An Assessment of the Role Mass Market Demand Response Could Play in Contributing to the Management of Variable Generation Integration Issues
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Here, the catalytic conversion of CO 2 into industrially relevant chemicals is one strategy for mitigating greenhouse gas emissions. Along these lines, electrochemical CO 2 conversion technologies are attractive because they can operate with high reaction rates at ambient conditions. However, electrochemical systems require electricity, and CO 2 conversion processes must integrate with carbon-free, renewable-energy sources to be viable on larger scales. We utilize Au 25 nanoclusters as renewably powered CO 2 conversion electrocatalysts with CO 2 → CO reaction rates between 400 and 800 L of CO 2 per gram of catalytic metal per hour and product selectivities between 80 and 95%. These performance metrics correspond to conversion rates approaching 0.8–1.6 kg of CO 2 per gram of catalytic metal per hour. We also present data showing CO 2 conversion rates and product selectivity strongly depend on catalyst loading. Optimized systems demonstrate stable operation and reaction turnover numbers (TONs) approaching 6 × 10 6 mol CO 2 molcatalyst–1 during a multiday (36 hours total hours) CO 2 electrolysis experiment containing multiple start/stop cycles. TONs between 1 × 10 6 and 4 × 10 6 molCO 2 molcatalyst–1 were obtained when our system was powered by consumer-grade renewable-energy sources. Daytime photovoltaic-powered CO 2 conversion was demonstrated for 12 h and we mimicked low-light or nighttime operation for 24 h with a solar-rechargeable battery. This proof-of-principle study provides some of the initial performance data necessary for assessing the scalability and technical viability of electrochemical CO 2 conversion technologies. Specifically, we show the following: (1) all electrochemical CO 2 conversion systems will produce a net increase in CO 2 emissions if they do not integrate with renewable-energy sources, (2) catalyst loading vs activity trends can be used to tune process rates and product distributions, and (3) state-of-the-art renewable-energy technologies are sufficient to power larger-scale, tonne per day CO 2 conversion systems.
Replacement of petroleum-derived monomers with renewable alternatives is an integral part of the sustainable polymer framework. Research in this area involves the search for bio-based or recycled starting materials for traditional polymers, as well as investigations into new materials accessible from renewable feedstocks. Focusing on the latter, we studied the properties of polyamides synthesized from γ-methyl-ε-caprolactam through anionic ring-opening polymerization by an activated monomer mechanism. Here, the amorphous homopolymer presents high stiffness (Young’s modulus, ≈3 GPa), strength (stress at break, ≈80 MPa) and toughness under dry (low humidity) conditions, high ductility (strain at break, ≈1100%) in humid environments, optical clarity, and excellent processability due to its non-crystallizable nature and solubility in common organic solvents. Copolymerization with ε-caprolactam allows tailoring the mechanical properties and crystallinity in the resultant copolymers and provides new opportunities for advanced manufacturing and other applications.
This is a summary of the roles of power electronics in renewable energy deployment.
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Recent efforts to reduce energy consumption and greenhouse gas emissions have resulted in the development of sustainable, smart districts with highly energy efficient buildings, renewable distributed energy resources (DERs), and support for alternative modes of transportation. However, there is typically little if any coordination between the district developers and the local utility. Most attention is paid to the district's annual net load and generation without considering their instantaneous imbalance or the connecting network's state. This presents an opportunity to learn lessons from the design of distribution feeders for districts characterized by low loads and high penetrations of DERs that can be applied to the distribution grid at large. The aim of this overview is to summarize current practices in sustainable district planning as well as advances in modeling and design tools for incorporating the power distribution system into the district planning process. Recent developments in the modeling and optimization of district power systems, including their coordination with multi-energy systems and the impact of high penetration levels of renewable energy, are introduced. Sustainable districts in England and Japan are reviewed as case studies to illustrate the extent to which distribution system planning has been considered in practice. Finally, newly developed building-to-grid modeling tools that can facilitate coordinated district and power system design with utility involvement are introduced, along with suggestions for future research directions.
Climate change has prompted many communities to set targets for carbon-free power supplies, but they often lack data-driven strategies to achieve them. We present a comprehensive analysis of an entirely renewable electric power system that can maintain operating reliability and resource adequacy using detailed models of the city of Los Angeles power grid. In consultation with the operating utility, the Los Angeles Department of Water and Power (LADWP), and the local community, we develop four supply scenarios across three demand projections to analyze which types of infrastructure and operational changes would achieve reliable electricity at least cost. We find that a reliable, 100%-renewable power system yielding more than $1 billion annually in health and climate co-benefits is achievable. Solar can supply most future energy needs, while combustion turbines that use renewable, storable carbon-neutral fuels are key to maintaining reliability. This study provides a replicable methodology that other jurisdictions globally can follow.
This preface introduces the special section on the assessment of wind and solar in global low-carbon energy scenarios. The special section documents the results of a coordinated research effort to improve the representation of variable renewable energies (VRE), including wind and solar power, in Integrated Assessment Models (IAM) and presents an overview of the results obtained in the underlying coordinated model inter-comparison exercise.
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Electricity generation from wind power and other renewable energy sources is increasing, and their variability introduces new challenges to the power system. The emergence of smart grid technologies in recent years has seen a paradigm shift in redefining the electrical system of the future, in which controlled response of the demand side is used to balance fluctuations and intermittencies from the generation side. This paper presents a modeling framework for an integrated electricity system where loads become an additional resource. The agent-based model represents a smart grid power system integrating generators, transmission, distribution, loads and market. The model incorporates generator and load controllers, allowing suppliers and demanders to bid into a Real-Time Pricing (RTP) electricity market. The modeling framework is applied to represent a physical demonstration project conducted on the Olympic Peninsula, Washington, USA, and validation simulations are performed using actual dynamic data. Wind power is then introduced into the power generation mix illustrating the potential of demand response to mitigate the impact of wind power variability, primarily through thermostatically controlled loads. The results also indicate that effective implementation of Demand Response (DR) to assist integration of variable renewable energy resources requires a diversity of loads to ensure functionality of the overall system.
In line with the Sustainable D.C. 2.0 plan to combat climate change, Washington D.C. aims to decrease its greenhouse gas emissions by 100% by 2050. As solar energy is a clean, renewable energy form, its integration into the region’s power grids lowers energy costs and incentivizes sustainable development. We partnered with the Washington D.C. Department of Energy & Environment (DOEE) to determine how urban areas surrounding D.C. can better be incorporated into decisions regarding renewable energy policy. The team used NASA’s Prediction of Worldwide Energy Resources (POWER) solar data and a Light Detection and Ranging (LiDAR) derived digital surface model, to estimate and visualize rooftop solar potential for Maryland’s Prince George’s and Montgomery counties. POWER provided solar irradiance data adjusted for tilt angle while the digital surface model contributed aspect and slope data. This methodology factored out areas that were unsuitable for solar panel installation while displaying areas that possess a high potential for energy return. The team found the total rooftop solar potential for the study area to be almost 32 million kW, which is equivalent to roughly 660 kW per building. The methodology used to generate the solar potential maps can be applied to other regions of the country seeking to efficiently utilize solar energy. The end users at the DOEE can use our resulting solar potential map and data table to effectively target buildings that have the highest potential to generate solar energy.
This report examines the opportunities, challenges, and costs associated with renewable energy implementation in Alaska and provides strategies that position Alaska's accumulating knowledge in renewable energy development for export to the rapidly growing energy/electric markets of the developing world.
The uncertainties resulting from the escalating penetration of renewable energy resources pose severe challenges to the efficient operation of modern power systems. Hydroelectricity is characterized by its flexibility, controllability, and reliability, and thus becomes one of the most ideal energy resources to hedge against such uncertainties. This paper studies the mid-term integrated generation and maintenance scheduling of a cascaded hydroelectric system (CHS) consisting of multiple cascaded reservoirs and hydroelectric units. To precisely describe the mid-term water regulation policies, the hydraulic coupling relationship and water-energy nexus of CHS are incorporated into the proposed optimization model. The uncertainties of natural water inflow and the power outputs of wind/solar energy generation are taken into consideration and captured via a stochastic process modeled by a scenario tree. A multistage stochastic optimization (MSO) approach is developed to coordinate the complementary operations of multiple energy resources, by optimizing the mid-term water resource management, generation scheduling, and maintenance scheduling of CHS. The proposed MSO model is formulated as a large-scale mixed-integer linear program that presents significant computational intractability. To address this issue, a tailored Benders decomposition algorithm is developed. Two real-world case studies are conducted to demonstrate the capability and characteristics of the proposed model and algorithm. The computational results show that the proposed MSO model can exploit the flexibility of hydroelectricity to efficiently respond to variable wind and solar power, and reserve water resources for the generation in peak months to reduce the consumption of fossil fuel. Furthermore, the proposed solution approach also exhibits promising computational efficiency when handling large-scale models.
The Renewable Electricity Futures Study (RE Futures) provides an analysis of the grid integration opportunities, challenges, and implications of high levels of renewable electricity generation for the U.S. electric system. The study is not a market or policy assessment. Rather, RE Futures examines renewable energy resources and many technical issues related to the operability of the U.S. electricity grid, and provides initial answers to important questions about the integration of high penetrations of renewable electricity technologies from a national perspective. RE Futures results indicate that a future U.S. electricity system that is largely powered by renewable sources is possible and that further work is warranted to investigate this clean generation pathway.
The national interest in a broad class of problems loosely characterized as the smart grid is rapidly growing. At its core, the smart grid is the modernization of our existing electric power systems through improvements in efficiency, increased robustness and resiliency, integration of time-variable renewable generation, and reduction of environmental impacts. To date, the focus of most commercial entities has been on development of hardware such as smart meters and green technologies. However, with the exception of a handful of academic researchers, there has been limited research on optimization, control and more broadly, the information science required to effectively utilize this hardware. Our proposal targets development of the basic information science that will effectively bridge this gap. Using our expertise in information theory, network analysis, infrastructure analysis and power engineering, we will develop new algorithms for optimal design of the nation's next generation power transmission and distribution system that address the realities and challenges of the future grid. We focus on three core information science challenges in Grid Design, Grid Control and Grid Stability by considering a set of challenging problems. First, we study efficient and robust integration of geographically widespread renewable generation by solving large, cutting-edge optimization problems that incorporate difficult constraints imposed by the transmission of electrical power. Second, we consider two load balancing problems in the low-voltage distribution grid: development of robust and efficient distributed control techniques and algorithms based on queuing theory. These tools will enable high penetration of small-scale distributed generation and plug-in hybrid vehicles with limited or no communications. We will also develop efficient control algorithms for maintaining an operational distribution grid via switching of redundant lines. Third, we will develop a preventive toolbox capable of detecting instabilities and failures prior to their occurrence. Damaging failures and cascading outages, which can result in billions of dollars worth of damage, have substantial economic consequences. We will focus on estimating the probability of these outages, identifying their signatures and precursors, and developing detection algorithms for alerting the transmission grid operator. The new challenges in IS&T for smart grids require coherent advances in analysis and control, stability and reliability metrics, state estimation, data aggregation and assimilation, and communication middleware for the grid as well as understanding consumer response.
This fact sheet highlights the Smart Home Test Bed capability at the Energy Systems Integration Facility. The National Renewable Energy Laboratory (NREL) is working on one of the new frontiers of smart home research: finding ways for smart home technologies and systems to enhance grid operations in the presence of distributed, clean energy technologies such as photovoltaics (PV). To help advance this research, NREL has developed a controllable, flexible, and fully integrated Smart Home Test Bed.
The Interstate Renewable Energy Council (IREC) designed the “Integration of Solar Training into Allied Professional Development Platforms” project to surmount barriers to the expansion of solar technology caused by gaps in knowledge impacting on-the-job performance of allied professionals. At project start, questionnaires deployed nationally indicated that only 9% of firefighters felt certain they could shut down a PV system to the extent possible, and only a third of code officials thought they could even discern the difference between a PV and solar thermal system. Therefore, the project objective was to measurably and significantly increase the number of code officials and fire service professionals with solar knowledge directly applicable to their job function. IREC identified specific gaps in current knowledge, and integrated research-proven adult learning principles and technology solutions to enable a cost-effect but impactful reach. The project design ensured that solar training is a continuing component of the targeted sector professional development toolkit. To this end, the key partners recruited and cultivated were existing, trusted training partners in the targeted sectors: International Code Council Solar Rating and Certification Corporation (ICC-SRCC), International Association of Electrical Inspectors (IAEI), International Association of Fire Fighters (IAFF) and National Association of State Fire Marshals (NASFM). During the project, IREC held 79 courses in 25 states that trained 4,156 people, offered a PV in the 2017 National Electric Code webinar attended by 787 people, developed on-line training for code officials with 2,298 on-line learners, and developed an on-line training for firefighters with 4,930 on-line learners. In addition, the project participated in 28 conferences and reached over 537,000 professionals with solar information.
Through the Hawaii Renewable Energy Development Venture, the State of Hawaii may make progress toward a meaningful level of energy self-sufficiency and provides a testing ground for the development of technologies to convert, store and transport there renewable energy sources for integration with the island electrical grids and transportation systems.