Intermittent Renewable Energy Sources Research Articles

A Review on the Recent Advances in Battery Development and Energy Storage Technologies

Energy storage is a more sustainable choice to meet net-zero carbon foot print and decarbonization of the environment in the pursuit of an energy independent future, green energy transition, and uptake. The journey to reduced greenhouse gas emissions, increased grid stability and reliability, and improved green energy access and security are the result of innovation in energy storage systems. Renewable energy sources are fundamentally intermittent, which means they rely on the availability of natural resources like the sun and wind rather than continuously producing energy. Due to its ability to address the inherent intermittency of renewable energy sources, manage peak demand, enhance grid stability and reliability, and make it possible to integrate small-scale renewable energy systems into the grid, energy storage is essential for the continued development of renewable energy sources and the decentralization of energy generation. Accordingly, the development of an effective energy storage system has been prompted by the demand for unlimited supply of energy, primarily through harnessing of solar, chemical, and mechanical energy. Nonetheless, in order to achieve green energy transition and mitigate climate risks resulting from the use of fossil-based fuels, robust energy storage systems are necessary. Herein, the need for better, more effective energy storage devices such as batteries, supercapacitors, and bio-batteries is critically reviewed. Due to their low maintenance needs, supercapacitors are the devices of choice for energy storage in renewable energy producing facilities, most notably in harnessing wind energy. Moreover, supercapacitors possess robust charging and discharging cycles, high power density, low maintenance requirements, extended lifespan, and are environmentally friendly. On the other hand, combining aluminum with nonaqueous charge storage materials such as conductive polymers to make use of each material’s unique capabilities could be crucial for continued development of robust storage batteries. In general, energy density is a key component in battery development, and scientists are constantly developing new methods and technologies to make existing batteries more energy proficient and safe. This will make it possible to design energy storage devices that are more powerful and lighter for a range of applications. When there is an imbalance between supply and demand, energy storage systems (ESS) offer a way of increasing the effectiveness of electrical systems. They also play a central role in enhancing the reliability and excellence of electrical networks that can also be deployed in off-grid localities.

Advanced polymer electrolyte membrane water electrolysis for power to gas applications

Abstract Water electrolysis fed by renewable energy is the foremost technology to generate green hydrogen. Relevant challenges regard decrease of precious metal loadings and performance enhancement while maintaining cutting edge efficiency. Next generation electrolysers must provide dynamic behaviour to improve grid-balancing services and thus integrate with the grid the intermittent renewable energy sources. The HPEM2GAS project developed a low-cost optimised PEM electrolyser for grid management through both stack and balance of plant innovations.

The current state of transition metal-based electrocatalysts (oxides, alloys, POMs, and MOFs) for oxygen reduction, oxygen evolution, and hydrogen evolution reactions

Climate change is showing its impacts now more than ever. The intense use of fossil fuels and the resulting CO2 emissions are mainly to blame, accentuating the need to develop further the available energy conversion and storage technologies, which are regarded as effective solutions to maximize the use of intermittent renewable energy sources and reduce global CO2 emissions. This work comprehensively overviews the most recent progress and trends in the use of transition metal-based electrocatalysts for three crucial reactions in electrochemical energy conversion and storage, namely, the oxygen evolution (OER), oxygen reduction (ORR), and hydrogen evolution (HER) reactions. By analyzing the state-of-the-art polyoxometalates (POMs) and metal-organic frameworks (MOFs), the performance of these two promising types of materials for OER, ORR, and HER is compared to that of more traditional transition metal oxides and alloy-based electrocatalysts. Both catalytic activity and stability are highly influenced by the adsorption energies of the intermediate species formed in each reaction, which are very sensitive to changes in the microstructure and chemical microenvironment. POMs and MOFs allow these aspects to be easily modified to fine-tune the catalytic performances. Therefore, their chemical tunability and versatility make it possible to tailor such properties to obtain higher electrocatalytic activities, or even to obtain derived materials with more compelling properties towards these reactions.

Marine Renewable-Driven Green Hydrogen Production toward a Sustainable Solution and a Low-Carbon Future in Morocco

Oceanic energy sources, notably offshore wind and wave power, present a significant opportunity to generate green hydrogen through water electrolysis. This approach allows for offshore hydrogen production, which can be efficiently transported through existing pipelines and stored in various forms, offering a versatile solution to tackle the intermittency of renewable energy sources and potentially revolutionize the entire electrical grid infrastructure. This research focusses on assessing the technical and economic feasibility of this method in six strategic coastal regions in Morocco: Laayoune, Agadir, Essaouira, Eljadida, Casablanca and Larache. Our proposed system integrates offshore wind turbines, oscillating water column wave energy converters, and PEM electrolyzers, to meet energy demands while aligning with global sustainability objectives. Significant electricity production estimates are observed across these regions, ranging from 14 MW to 20 MW. Additionally, encouraging annual estimates of hydrogen production, varying between 20 and 40 tonnes for specific locations, showcase the potential of this approach. The system’s performance demonstrates promising efficiency rates, ranging from 13% to 18%, while maintaining competitive production costs. These findings underscore the ability of oceanic energy-driven green hydrogen to diversify Morocco’s energy portfolio, bolster water resilience, and foster sustainable development. Ultimately, this research lays the groundwork for comprehensive energy policies and substantial infrastructure investments, positioning Morocco on a trajectory towards a decarbonized future powered by innovative and clean technologies.

On the prediction of the induced damage by the start-up sequence of Francis turbines: On operational resilience framework

The number of transient operations in hydraulic machinery connected to power grid, notably start-ups and shut-downs, has observed a substantial increase in recent decades, primarily driven by the global shift toward intermittent renewable energy sources. Simultaneously, advancements in MW power converter technology and its cost-effectiveness have altered the operational paradigms of hydropower plants. These transformations offer novel opportunities for asset management within the industry. This study introduces a new method aimed at forecasting stress during start-up procedures, leveraging steady-state measurements acquired from a reduced scale model of the hydraulic turbine. Through a dedicated modular telemetry measurement system and the integration of strain gauges onto the reduced-scale runner blades, a tool is devised to predict dynamic loads characteristic of these transient operations. Utilizing steady-state measurements and a Voronoi cell tessellation, the transient predicted stress signal is constructed by concatenating the information from each encountered cell, thus providing an estimated projection of the stress likely to occur during the sequence. The proposed methodology demonstrates a robust forecast of the stresses on the runner blades during steady-state and transient operations of Francis turbines. Its immediate value lies in the ability to correctly estimate the lifetime of the runner as well as the possible integration into an optimization framework for stress reduction, thereby potentially extending the operational lifespan of the unit, from the runner structure perspectives.

Incorporating operational constraints into long-term energy planning: The case of the Egyptian power system under high share of renewables

This study assesses the performance of Egypt's energy system on a short-term basis to ensure that it can handle a high share of renewable energy, as predicted in the long-term planning up to 2040. PLEXOS software is used for short-term analysis to simulate operational performance on an hourly basis while considering the constraints of Unit Commitment (UC) and Economic Dispatch (ED). The long-term energy planning model, which covered the years 2020–2040 with chosen representative years (2020 as the base year and 2025, 2030, 2035, and 2040), was validated by the short-term operational model. The results from the short-term analysis indicate that by the year 2040, 69.5 % of the electricity mix from renewable energy sources (excluding hydro) can be accommodated, representing a slightly lower capacity than the 70 % predicted by the long-term plan. Due to the high share of intermittent renewable energy sources, traditional generators will experience excessive cycling in 2040. The average weighted short-run marginal cost in 2040 is projected to be 7.8 USD/MWh, compared to 18.37 USD/MWh in 2020, due to the low operating costs of renewable energy plants and their high penetration in 2040. Various operational techniques have been suggested to reduce the curtailment of renewable energy to achieve only 1.2 % of the total energy generation of the system by 2040. Additionally, other adjustments to the system operation are being considered to maintain a balance in the power system on a short-term basis.

Reviewing experimental studies on sensible thermal energy storage in cementitious composites: report of the RILEM TC 299-TES

Thermal energy storage (TES) systems have been a subject of growing interest due to their potential to address the challenges of intermittent renewable energy sources. In this context, cementitious materials are emerging as a promising TES media because of their relative low cost, good thermal properties and ease of handling. This article presents a comprehensive review of studies exploring the use of cementitious materials, particularly concrete, as sensible heat storage media at varying scales, ranging from laboratory investigations to prototype evaluations. Starting from the different kinds of energy storage systems and applications where concrete has been used as a storage media, this article reviews the important properties which makes them a suitable material for the purpose. Reported observations are discussed and summarised based on concrete mix composition/design, aggregate/addition type, size gradation, etc., and performance of these materials. Finally, different cement-based prototypes are examined highlighting their strengths and weaknesses, and general conclusions are drawn.

Renewable sources with virtual inertia penetration in multi area interconnected AGC using a modified MPC controller

The challenge of controlling frequency deviation becomes more difficult as the complexity of a power plant increases. The robustness of the controller has a major impact on the stability of a complex power system (CPS). Due to the hybridization of CPS basic Automatic Generation Control (AGC) controllers (PID, FOPID, and TID), they are insufficient to give optimal performance to a plant. This requires a robust controller. So, a modified MPC controller has been proposed and evaluated by comparing it with several existing controllers, which gives optimal performance in terms of overshoot, undershoot, and settling time and improves its performance approximately 45%. This research discusses a combined AGC model and control for a three-area CPS, where each producing area consists of a thermal plant, a Diesel power plant, and a Solar Thermal Power Plant (STPP). The results of the modified MPC are superior to those of the basic controller compared to several existing controllers. An improved version of Sea-horse Optimization (SHO) has been proposed to optimize the different controller settings. The superiority of the SHO is shown by a comparison with some well-known, current meta-heuristic methods. The higher penetration levels of renewable energy sources (RESs) reduced system inertia which further deteriorate frequency response in CPS. To overcome these challenges, virtual inertia (VI) has been implemented with MPC. VI is applied to improve the performance of the AGC of the interconnected CPS along with emphasizing the nature of intermittent RESs of PV and wind energy. The thorough study findings provide compelling evidence for the effectiveness and efficiency of the recommended control strategies and also point to the possibility of applying them in actual power systems to improve stability and performance.

Economic operation of an agent-based virtual storage aggregated residential electric-heating loads in multiple electricity markets

The increasing penetration of intermittent renewable energy sources leads to a higher demand for flexible balancing service in the power system. Consequently, demand-side management techniques, such as utilizing flexible resources from residential electric-heating loads, provide a promising solution. However, due to various uncertainties such as stochastic weather and market prices, it is challenging to develop an economically efficient strategy. Hence, this paper proposes an economic operation optimization approach for residential electric-heating loads to develop optimal bidding and scheduling strategy in the multi-stage market. First, the dynamic characteristics of aggregated electric-heating loads are modeled as the virtual energy storage systems (VESS) to quantify the flexibility potential arising from the combination of building thermal inertia, user tolerance and thermal energy storage (TES). Subsequently, the joint energy and balancing service market is introduced to exploit the operating flexibility of VESS. A multi-agent deep reinforcement learning (MADRL) optimization framework is proposed to address the multi-objective problem at different decision frequency, which involves achieving lower economic costs while maintaining indoor comfort. Finally, we combine the DRL with imitation learning (IL) by introducing the behavior cloning mechanism to mitigate training process instability. It reduces the computational costs and eliminates the need for redundant additional structure. Comparative simulation experiments demonstrate the efficiency of data-driven optimization approach, which provides an adaptive, economic cost-effective and general solution for multi-type aggregators to activate their flexibility in dynamic markets.

Modelling of Solid-State Transformer to Support the Interconnection of Microgrids for Power Sharing and Harmonic Compensation During Islanded Operation

The concept of mcirogrids has gained popularity in the distribution of electricity to the final consumer. Microgrids integrating energy storage devices, combined heat and power system (CHP) and renewable energy generation are especially becoming attractive to industrial consumers –such as industrial parks – due to environmental and economic benefits. However, the intermittence of renewable energy sources imply that storage is essential for economic operation. However, technological limitations of storage solutions for the grid imply that we need to consider supplying the power into the main grid. However, grids are designed for unidirectional operation, which implies that mcirogrids cannot receive and send power to the grid. This research paper, shows the potential for SSTs to support power-sharing among islanded microgrids. The microgrids are interconnected through the low-voltage medium, which implies that they can send and receive power from the main grid. Simulations through MATLAB demonstrate that the SST can support the integration of renewable energy sources at the low-voltage DC bus. Furthermore, advanced controls – particularly, particle swarm optimization – can be implemented to mitigate harmonics (only 1.17% in the presence of non-linear loads and 0.36% in the presence of resistive loads alone) and voltage imbalance (the voltage unbalance factor is less than 1%) at the microgrid level. Microgrids generating excess power can also share with neighboring microgrids in the absence of the main grid (for instance, during a fault). This research is instrumental in reconfiguring conventional grids to meet the needs of modern power system requirements.

Enhancing frequency regulation in multi‐area interconnected MPS with virtual inertia using MPC + PIDN controller

AbstractThe challenge of controlling frequency deviation becomes more difficult as the complexity of a power network increases. The robustness of the controller has a major impact on the stability of a Modern Power system (MPS). Due to the hybridization of MPS basic AGC controllers (PID, FOPID, and TID) are insufficient to give optimal performance of a plant. This requires a robust controller. So, a novel MPC + PIDN controller has been proposed and evaluated by comparing it with several existing controllers, which gives optimal performance in terms of overshoot, undershoot, and settling time. A new modified Opposition‐based Sea‐horse Optimization (OSHO) method has been suggested to optimize the various controller settings. To demonstrate the OSHO's superiority, it is compared with a few popular, existing meta‐heuristic optimizations. The higher penetration levels of RESs reduced system inertia which further deteriorate frequency response in MPS. To overcome these challenges virtual inertia (VI) is implemented with MPC. VI is applied to improve the performance of the AGC of the interconnected MPS along with emphasizing the nature of intermittent renewable energy sources (RESs) of PV and wind energy. To determine the reliability and flexibility of the proposed controller, analysis has been done under a different situation, including step, random disturbances, and modified IEEE‐39 bus. Finally, the stability analysis is performed on a bode plot and the proposed results are compared with previously published literature. The extensive study demonstrates strong evidence that the suggested control approach is efficient and effective.

Molten sodium batteries: advances in chemistries, electrolytes, and interfaces

The need for clean, renewable energy has driven the expansion of renewable energy generators, such as wind and solar. However, to achieve a robust and responsive electrical grid based on such inherently intermittent renewable energy sources, grid-scale energy storage is essential. The unmet need for this critical component has motivated extensive grid-scale battery research, especially exploring chemistries “beyond Li-ion”. Among others, molten sodium (Na) batteries, which date back to the 1960s with Na-S, have seen a strong revival, owing mostly to raw material abundance and the excellent electrochemical properties of Na metal. Recently, many groups have demonstrated important advances in battery chemistries, electrolytes, and interfaces to lower material and operating costs, enhance cyclability, and understand key mechanisms that drive failure in molten Na batteries. For widespread implementation of molten Na batteries, though, further optimization, cost reduction, and mechanistic insight is necessary. In this light, this work provides a brief history of mature molten Na technologies, a comprehensive review of recent progress, and explores possibilities for future advancements.

Grid connected solar panel with battery energy storage system

A grid-connected battery energy storage system (BESS) is a crucial component in modern electrical grids that enables efficient management of electricity supply and demand. BESS consists of a set of batteries connected to the power grid, allowing for the storage and release of electricity when needed. This paper addresses the challenges associated with intermittent renewable energy sources and enhancing grid stability and reliability. The primary objective of this work is to store surplus electricity during low demand and supply it to the grid during peak demand periods or when renewable energy generation is low. By storing surplus energy, BESS helps balance supply and demand fluctuations, reducing the need for expensive fossil fuel-based power plants and minimizing greenhouse gas emissions. Additionally, BESS provides frequency regulation, voltage support, and grid stabilization. Furthermore, BESS reduces the intermittency of renewable energy sources like solar and wind, allowing for its integration into the grid. It allows the captured energy to be stored and utilized when the renewable sources are not actively generating electricity. Grid-connected BESS are a vital component in the transition towards a more sustainable and resilient energy future. They facilitate the effective utilization of renewable energy, enhance grid flexibility, and contribute to the reduction of carbon emissions, ultimately promoting a cleaner and more reliable electricity supply. The simulation of grid connected solar system with BESS is carried out using MATLAB/Simulink environment.

Towards Risk-Aware Real-Time Security Constrained Economic Dispatch: A Tailored Deep Reinforcement Learning Approach

In the presence of increasing uncertainties brought by intermittent renewable energy sources, security and risk management continue to be the most critical concern in modern power system operation. Risk-aware, real-time security constrained economic dispatch (RT-SCED) provides an efficient solution towards promptly, economically and robustly responding to the changes in the power system operating state. Despite different model-based methods have been developed to handle uncertainties, significant computation burden arise to incorporate <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$N$</tex-math></inline-formula> -1 contingency constraints with a higher temporal resolution in RT-SCED. Driven by similar computational challenges, risk evaluation is often overlooked in the current application of deep reinforcement learning (DRL) based data-driven methods in RT-SCED. This paper proposes a DRL-based risk-aware RT-SCED methodological framework by incorporating a novel data-driven risk evaluation model to foster efficient agent-environment interactions. The real-time dispatch policies are constructed with an improved twin delayed deep deterministic policy gradient method. The policy network features a residual network architecture and incorporates an active power allocation mechanism to integrate empirical dispatch knowledge, preventing early termination and fostering more efficient learning behavior. Case studies validate the superior performance of the proposed method in risk-aware RT-SCED on cost efficiency, uncertainty adaptability and computational efficiency, through benchmarking against model-based and data-driven baseline methods.

Rotor–stator interaction investigations in variable speed reversible pump-turbine at higher head

Efficiency and grid stability can be improved by variable speed operation using doubly fed induction machine technology for pumped storage plants experiencing significant head variations. With the higher penetration of intermittent and variable renewable energy sources, viz., solar and wind, the grid may be stabilized by operating the reversible pump-turbines (RPTs) in off-design conditions. In a turbine mode, the RPT is more susceptible to fatigue and vibrations when operating at a higher head as a result of hydraulic instability generated by rotor–stator interaction (RSI); therefore, its performance becomes even more critical. The powerhouse structural components, including floors and columns, could experience intense vibrations because of this instability. Therefore, it is essential to investigate the RSI in the variable speed RPTs at the higher head. These investigations present the results of a numerical analysis of RSI and its associated pressure fluctuations in the variable speed RPTs at the higher head. The high-head scaled model of variable speed RPT was used, and the numerical simulations were executed by utilizing the shear stress transport k-ω turbulence model. The numerical analysis was performed at the best efficiency point and high-head operating conditions having optimized rotational speed. The results show that the main source of pressure fluctuations in the variable speed RPT at all operating conditions is RSI, where the dominant frequencies are blade passing frequency (9fn) and its harmonics. It is also found that the variable speed operation lowers the pressure fluctuations in the RPT.

Seq2Seq-Based-Day-Ahead Scheduling for SCUC in Islanded Power Systems with Limited Intermittent Generation

Due to their dependence on intermittent renewable energy sources, island power systems, which are generally located in remote places or on islands, offer particular issues for day-ahead scheduling. Using the capabilities of neural networks, we offer a Seq2Seq-based technique for day-ahead scheduling, which increases the precision and flexibility of unit commitment choices. The attention mechanisms in the Seq2Seq model are trained with historical data that includes projections for intermittent generation, demand, and unit commitment choices. The model is tested for its capacity to incorporate dynamic temporal relationships and deal with regenerative uncertainty. Seq2Seq models, a kind of deep learning approach, have shown impressive performance in several applications requiring sequence prediction. Uncertainty in renewable energy production, energy demand forecasts, and security limitations are all addressed in this work as Seq2Seq algorithms are applied to microgrid SCUC. In comparison to conventional scheduling approaches, the results show potential gains in prediction accuracy and operational efficiency. This study demonstrates how Seq2Seq models may be used to improve the longevity and dependability of isolated electrical grids and the way for the development of more effective, sustainable, and resilient energy infrastructure by contributing to the advancement of the area of microgrid optimization.

LNG as a bridge fuel in the transition to renewable energy: A global perspective

The global energy landscape stands at the precipice of transformation, with a growing consensus on the imperative to shift towards sustainable and renewable sources. Amidst this transition, Liquefied Natural Gas (LNG) emerges as a pivotal bridge fuel, strategically positioned to facilitate the journey towards renewable energy. This review encapsulates the essence of the comprehensive review, delving into the global perspective on LNG's role as a bridge fuel in the renewable energy transition. The narrative unfolds with a contextualization of the pressing need for a renewable energy transition, acknowledging the escalating environmental concerns and the imperative to reduce carbon footprints. It then seamlessly transitions to the concept of LNG as a bridge fuel, elucidating its capacity to serve as a cleaner alternative to traditional fossil fuels and its role in mitigating the challenges associated with intermittent renewable energy sources. Examining LNG's significance on a global scale, the review navigates through key aspects. It scrutinizes the environmental considerations and carbon reduction goals that position LNG as a pragmatic choice in the decarbonization journey. The analysis extends to policy factors influencing LNG demand, unraveling the intricate tapestry of governmental initiatives supporting its adoption and the dynamic interplay with renewable energy policies. Economic drivers take center stage in the exploration of LNG's role as a bridge fuel. The review investigates the cost competitiveness, market dynamics, and the industrial demand propelling its consumption. The comprehensive examination encompasses the expansion of global LNG production capacity, featuring key exporting nations and the technological innovations transforming LNG production processes. Regional dynamics further enrich the narrative, providing insights into LNG's impact on major economies across Asia-Pacific, Europe, and North America. The review culminates in a nuanced exploration of the geopolitical implications surrounding LNG trade, emphasizing its role in geopolitical events, trade agreements, and potential risks for stakeholders. In essence, this review serves as a guide to stakeholders, policymakers, and industry players navigating the complex interplay between LNG and renewable energy in the global quest for a sustainable energy future.

Emerging Two-Dimensional Carbonaceous Materials for Electrocatalytic Energy Conversions: Rational Design of Active Structures through High-Temperature Chemistry.

Electrochemical energy conversion and storage technologies involving controlled catalysis provide a sustainable way to handle the intermittency of renewable energy sources, as well as to produce green chemicals/fuels in an ecofriendly manner. Core to such technology is the development of efficient electrocatalysts with high activity, selectivity, long-term stability, and low costs. Here, two-dimensional (2D) carbonaceous materials have emerged as promising contenders for advancing the chemistry in electrocatalysis. We review the emerging 2D carbonaceous materials for electrocatalysis, focusing primarily on the fine engineering of active structures through thermal condensation, where the design, fabrication, and mechanism investigations over different types of active moieties are summarized. Interestingly, all the recipes creating two-dimensionality on the carbon products also give specific electrocatalytic functionality, where the special mechanisms favoring 2D growth and their consequences on materials functionality are analyzed. Particularly, the structure-activity relationship between specific heteroatoms/defects and catalytic performance within 2D metal-free electrocatalysts is highlighted. Further, major challenges and opportunities for the practical implementation of 2D carbonaceous materials in electrocatalysis are summarized with the purpose to give future material design guidelines for attaining desirable catalytic structures.

Review of Energy Management Systems in Microgrids

Microgrids usually employ distributed energy resources such as wind turbines, solar photovoltaic modules, etc. When multiple distributed generation resources with different features are used in microgrids, managing these resources becomes an important problem. The generated power of solar photovoltaic modules and wind turbines used in microgrids is constantly changing with solar irradiation and wind speed. Due to this impermanent and uncertain nature of renewable energy resources, generally, energy storage systems are employed in microgrid systems. To control the distributed energy resources and energy storage units and sustain the supply and demand balance within the microgrid and provide sustainable and reliable energy to the loads, energy management systems are used. Many methods are used to realize and optimize energy management in microgrids. This review article provides a comparative and critical analysis of the energy management systems used in microgrids. The energy management system can be tailored for different purposes, which are also discussed in detail. Additionally, various uncertainty measurement methods are summarized to manage the variability and intermittency of renewable energy sources and load demand. Finally, some thoughts about potential future directions and practical applications are given.

Potential–Dependent BDAC Adsorption on Zinc Enabling Selective Suppression of Zinc Corrosion for Energy Storage Applications

Utility-scale zinc (Zn) batteries are a promising solution to address the problem of intermittency of renewable energy sources; however, Zn-metal anodes in these batteries suffer from capacity loss due to spontaneous corrosion of the Zn especially when high-surface area anode configurations are employed. Additionally, Zn dendrites are known to form during battery charging limiting the cycle-life of these batteries. Electrolyte additives have been explored that prevent aforementioned issues, but these too come at a cost, i.e., surface-blocking additives polarize the electrode surface leading to loss in the voltaic and energy efficiencies of the battery. In this contribution, a novel electrolyte additive, benzyldimethylhexadecylammonium chloride (BDAC), is investigated for its ability to suppresses corrosion of Zn in an acidic (pH = 3) electrolyte. An attribute of BDAC distinct from previously studied additives is that it selectively suppresses electrochemical activity when the Zn electrode is at its corrosion potential; however, during high-rate Zn deposition (charging) or stripping (discharging), BDAC is essentially deactivated and thus it does not appreciably polarize the electrode surface, thus minimizing voltaic efficiency losses. This selective corrosion suppression behavior is explored using slow-scan voltammetry, which reveals hysteresis implying a potential- or current-dependent BDAC adsorption mechanism in which BDAC reaches higher surface coverages when the partial currents at the Zn surface are low (e.g., at or near the corrosion potential), but BDAC coverage is reduced considerably when the Zn deposition or stripping rates are increased. Numerical simulations of the BDAC diffusion-adsorption process corroborate this mechanism. Ramifications of our approach to the selective suppression of Zn dendrites are discussed.