Integrated Energy Flexibility Management at Wastewater Treatment Facilities.

On-site batteries, low-pressure biogas storage, and wastewater storage could position wastewater resource recovery facilities as a widespread source of industrial energy demand flexibility. This work introduces a digital twin method that simulates the coordinated operation of current and future energy flexibility resources. We combine process models and statistical learning on 15 min resolution sensor data to construct a facility's energy and water flows. We then value energy flexibility interventions and use an iterative search algorithm to optimize energy flexibility upgrades. Results from a California facility with anaerobic sludge digestion and biogas cogeneration predict a 17% reduction in electricity bills and an annualized 3% return on investment. A national analysis suggests substantial benefit from using existing flexibility resources, such as wet-weather storage, to reduce electricity bills but finds that new energy flexibility investments are much less profitable in electricity markets without time-of-use incentives and plants without existing cogeneration facilities. Profitability of a range of energy flexibility interventions may increase as a larger number of utilities place a premium on energy flexibility, and cogeneration is more widely adopted. Our findings suggest that policies are needed to incentivize the sector's energy flexibility and provide subsidized lending to finance it.

An Automatic Aggregator of Power Flexibility in Smart Buildings Using Software Based Orchestration.

This paper presents a software-based modular and hierarchical building energy management system (BEMS) to control the power consumption in sensor-equipped buildings. In addition, the need of this type of solution is also highlighted by presenting the worldwide trends of thermal energy end use in buildings and peak power problems. Buildings are critical component of smart grid environments and bottom-up BEMS solutions are need of the hour to optimize the consumption and to provide consumption side flexibility. This system is able to aggregate the controls of the all-controllable resources in building to realize its flexible power capacity. This system provides a solution for consumer to aggregate the controls of 'behind-the-meter' small loads in short response and provide 'deep' demand-side flexibility. This system is capable of discovery, status check, control and management of networked loads. The main novelty of this solution is that it can handle the heterogeneity of the installed hardware system along with time bound changes in the load device network and its scalability; resulting in low maintenance requirements after deployment. The control execution latency (including data logging) of this BEMS system for an external control signal is less than one second per connected load. In addition, the system is capable of overriding the external control signal in order to maintain consumer coziness within the comfort temperature thresholds. This system provides a way forward in future for the estimation of the energy stored in the buildings in the form of heat/temperature and use buildings as temporary batteries when electricity supply is constrained or abundant.

Blockchain and Demand Response: Zero-Knowledge Proofs for Energy Transactions Privacy.

Nowadays, the adoption of demand response programs is still lagging due to the prosumers' lack of awareness, fear of losing control and privacy of energy data, etc. Programs decentralization, by adopting promising technologies such as blockchain, may bring significant advantages in terms of transparency, openness, improved control, and increased active participation of prosumers. Nevertheless, even though in general the transparency of the public blockchain is a desirable feature in the energy domain, the prosumer energy data is sensitive and rather private, thus, a privacy-preserving solution is required. In this paper, we present a decentralized implementation of demand response programs on top of the public blockchain which deals with the privacy of the prosumer's energy data using zero-knowledge proofs and validates on the blockchain the prosumer's activity inside the program using smart contracts. Prosumer energy data is kept private, while on the blockchain it is stored a zero-knowledge proof that is generated by the prosumer itself allowing the implementation of functions to validate potential deviations from the request and settle prosumer's activity. The solution evaluation results are promising in terms of ensuring the privacy of prosumer energy data stored in the public blockchain and detecting potential data inconsistencies.

Mitochondria and Calcium Homeostasis: Cisd2 as a Big Player in Cardiac Ageing.

The ageing of human populations has become a problem throughout the world. In this context, increasing the healthy lifespan of individuals has become an important target for medical research and governments. Cardiac disease remains the leading cause of morbidity and mortality in ageing populations and results in significant increases in healthcare costs. Although clinical and basic research have revealed many novel insights into the pathways that drive heart failure, the molecular mechanisms underlying cardiac ageing and age-related cardiac dysfunction are still not fully understood. In this review we summarize the most updated publications and discuss the central components that drive cardiac ageing. The following characters of mitochondria-related dysfunction have been identified during cardiac ageing: (a) disruption of the integrity of mitochondria-associated membrane (MAM) contact sites; (b) dysregulation of energy metabolism and dynamic flexibility; (c) dyshomeostasis of Ca2+ control; (d) disturbance to mitochondria-lysosomal crosstalk. Furthermore, Cisd2, a pro-longevity gene, is known to be mainly located in the endoplasmic reticulum (ER), mitochondria, and MAM. The expression level of Cisd2 decreases during cardiac ageing. Remarkably, a high level of Cisd2 delays cardiac ageing and ameliorates age-related cardiac dysfunction; this occurs by maintaining correct regulation of energy metabolism and allowing dynamic control of metabolic flexibility. Together, our previous studies and new evidence provided here highlight Cisd2 as a novel target for developing therapies to promote healthy ageing.

Modularized neural network incorporating physical priors for future building energy modeling.

Building energy modeling (BEM) is fundamental for achieving optimized energy control, resilient retrofit designs, and sustainable urbanization to mitigate climate change. However, traditional BEM requires detailed building information, expert knowledge, substantial modeling efforts, and customized case-by-case calibrations. This process must be repeated for every building, thereby limiting its scalability. To address these limitations, we developed a modularized neural network incorporating physical priors (ModNN), which is improved by its model structure incorporating heat balance equations, physically consistent model constraints, and data-driven modular design that can allow for multiple-building applications through model sharing and inheritance. We demonstrated its scalability in four cases: load prediction, indoor environment modeling, building retrofitting, and energy optimization. This approach provides guidance for future BEM by incorporating physical priors into data-driven models without extensive modeling efforts, paving the way for large-scale BEM, energy management, retrofit designs, and buildings-to-grid integration.

Electric vehicle charging dataset with 35,000 charging sessions from 12 residential locations in Norway.

This data article refers to the paper "A method for generating complete EV charging datasets and analysis of residential charging behaviour in a large Norwegian case study" [1]. The Electric Vehicle (EV) charging dataset includes detailed information on plug-in times, plug-out times, and energy charged for over 35,000 residential charging sessions, covering 267 user IDs across 12 locations within a mature EV market in Norway. Utilising methodologies outlined in [1], realistic predictions have been integrated into the datasets, encompassing EV battery capacities, charging power, and plug-in State-of-Charge (SoC) for each EV-user and charging session. In addition, hourly data is provided, such as energy charged and connected energy capacity for each charging session. The comprehensive dataset provides the basis for assessing current and future EV charging behaviour, analysing and modelling EV charging loads and energy flexibility, and studying the integration of EVs into power grids.

Decarbonizing real estate portfolios considering optimal retrofit investment and policy conditions to 2050.

Retrofitting existing buildings is crucial for achieving Net Zero emissions. Institutional real estate owners play a key role because of their significant ownership, especially of large buildings. We utilize an interdisciplinary approach to evaluate cost-optimal decarbonization conditions for three Swiss real estate portfolios owned by a global institutional investor. We leverage a bottom-up optimization framework for building asset retrofitting, scaled to the portfolio-level, to study the effect of policy scenarios and implementations. Results indicate that achieving Net Zero necessitates significant investments, largely through thermal energy efficiency measures and low-CO2 energy systems, as early as possible to avoid locked-in emissions. Owners will be challenged to smooth long-term capital investments, pointing to a potential liquidity crisis. Consequently, hard-to-decarbonize assets are unable to reach regulatory benchmarks largely because of lingering embodied emissions. To lower transition risk, we recommend that policymakers move toward average CO2 benchmarks at the real estate portfolio-level, emulating automotive fleets.

Toward evaluating the effect of technology choices on linkages between sustainable development goals.

Linkages between the Sustainable Development Goals (SDGs) have sparked research interest because a better understanding of SDG co-benefits may enable faster progress on multiple sustainability fronts. However, SDG linkages are typically analyzed without considering the technologies used to implement a primary SDG, which may have secondary effects on other SDGs. Here, we outline an approach to study this problem by connecting the industries and services required to produce a technology to the United Nations SDG indicator framework, using SDG7 and four energy technologies as an illustrative case. We find that all technologies in our set involve potential co-benefits with SDGs 1, 8-10, 12-13, and 17, and trade-offs with SDGs 6, 8-9, 11-12, and 14-15. Deployment services primarily induce co-benefits; manufacturing has mixed impacts. Our work sheds light on the technology characteristics (e.g., scale, high- or low-tech) that influence linkages while also pointing to SDG-relevant characteristics not captured by UN indicators.

Multi-responsive, flexible, and structurally colored film based on a 1D diffraction grating structure.

In nature, many organisms (e.g., chameleons) protect themselves by changing their colors in response to environmental changes. Inspired by these organisms, we present a multi-responsive, flexible, and structurally colored hydrogel film with a one-dimensional (1D) ordered periodic groove structure. The groove structure endows the film with bright, highly angle-dependent structural colors, which can be reversibly tuned by stretching and releasing. In addition, because of the thermosensitive properties of the hydrogel, the film can be switched between colored state and opaque white state with temperature. In addition, the optical state of the film is sensitive to solvent and can be reversibly changed between colored state and transparent state with soaking and evaporation of the solvent. This reversible, multi-responsive, flexible, and structurally colored hydrogel film has great potential to be used in the fields of color display, sensors, anti-counterfeiting, and so on because of its flexible and diverse tuning methods, excellent optical performance, and convenient preparation process.

Private vs. public value of U.S. residential battery storage operated for solar self-consumption.

Compensation structures for residential solar are evolving toward a model that incentivizes using battery storage to maximize solar self-consumption. Using metered data from 1,800 residential customers across six U.S. utilities, we show that batteries operated solely in this manner provide customer bill savings up to $20-30 per kWh of storage capacity annually, but virtually no grid value. Relative to market-based dispatch, this value gap remains across customers and will become more severe over time, insofar as increased renewable energy penetration leads to more volatile wholesale prices. This inefficiency primarily stems from residential batteries largely sitting idle on peak days. We show that incentivizing storage customers to respond to market prices, particularly on peak days, would enhance both private and public value. Unconstrained grid discharging increases exports to distribution networks, but 50-70% of the potential market value could be achieved without materially degrading solar self-consumption levels or increasing local grid stress.

Carbon contracts-for-difference: How to de-risk innovative investments for a low-carbon industry?

The shift to climate neutrality requires new process technologies for energy-intensive industries, such as steel, chemicals, or cement. A variety of technology options exist - but they face the challenges of (i) first-of-kind costs, (ii) higher operation and investment costs, and (iii) insufficient and uncertain carbon prices, which partly stem from political uncertainty. Existing innovation policy instruments and carbon policies such as price floors can only partly address these challenges. Project-based carbon contracts-for-difference (CCfDs) guarantee investors a fixed carbon price over the contract duration, thus de-risking such investments from political and market uncertainty, and allowing governments to set carbon prices above current levels. Here we show for a case study in the steel sector that carbon mitigation costs can be reduced by up to 27% and that owing to high incremental operation costs, price floors of 79% of the CCfD price would be needed for projects to achieve bankability.

Beyond A single stimulus: How to leverage the federal government to advance clean energy innovation?

There is a critical need to accelerate and improve the innovation process for clean energy technologies. In order to stem the most-dire effects of the climate crisis, there will need to be increased research, development, demonstration, commercialization, deployment, and adoption of clean energy technologies. The innovation process for energy technologies is especially challenging compared with other technological sectors, and can be strengthened through better use of the unique capabilities of the federal government. Recently, the focus of efforts to enhance clean energy innovation has been on what a stimulus bill and/or single piece of legislation can achieve. However, the federal government possesses numerous other means for strengthening the energy innovation process: (1) taking on a greater quantity of risk in the federal government's RD&D portfolio; (2) extending the federal government's support for clean energy technologies through its purchasing power; (3) drawing on the full scope of the federal government; and (4) putting energy innovation in the context of societal transformations. Insights on how to draw on the federal government's resources to support clean energy innovation through these means are described and discussed with an eye toward applicability and actionable steps.

Electrifying New York City Ride-Hailing fleets: An examination of the need for public fast charging.

This report assesses the scale of public fast charging needed to electrify approximately 20,000 vehicles across the yellow cab and for-hire segments in New York City. The analysis considers real-world trip data in conjunction with driver home locations, overnight charging access rates, driver schedules, and more. Outcomes indicate that the existing charging network in New York City is not adequate even in the most optimistic scenario; 1,054 150-kW ports are required when 15% of drivers have access to overnight charging, whereas 367 150-kW ports are needed when 100% of drivers have access. Results also indicate that although charging is demanded in areas nearby high trip demand, fast charging ports are also demanded in areas near driver residences as a supplement for home charging in scenarios with limited overnight charging access. These findings motivate investment into both overnight charging and public fast charging to meet the charging demands of ride-hailing fleets.

The quantity-quality transition in the value of expanding wind and solar power generation.

Wind and solar photovoltaic generators are projected to play important roles in achieving a net-zero-carbon electricity system that meets current and future energy needs. Here, we show potential advantages of long-term site planning of wind and solar power plants in deeply decarbonized electricity systems using a macro-scale energy model. With weak carbon emission constraints and substantial amounts of flexible electricity sources on the grid (e.g., dispatchable power), relatively high value is placed on sites with high capacity factors because the added wind or solar capacity can efficiently substitute for running natural gas power plants. With strict carbon emission constraints, relatively high value is placed on sites with high correlation with residual demand because resource complementarity can efficiently compensate for lower system flexibility. Our results suggest that decisions regarding long-term wind and solar farm siting may benefit from consideration of the spatial and temporal evolution of mismatches in electricity demand and generation capacity.

Decarbonization of the Indian electricity sector: Technology choices and policy trade-offs.

India is the third largest CO2 emitter worldwide, and its electricity demand, which is primarily supplied by coal-fired generation, is expected to increase almost threefold over the next twenty years. Here, we simulate 40 scenarios for the 2040 Indian electricity sector, considering uncertainty in future natural gas prices and costs for batteries and variable renewable energy (VRE) technologies, under different CO2 emissions limits and renewable portfolio standard (RPS) targets. We find a large-scale expansion of VRE, particularly, solar PV, in most scenarios. Furthermore, energy storage competes with natural gas and coal to provide flexibility to integrate VRE. Given a set of technology assumptions, policies that explicitly limit CO2 emissions are more cost-effective at reducing emissions than RPS policies. The former are also more effective at reducing air pollution than RPS policies by explicitly penalizing CO2 emissions, thereby reducing coal generation more substantially than RPS policies.

Targeted demand response for mitigating price volatility and enhancing grid reliability in synthetic Texas electricity markets.

Demand response (DR) is rapidly gaining attention as a solution to enhance the grid reliability with deep renewable energy penetration. Although studies have demonstrated the benefits of DR in mitigating price volatility, there is limited work considering the choice of locations for DR for maximal impact. We reveal that very small load reductions at a handful of targeted locations can lead to a significant decrease in price volatility and grid congestion levels based on a synthetic Texas grid model. We achieve this through exploiting the highly nonlinear nature of congestion dynamics and by strategically selecting DR locations. We demonstrate that we can similarly place energy storage to achieve an equivalent impact. Our findings suggest that targeted DR at specific locations, rather than across-the-board DR, can have substantial benefits to the grid. These findings can inform energy policy makers and grid operators how to target DR initiatives for improving grid reliability.

Potential greenhouse gas risk led by renewable energy crowding out nuclear power.

Increasing variable renewable energy (VRE) is one of the main approaches for greenhouse gas (GHG) mitigation. However, we find a GHG increase risk associated with increasing VRE: VRE crowds out nuclear power (VRECON) but cannot fully obtain the left market share, which is obtained by fossil energy. We developed an integrated dispatch-and-investment model to estimate the VRECON GHG-boosting effect in the Pennsylvania-New Jersey-Maryland Interconnection and the Electric Reliability Council of Texas. In the above two markets, VRECON could increase the annual GHG emission by up to 136 MTCO2eq totally. Furthermore, we find that the VRECON GHG-boosting effect can be mitigated by combining wind and solar power. We argue that, for GHG abatement, policymakers should require the proper mix of wind and solar power in renewable portfolio standards and control nuclear power's retirement pace to match the progress of VRE growth.

Electricity systems in the limit of free solar photovoltaics and continent-scale transmission.

Solar photovoltaics, with sufficient power generation potential, low-carbon footprint, and rapidly declining costs, could supplant fossil fuels and help produce lower-cost net-zero emissions energy systems. Here we used an idealized linear optimization model, including free lossless transmission, to study the response of electricity systems to increasing prescribed amounts of solar power. Our results show that there are initially great benefits when providing solar power to the system, especially under deep decarbonization scenarios. The marginal value of additional solar power decreases substantially with increasing cumulative solar capacities. At costs near today's levels, the modeled zero-emission electricity system with free solar generation equaling twice the annual mean demand is more costly than a carbon-emitting natural-gas-based system supplying the same electricity demand with no solar. Taking full advantage of low-cost solar will depend on developing and deploying low-cost approaches to temporally shift either energy supply (e.g., storage) or electricity loads (e.g., load-shifting).

Understanding the complexity of existing fossil fuel power plant decarbonization.

Growing national decarbonization commitments require rapid and deep reductions of carbon dioxide emissions from existing fossil-fuel power plants. Although retrofitting existing plants with carbon capture and storage or biomass has been discussed extensively, yet such options have failed to provide evident emission reductions at a global scale so far. Assessments of decarbonization technologies tend to focus on one specific option but omit its interactions with competing technologies and related sectors (e.g., water, food, and land use). Energy system models could mimic such inter-technological and inter-sectoral competition but often aggregate plant-level parameters without validation, as well as fleet-level inputs with large variability and uncertainty. To enhance the accuracy and reliability of top-down optimization models, bottom-up plant-level experience accumulation is of vital importance. Identifying sweet spots for plant-level pilot projects, overcoming the technical, financial, and social obstacles of early large-scale demonstration projects, incorporating equity into the transition, propagating the plant-level potential to generate fleet-level impacts represent some key complexity of existing fossil-fuel power plant decarbonization challenges that imposes the need for a serious re-evaluation of existing fossil fuel power plant abatement in energy transition.

Large-scale stationary hydrogen storage via liquid organic hydrogen carriers.

Large-scale stationary hydrogen storage is critical if hydrogen is to fulfill its promise as a global energy carrier. While densified storage via compressed gas and liquid hydrogen is currently the dominant approach, liquid organic molecules have emerged as a favorable storage medium because of their desirable properties, such as low cost and compatibility with existing fuel transport infrastructure. This perspective article analytically investigates hydrogenation systems' technical and economic prospects using liquid organic hydrogen carriers (LOHCs) to store hydrogen at a large scale compared to densified storage technologies and circular hydrogen carriers (mainly ammonia and methanol). Our analysis of major system components indicates that the capital cost for liquid hydrogen storage is more than two times that for the gaseous approach and four times that for the LOHC approach. Ammonia and methanol could be attractive options as hydrogen carriers at a large scale because of their compatibility with existing liquid fuel infrastructure. However, their synthesis and decomposition are energy and capital intensive compared to LOHCs. Together with other properties such as safety, these factors make LOHCs a possible option for large-scale stationary hydrogen storage. In addition, hydrogen transportation via various approaches is briefly discussed. We end our discussions by identifying important directions for future research on LOHCs.