include that localized pressures within the catalyst layers can enhance crossover, bubble-nucleation kinetics limit the exhaust of product gases, and convective fluxes due to electroomostic drag are negligible. An improved understanding of the crossover mechanisms can inform the development of low-crossover designs and mitigation strategies. Figure 1

Multifaceted impact of renewable energy on achieving global climate targets: Technological innovations, policy frameworks, and international collaborations

This review comprehensively examines the multifaceted impact of renewable energy on achieving global climate targets, focusing on technological innovations, policy frameworks, and international collaborations. The study aims to highlight the critical role of renewable energy in mitigating climate change and promoting sustainable development. Methodologically, the paper synthesizes findings from the latest research and case studies to inform policymakers, industry stakeholders, and researchers. The main findings indicate significant advancements in renewable energy technologies, such as improvements in solar photovoltaics and wind turbines, which have enhanced efficiency and affordability. Energy storage solutions and smart grid technologies are crucial for integrating variable renewable energy sources into existing energy grids. Effective policy frameworks, including feed-in tariffs, tax incentives, and renewable portfolio standards, have been instrumental in driving renewable energy adoption. The role of international collaborations, facilitated by organizations like IRENA and agreements such as the Paris Agreement, is vital in promoting global renewable energy deployment. Conclusions drawn from the study emphasize that achieving global climate targets requires a multifaceted approach encompassing technological innovation, supportive policy frameworks, and robust international collaboration. Future research should focus on advancing renewable energy technologies, optimizing policy frameworks, enhancing international cooperation, and addressing socio-economic and environmental challenges. Recommendations include increased investment in renewable energy R&D, implementation of comprehensive policy measures that promote social equity, and strengthening international mechanisms for technology transfer and financial support. By addressing these areas, the global community can accelerate the transition to a sustainable and resilient energy system, ensuring a prosperous and climate-resilient future for all. Keywords: Renewable Energy, Climate Targets, Technological Innovations, Policy Frameworks, International Collaborations, Sustainable Development.

Frequency stabilization in microgrid with PV system based on maximum power extraction: A sliding mode approach

The article addresses the critical issue of frequency regulation in microgrids (MG) integrated with solar photovoltaic (PV) systems, which rely on maximum power point tracking (MPPT) using sliding mode control (SMC). The frequency stability of MGs is a significant concern due to the inherent variability of renewable energy sources, making frequency regulation challenging. This research proposes a dual-objective control strategy. Firstly, it ensures the solar PV system maximizes power extraction via a buck-boost converter controlled by SMC. Simultaneously, it maintains frequency regulation in the MG under load disturbances using SMC. The SMC technique guarantees precise convergence to the maximum power operating point and minimizes frequency deviations in the MG. The proposed solution demonstrates effective maximum power extraction under varying irradiance levels and reliable frequency regulation despite system parameter uncertainties and nonlinearities such as generation rate constraints (GRC) and governor deadband (GDB). Additionally, the SMC-based design achieves faster convergence compared to traditional proportional-integral (PI) controllers optimized using intelligent techniques. Stability analysis, performed using Bode and Nyquist plots, further confirms the robustness of the proposed system. The model was developed and tested in the MATLAB Simulink environment, showcasing its efficacy and reliability.

The role of renewable energies in the transition to a sustainable energy model: Challenges and opportunities

This study focused on the important role of renewable energies in the transition to a sustainable energy model and assessed their benefits, challenges and opportunities. Renewable energies have been identified as an important solution to respond to climate change by reducing greenhouse gas emissions and diversifying the energy matrix. However, challenges have been identified, including the scarcity and variability of renewable energy sources, high upfront costs and the need for infrastructure improvements. However, significant opportunities in energy storage were highlighted, including technological advances, favorable policies and regulations, and financial innovations. The positive socio-economic impact of renewable energy on job creation, social development and poverty reduction has also been demonstrated. In summary, the importance of harnessing the potential of renewable energy and addressing current challenges is key to moving towards a more secure and sustainable future.

Characterizing Supply Reliability Through the Synergistic Integration of VRE towards Enhancing Electrification in Kenya

Decentralized electrical power systems, driven by variable renewable energy sources such as solar PV and wind, have the potential to provide accessible and sustainable energy, contributing to the realization of a zero-carbon transition. However, these sources are susceptible to extreme weather conditions, presenting a challenge to the reliability of the power system. With abundant resources and a significant rural population lacking access to electricity, Africa has emerged as a key area for research on variable renewable energy-based electricity generation. Despite this focus, there remains a substantial gap in understanding at regional-scale the potential and variability of solar and wind power across various time scales, as well asthe impact of available resource synergy. Thisstudy aims to bridge this knowledge gap by conducting comprehensive simulations of hybrid wind and solar energy systems, both on-grid and off-grid, across 20 geographically diverse locations in Kenya. Using high-resolution hourly time step data, we examine the effect of resource complementarity on system reliability at varying time scales: daily, monthly and annually. The study findings shows the available VRE resource exhibit moderate tendency for complementarity, and optimizing their deployment can reduce hourly variability by 20%, significantly enhancing supply reliability, especially in the northern and eastern regions.

Cost and system effects of nuclear power in carbon-neutral energy systems

Moving towards carbon-neutral societies, both nuclear and renewable energy can potentially supply CO2-free electricity. While the cost of renewable energy has decreased significantly, the cost of nuclear has, however, increased in the past decades and now in general exceeds the cost of renewables. However, one cannot compare directly the per unit cost of electricity since temporal behavior in the electricity production differs substantially between the two groups of technologies. Nuclear power inherently aims to provide a constant base load supply of electricity, while renewables generally depend on weather patterns. Thus, the two have different requirements and impact the overall system costs differently regarding flexibility and system design. Focusing on the case of Denmark, this article investigates a future fully sector-coupled energy system in a carbon-neutral society and compares the operation and costs of renewables and nuclear-based energy systems. The study finds that investments in flexibility in the electricity supply are needed in both systems due to the constant production pattern of nuclear and the variability of renewable energy sources. However, the scenario with high nuclear implementation is 1.2 billion EUR more expensive annually compared to a scenario only based on renewables, with all systems completely balancing supply and demand across all energy sectors in every hour. For nuclear power to be cost competitive with renewables an investment cost of 1.55 MEUR/MW must be achieved, which is substantially below any cost projection for nuclear power.

A fractional-order multiple-model type-2 fuzzy control for interconnected power systems incorporating renewable energies and demand response

Frequency regulation in Multi-region Interconnected Power Systems (MIPS), incorporating wind turbine systems, energy storage units, and demand response, is a challenging control problem. The problem involves maintaining grid stability, integrating variable renewable energy sources, enhancing grid resilience, optimizing energy storage and demand response capabilities, and ensuring regulatory compliance. Effective frequency regulation is a key problem for reliable and sustainable power system operation. In this paper, complex and uncertain dynamics in various components of a MIPS are modeled using multiple first-order dynamic fractional-order Type-2 Fuzzy Logic Systems (T2-FLSs). The models are evaluated, and the best possible dynamic model is chosen. With the best possible model, an optimal controller is designed. The stability and optimality analysis are presented through a Linear Matrix Inequality (LMI) approach. The adaptive laws of T2-FLSs are derived such that some LMI-based conditions are satisfied. The designed controller does not depend on the dynamics of MIPS. The uncertainties of time-varying load, wind energy, and solar power are modeled using T2-FLSs. The suggested LMI technique presents adaptation laws for T2-FLSs to ensure stability in the presage of natural disturbances and errors. The designed scheme is validated by applying to a practical 39-bus IEEE test system that includes the wind farms, demand response, and energy storage systems. The simulation results under various conditions verify the usefulness of the suggested controller. The comparisons with conventional controllers demonstrate that the suggested approach is more effective under uncertainties and natural perturbations.

River systems under peaked stress

The change in the global energy production mix towards variable renewable energy sources requires efficient utilization of regulated rivers to optimise hydropower operations meet the needs of a changing energy market. However, the flexible operation of hydropower plants causes non-natural, sub-daily fluctuating flows in the receiving water bodies, often referred to as ‘hydropeaking’. Drastic changes in sub-daily flow regimes undermine attempts to improve river system health. Environmental decision makers, including permitting authorities and river basin managers facing the intense and increasing pressure on river environments, should consider ecosystem services and biodiversity issues more thoroughly. The need for research innovations in hydropeaking operation design to fulfil both the water and energy security responsibilities of hydropower is highlighted. Our paper outlines optimized hydropeaking design as a future research direction to help researchers, managers, and decision-makers prioritize actions that could enable better integration of river science and energy system planning. The goal of this is to find a balanced hydropower operation strategy.

System flexibility in the context of transition towards a net-zero sector-coupled renewable energy system—case study of Germany

To integrate variable renewable energy sources into the energy system and achieve net-zero emissions, the flexible operation of the power system is essential. Options that provide flexibility include electrolysis, demand side management, import and export of electricity, and flexible power plants. However, the interplay of these flexibility options in a renewable energy system with highly interacting energy and end-use sectors (known as sector coupling) is not yet fully understood. The aim of this paper is to improve the understanding of energy flexibility from a system perspective by explaining which flexibility options can provide how much flexibility and when are they operated. The analysis of the hourly results of the sector-coupled, long-term energy system model REMod shows that in times with high renewable electricity production, sector coupling technologies, specifically electrolysis and power-to-heat, dominate the annual flexibility shares. On the other hand, in times with low renewable production and high non-flexible demand, combined and open cycle gas turbines and electricity imports dominate in winter, while discharging electricity storage technologies dominate in summer. The operation of short-term electricity storage aligns in particular with photovoltaic production, while the operation of electrolysis is especially aligned to wind production. Non-flexible demand variations are driving the operation of combined and open cycle gas turbines and electricity imports. The results emphasize the pivotal role of flexibility, highlighting the need for efficient surplus electricity utilization and sector coupling. The results further suggest that it is crucial to establish market conditions that facilitate the flexible operation of various technologies in order to achieve economic efficiency.