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At least 1,171 records · Page 65

Agriculture, Land Use, Energy and Carbon Emission Impacts of Global Biofuel Mandates to Mid-Century

Three potential future scenarios of expanded global biofuel production are presented here utilizing the GCAM integrated assessment model. These scenarios span a range that encompasses on the low end a continuation of existing biofuel production policies to two scenarios that would require an expansion of current targets as well as an extension of biofuels targets to other regions of the world. Conventional oil use is reduced by 4-8% in the expanded biofuel scenarios, which results in a decrease of in CO2 emissions on the order of 1-2 GtCO2/year by mid-century from the global transportation sector. The regional distribution of crop production is relatively unaffected, but the biofuels targets do result in a marked increase in the production of conventional crops used for energy. Producer prices of sugar and corn reach levels about 12% and 7% above year 2005 levels, while the increased competition for land causes the price of food crops such as wheat, although not used for bioenergy in this study, to increase by 1 to 2%. The amount of land devoted to growing all food crops and dedicated bioenergy crops is increased by about 10% by 2050 in the High biofuel case, with concurrent decreases in other uses of land such as forest and pasture. In both of the expanded biofuels cases studied, there is an increase in net cumulative carbon emissions for the first couple of decades due to these induced land use changes. However, the difference in net cumulative emissions from the biofuels expansion decline by about 2035 as the reductions in energy system emissions exceed further increases in emissions from land use change. Even in the absence of a policy that would limit emissions from land use change, the differences in net cumulative emissions from the biofuels scenarios reach zero by 2050, and are decreasing further over time in both cases.

Biofuels↗

Hybridizing a geothermal power plant with concentrating solar power and thermal storage to increase power generation and dispatchability

Geothermal power plants often deploy less than their full power capacity due to declining geothermal resources. Integrating heat from a concentrating solar power (CSP) collector field increases the power output at low cost. This article considers five methods of solar heat addition in a double-flash geothermal plant. The most promising solution converts solar heat into electrical work with an efficiency of 24.3%. The economic feasibility and optimal sizing of the solar field and thermal stores are evaluated. A hybrid plant that increases power generation from 22 to 24 MWe has a Levelized Cost of Electricity (LCOE) of 0.07 +/- 0.01 $/kWhe. Adding three hours of storage increases the LCOE to 0.08 +/- 0.01 $/kWhe. Photovoltaic systems are considered to be a low-cost renewable technology, but an equivalent photovoltaic system with battery storage costs 0.15 +/- 0.07 $/kWhe due to the high cost and replacement rate of batteries compared to thermal storage. The hybrid plant also has a lower LCOE than a conventional CSP plant. If the dispatchability that thermal storage provides is rewarded with higher electricity prices, calculations indicate storage becomes an attractive investment when discharged power receives 1.75 times the typical price of electricity.

15 GEOTHERMAL ENERGY↗

Techno-economic analysis of producing solid biofuels and biochar from forest residues using portable systems

Wildfires are becoming extreme and more frequent because of increased fuel loads in the forest and extended dry conditions. Prevention of wildfire by fuel treatment methods will generate forest residues in large volumes, which in addition to available logging residues, can be used to produce biofuels and bioproducts. In this study, the techno-economic assessment of three portable systems to produce woodchips briquettes (WCB), torrefied-woodchips briquettes (TWCB) and biochar from forest residues were evaluated using pilot-scale experimental data. A discounted cash flow rate of return method was used to estimate minimum selling prices (MSPs) for each product, to conduct sensitivity analyses, and to identify potential cost-reduction strategies. Using a before-finance-and-tax 16.5% nominal required return on investment, and a mean transport distance of 200 km, the estimated delivered MSPs per oven-dry metric ton (ODMT) of WCB, TWCB, and biochar were $162, $274, and $1044 respectively. The capital investment (16–30%), labor cost (23–28%), and feedstock cost (10–13%) without stumpage cost were the major factors influencing the MSP of solid biofuels and biochar. However, the MSPs of WCB, TWCB, and biochar could be reduced to $65, $145, and $470/ODMT respectively with technologically improved portable systems. In addition, the MSPs of solid biofuels and biochar could be further reduced by renewable energy and carbon credits, if the greenhouse gas (GHG) reduction potentials are quantified and remunerated. In conclusion, portable systems could be economically feasible to use forest residues and make useful products at current market prices while simultaneously reducing potential wildfires and GHG emissions.

09 BIOMASS FUELS↗

Techno-economic optimization of shale gas to dimethyl ether production processes via direct and indirect synthesis routes

The shale gas to dimethyl ether process via direct synthesis route with a syngas H2/CO=1 has a higher dimethyl ether yield than that via indirect synthesis route. However, the direct synthesis route involves various energy and capital-intensive processes, such as the complicated dimethyl ether separation process, and the CO2 recycle and comprssion process. In this study, a techno-economic analysis of the shale gas to dimethyl ether process via direct and indirect synthesis routes is performed using Aspen Process Economic Analyzer based on the rigorous process model developed in Aspen Plus. Effects of different CO2 removal technologies and dimethyl ether synthesis technologies from syngas are evaluated. Both, direct and indirect plants are optimized in Aspen Plus equation-oriented environment using the rigorous process models. The effects of key design parameters (i.e. H2/CO in the syngas) as well as investment parameters (i.e. prices of raw materials, products, and utilities, plant scale) on the process economics as been evaluated. The direct dimethyl ether synthesis route processing a syngas with H2/CO =1 and using the Rectisol process for CO2 capture has the highest overall thermal efficiency on the lower heat value basis is found to be much lower than the current U.S. market diesel price indicating the feasibility of the process.

Mevawala, Chirag↗

Bioalcohol production from acidogenic products via a two-step process: A case study of butyric acid to butanol

This article presents the full study (lab-scale experimental study and large-scale techno-economic analysis) results of a two-step catalytic process for the conversion of organic waste–derived butyric acid to butanol. Butanol from biomass resources like organic waste promise to become an attractive and sustainable fuel and industrial precursor due to an increase in greenhouse gas content in the atmosphere. Therefore, research in this field is important for energy applications and reduction in greenhouse gas emissions. In this regard, a two-step process was applied in this study to produce butanol from butyric acid that can potentially be derived from organic waste. The two-step process consists of the (1) esterification of butyric acid to methyl butyrate and (2) hydrogenolysis of this methyl butyrate to butanol. The first reaction, esterification of butyric acid, was optimized using carbon-based catalysts. The production of butanol from methyl butyrate via hydrogenolysis was investigated using bimetallic Pt–Co catalysts. The hydrogenolysis of methyl butyrate on these catalysts under optimal conditions of 250 °C, 5 MPa H 2 , and a feed/catalyst weight ratio of 11.2 led to 54.1% selectivity toward 1-butanol. Based on the experimental results, an integrated process simulation model was developed to determine the economic potential of the two-step production of butanol from butyric acid. Using this model, the techno-economic feasibility of the two-step process was analyzed. Here, the minimum selling price (MSP) of 1-butanol produced from butyric acid using this process was US dollars 3.388 per gallon of gasoline equivalent (GGE). This MSP is in the range of recent biofuel market prices of US dollars 2.03/GGE to US dollars 3.83/GGE.

09 BIOMASS FUELS↗

A Model for Evaluating the Configuration and Dispatch of PV Plus Battery Power Plants

An open-source model was developed to optimize energy storage operation for photovoltaic- (PV-) plus-battery systems with AC-coupled and DC-coupled configurations. It includes the ability to use forecast energy prices to optimize battery charge and discharge on a rolling time horizon. The model allows for exploration of different configurations, including capital costs, inverter performance, dispatch flexibility, and capturing otherwise clipped energy for the DC-coupled system. The model can run 20 full years of hourly data in approximately two seconds, allowing comparison of a large number of configurations. We applied the model in a test case demonstrating reduced inverter clipping for DC-coupled systems and yielded slightly higher overall value than AC-coupled systems, with an approximately 2 percent increase in internal rate of return or benefit/cost ratio. Our results show that at current estimated prices for lithium-ion battery systems, large-scale PV-plus-battery plants are economically viable under the right conditions, with the configuration playing a role in system flexibility and performance. This model provides the ability for project developers, industry professionals, and researchers to use readily available software to quickly evaluate and design these systems.

41 EE - Solar Energy Technologies Office (EE-4S)↗

Technologies and policies to decarbonize global industry: Review and assessment of mitigation drivers through 2070

Fully decarbonizing global industry is essential to achieving climate stabilization, and reaching net zero greenhouse gas emissions by 2050–2070 is necessary to limit global warming to 2 °C. This paper assembles and evaluates technical and policy interventions, both on the supply side and on the demand side. It identifies measures that, employed together, can achieve net zero industrial emissions in the required timeframe. Key supply-side technologies include energy efficiency (especially at the system level), carbon capture, electrification, and zero-carbon hydrogen as a heat source and chemical feedstock. There are also promising technologies specific to each of the three top-emitting industries: cement, iron & steel, and chemicals & plastics. These include cement admixtures and alternative chemistries, several technological routes for zero-carbon steelmaking, and novel chemical catalysts and separation technologies. Crucial demand-side approaches include material-efficient design, reductions in material waste, substituting low-carbon for high-carbon materials, and circular economy interventions (such as improving product longevity, reusability, ease of refurbishment, and recyclability). Strategic, well-designed policy can accelerate innovation and provide incentives for technology deployment. High-value policies include carbon pricing with border adjustments or other price signals; robust government support for research, development, and deployment; and energy efficiency or emissions standards. These core policies should be supported by labeling and government procurement of low-carbon products, data collection and disclosure requirements, and recycling incentives. In implementing these policies, care must be taken to ensure a just transition for displaced workers and affected communities. Similarly, decarbonization must complement the human and economic development of low- and middle-income countries.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

The value of in-reservoir energy storage for flexible dispatch of geothermal power

Geothermal systems making use of advanced drilling and well stimulation techniques have the potential to provide tens to hundreds of gigawatts of clean electricity generation in the United States by 2050. With near-zero variable costs, geothermal plants have traditionally been envisioned as providing “baseload” power, generating at their maximum rated output at all times. However, as variable renewable energy sources (VREs) see greater deployment in energy markets, baseload power is becoming increasingly less competitive relative to flexible, dispatchable generation and energy storage. Herein we conduct an analysis of the potential for future geothermal plants to provide both of these services, taking advantage of the natural properties of confined, engineered geothermal reservoirs to store energy in the form of accumulated, pressurized geofluid and provide flexible load-following generation. We develop a linear optimization model based on multi-physics reservoir simulations that captures the transient pressure and flow behaviors within a confined, engineered geothermal reservoir. We then optimize the investment decisions and hourly operations of a power plant exploiting such a reservoir against a set of historical and modeled future electricity price series. Further, we find that operational flexibility and in-reservoir energy storage can significantly enhance the value of geothermal plants in markets with high VRE penetration, with energy value improvements of up to 60% relative to conventional baseload plants operating under identical conditions. Across a range of realistic subsurface and operational conditions, our modeling demonstrates that confined, engineered geothermal reservoirs can provide large and effectively free energy storage capacity, with round-trip storage efficiencies comparable to those of leading grid-scale energy storage technologies. Optimized operational strategies indicate that flexible geothermal plants can provide both short- and long-duration energy storage, prioritizing output during periods of high electricity prices. Sensitivity analysis assesses the variation in outcomes across a range of subsurface conditions and cost scenarios.

15 GEOTHERMAL ENERGY↗

Plant-wide modeling and techno-economic analysis of a direct non-oxidative methane dehydroaromatization process via conventional and microwave-assisted catalysis

Direct non-oxidative methane dehydroaromatization (DHA) process via conventional and microwave (MW)-assisted thermo-catalytic catalysis is studied. Rate models for methane DHA reactions, including the effect of catalyst deactivation, are developed by using the in-house experimental data. Model results for gas concentration profile and catalyst deactivation are in good agreement with the experimental data. This rate model is then used for the development of dynamic multi-scale, multi-physics commercial-scale reactor models. Total number of fixed bed reactors desired for a cyclic steady state process is estimated. Plant-wide models are then developed for conventional and MW-assisted processes for producing products of desired specifications. Techno-economic analysis of the methane DHA process is undertaken. Economics of these methane DHA processes are compared with the typical multi-step natural gas to aromatics production process via methanol synthesis. Sensitivity of internal rate of return (IRR) and net present value (NPV) to various economic and process parameters such as plant scale, desired rate of return, reactor cost, feedstock and utility cost, catalyst variable cost, and MW reactor cost is studied. Here, electric equivalent efficiency of the conventional methane DHA process is found to be 69.2 % and 67.3 % at 750 °C and 800 °C, respectively, while the MW-assisted methane DHA process has the electric equivalent efficiency of 48.9 % at 800 °C. IRRs of the conventional methane DHA process at 750 °C and 800 °C, and MW-assisted process are 15.2 %, 17.5 %, and 18.8 %, respectively for a methane feed flowrate of 19,782 kg/h, while the IRR of the multi-step natural gas to aromatics production process is estimated to be 0 % for the same plant scale. Impact of change in the methane price, electricity price, and catalyst cost is found to be considerable on the process economics, while the cost of the MW reactor is found to have negligible impact.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Opportunities for wave energy in bulk power system operations

Wave energy resources have high, yet largely untapped potential as candidate generation technology. In this paper, we perform a data-driven analysis to characterize the impact of wave energy integration on bulk-scale power systems and market operations. Through data-driven sensitivity studies centered on an optimization-based production cost modeling formulation, our work characterizes the inflection point beyond which wave integration starts impacting power system operations, considering present day transmission infrastructure. Furthermore, our analysis also considers the joint effects of wave energy integration and system-wide transmission expansion. Finally, potential resilience scenarios such as wildfire-driven transmission contingencies and heat wave events are investigated, whereby the contributions of grid-integrated wave energy in alleviating the effects of the resilience events are analyzed. As our demonstration test bed, we consider a reduced-order network topology for the U.S. Western Interconnection with wave energy generation integrated at carefully selected sites across the coastal areas of Washington, Oregon, and northern California. Our results indicate that over a representative year of operations, wave energy integration systematically reduces locational marginal prices (LMPs) of energy and price volatility, especially during periods of high wave resource availability (winter months for the U.S. west coast). Average, maximum, and minimum of hourly LMPs over a typical year of operation was reduced by 2.95, 51.28, and 1.13 $\$$/MWh respectively (over a baseline scenario with no wave energy integration), when the selected network model had a total of 5000 MW wave power installed capacity during the representative year of study. The effects of wave energy integration can remain localized with existing transmission infrastructure (identified to be most pronounced in the Pacific Northwest region in the example we studied). However, with concurrent transmission expansion, the impacts of wave energy integration are likely to have a higher geographical spread. Our results also indicate that wave energy may be able to assist power system operations during resilience events such as major transmission contingencies and heat wave events, although such benefits might be dependent on factors such as proximity of affected area to wave resources, availability of adequate resource potential and adequate transmission capacity.

16 TIDAL AND WAVE POWER↗

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 (plus-minus sign) 1.09M USD and 104.99M (plus-minus sign) 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.

25 ENERGY STORAGE↗

Investigating the effects of cooperative transmission expansion planning on grid performance during heat waves with varying spatial scales

There is growing recognition of the advantages of interregional transmission capacity to decarbonize electricity grids. A less explored benefit is potential performance improvements during extreme weather events. This study examines the impacts of cooperative transmission expansion planning using an advanced modeling chain to simulate power grid operations of the United States Western Interconnection in 2019 and 2059 under different levels of collaboration between transmission planning regions. Two historical heat waves in 2019 with varying geographical coverage are replayed under future climate change in 2059 to assess the transmission cooperation benefits during grid stress. The results show that cooperative transmission planning yields the best outcomes in terms of reducing wholesale electricity prices and minimizing energy outages both for the whole interconnection and individual transmission planning regions. Compared to individual planning, cooperative planning reduces wholesale electricity prices by 64.3 % and interconnection-wide total costs (transmission investments + grid operations) by 34.6 % in 2059. It also helps decrease greenhouse gas emissions by increasing renewable energy utilization. However, the benefits of cooperation diminish during the widespread heat wave when all regions face extreme electricity demand due to higher space cooling needs. Despite this, cooperative transmission planning remains advantageous, particularly for California Independent System Operator with significant diurnal solar generation capacity. This study suggests that cooperation in transmission planning is crucial for reducing costs and increasing reliability both during normal periods and extreme weather events. It highlights the importance of optimizing the strategic investments to mitigate challenges posed by wider-scale extreme weather events of the future.

24 POWER TRANSMISSION AND DISTRIBUTION↗

An empirical analysis of supply offers in the ERCOT operating reserves markets

Here, this paper seeks to improve theoretical and empirical understanding of supplier dynamics in wholesale markets for operating reserves, which have been understudied compared to energy markets. We begin by identifying several economic factors that unit owners may consider when submitting offers into operating reserves auctions in two-stage, co-optimized markets common across much of North America. Next, we analyze historical offer data from the Electric Reliability Council of Texas (ERCOT) market to assess whether actual reserve market behavior aligns with expectations based on economic theory, as well as with commonly used assumptions in electricity market modeling efforts. We find that the aggregate supply of operating reserves in ERCOT varies meaningfully over time, becoming more expensive during summer afternoons, which is consistent with theoretical expectations but contradicts the typical modeling assumption of temporally invariant reserve offers. Analysis of offers made by individual units uncovers additional insights, such as the existence of large offer pattern differences by unit owner and the tendency of battery storage units to submit very low offer prices. We conclude by discussing how our findings can be integrated into electricity market modeling assumptions to improve alignment with observed operating reserve offer inputs and pricing outcomes.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Broad range material-to-system screening of metal–organic frameworks for hydrogen storage using machine learning

Hydrogen is pivotal in the transition to sustainable energy systems, playing major roles in power generation and industrial applications. Metal–organic frameworks (MOFs) have emerged as promising mediums for efficient hydrogen storage. However, identifying potential candidates for deployment is challenging due to the vast number of currently available synthesized MOFs. This study integrates molecular simulations, machine learning, and techno-economic analysis to evaluate the performance of MOFs across broad operation conditions for hydrogen storage applications. While previous screenings of MOF databases have predominantly emphasized high hydrogen capacities under cryogenic conditions, this study reveals that optimal temperatures and pressures for cost minimization depend on the raw price of the MOF. Specifically, when MOFs are priced at $15/kg, among the 9720 MOFs tested, 9692 MOFs achieve the lowest cost at temperatures between 170 K and 250 K and a pressure of 150 bar. Under these optimal conditions, 362 MOFs deliver a lower levelized cost of storage than 350 bar compressed gas hydrogen storage. Furthermore, this study reveals key material properties that result in low system cost, such as high surface areas (>3000 m2/g), large void fractions (>0.78), and large pore volumes (>1.1 cm3/g).

Hydrogen storage↗