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At least 307 records · Page 17

Parallel hybrid quantum-classical machine learning for kernelized time-series classification

Supervised time-series classification garners widespread interest because of its applicability throughout a broad application domain including finance, astronomy, biosensors, and many others. Here, in this work, we tackle this problem with hybrid quantum-classical machine learning, deducing pairwise temporal relationships between time-series instances using a timeseries Hamiltonian kernel (TSHK). A TSHK is constructed with a sum of inner products generated by quantum states evolved using a parameterized time evolution operator. This sum is then optimally weighted using techniques derived from multiple kernel learning. Because we treat the kernel weighting step as a differentiable convex optimization problem, our method can be regarded as an end-to-end learnable hybrid quantum-classical-convex neural network, or QCC-net, whose output is a data set-generalized kernel function suitable for use in any kernelized machine learning technique such as the support vector machine (SVM). Using our TSHK as input to a SVM, we classify univariate and multivariate time-series using quantum circuit simulators and demonstrate the efficient parallel deployment of the algorithm to 127-qubit superconducting quantum processors using quantum multi-programming.

97 MATHEMATICS AND COMPUTING↗

Continuous-variable quantum Boltzmann machine

Here, we propose a continuous-variable quantum Boltzmann machine (CVQBM) using a powerful energy-based neural network. It can be realized experimentally on a continuous-variable (CV) photonic quantum computer. We used a CV quantum imaginary time evolution (QITE) algorithm to prepare the essential thermal state and then designed the CVQBM to proficiently generate continuous probability distributions. We applied our method to both classical and quantum data. Using real-world classical data, such as synthetic-aperture radar (SAR) images, we generated probability distributions. For quantum data, we used the output of CV quantum circuits. We obtained high fidelity and low Kullback–Leibler (KL) divergence showing that our CVQBM learns distributions from given data well and generates data sampling from that distribution efficiently. We also discussed the experimental feasibility of our proposed CVQBM. Our method can be applied to a wide range of real-world problems by choosing an appropriate target distribution (corresponding to, e.g., SAR images, medical images, and risk management in finance). Moreover, our CVQBM is versatile and could be programmed to perform tasks beyond generation, such as anomaly detection.

SAR images↗

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↗

Forecasting Peak Electricity Demand for Los Angeles Considering Higher Air Temperatures due to Climate Change

We report that Los Angeles County (LAC) is a large urbanized region with 9.7 million residents (as of 2010) and aging infrastructure. Population forecasts indicate that LAC will become home to an additional 1.2-3.1 million residents through 2060. Additionally, climate forecasts based upon representative concentration pathway (RCP) scenarios 4.5 and 8.5 indicate that average air temperatures will increase by 1-4 degrees C (2-7 degrees F) in the region. Both of these factors are expected to result in higher summertime peak electricity demand due to growth in the number of buildings, the percentage of installed air conditioners (ACs), and the additional cooling load on those air conditioners. In order to understand potential power reliability issues, and support infrastructure planning efforts, a long-term peak demand forecast was developed using hourly residential and commercial (R&C) building energy models. Peak hour electricity demand was estimated to increase from 9.5 to 12.8 GW for R&C sectors, to 13.0-17.3 GW (2-36%) and 14.7-19.2 GW (16-51%) by 2060 for the population forecasts from the California Department of Finance and the Southern California Association of Governments respectively. While marginal increases in ambient air temperature due to climate change accounted for only 4-8% of future increases in peak demand, differences in annual maximum temperatures within the 20-year periods affected results by 40-66% indicating a high sensitivity to heat waves. Population growth of at least 1 million people is anticipated to occur mostly in the northern cities of Palmdale, Lancaster, and Santa Clarita, bringing an additional 0.4-1 GW of peak demand in those regions. Building and AC efficiency are anticipated to improve as national and state efficiency standards increase, and as older, less efficient units are replaced; this could offset some of the projected increases in peak demand. Furthermore, development of shared wall, multi-family dwelling units could enable population growth of up to 3 million people without increasing peak demand.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Techno-economic analysis of carbon dioxide capture from low concentration sources using membranes

Rising carbon dioxide (CO 2 ) levels in the atmosphere lead to global warming, causing climate change. As such, carbon capture has become necessary to slow the increase and reduce CO 2 levels in the atmosphere. Point source emissions have a wide range of CO 2 concentrations, but emissions below 3% CO 2 have mostly been ignored because Carbon capture from these sources has been viewed as costly and economically unsustainable. Membrane technologies are considered the most viable solution by virtue of more energy-efficient operation. Our group at Idaho National Laboratory (INL) has developed poly[bis((2-methoxyethoxy)ethoxy)phosphazene] (MEEP)-based carbon dioxide selective membranes with CO 2 /N 2 selectivity greater than 40 and CO 2 permeability greater than 450 Barrer. To understand the economics of carbon capture, a spreadsheet-based techno-economic analysis (TEA) model was developed to consider multiple parameters, including selectivity and permeability of the membranes, performance conditions such as the number of stages, module material, electricity price, membrane price, and capital financing. The cost of carbon capture in US $\$$/metric ton was calculated at various purities and compared with other membrane processes, cryogenic capture, solvent-based capture, and pressure swing adsorption-based capture. It was determined that a MEEP-based three-stage process had a capture cost of US $\$$ 50.1/metric ton for 99.8% purity CO 2 from a 1% CO 2 feed source in nitrogen (N 2 ). In conclusion, the capture cost using the best performing Pebax-based membrane was 464% higher, cryogenic capture was 60%–140% higher, pressure swing adsorption was 55%–165% higher, and chemical absorption was -10%–110% higher than MEEP-based membrane capture, respectively.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Equity implications of net-zero emissions: A multi-model analysis of energy expenditures across income classes under economy-wide deep decarbonization policies

With companies, states, and countries targeting net-zero emissions around midcentury, there are questions about how these targets alter household welfare and finances, including distributional effects across income groups. This paper examines the distributional dimensions of technology transitions and net-zero policies with a focus on welfare impacts across household incomes. The analysis uses a model intercomparison with a range of energy-economy models using harmonized policy scenarios reaching economy-wide, net-zero CO 2 emissions across the United States in 2050. Here we employ a novel linking approach that connects output from detailed energy system models with survey microdata on energy expenditures across income classes to provide distributional analysis of net-zero policies. Although there are differences in model structure and input assumptions, we find broad agreement in qualitative trends in policy incidence and energy burdens across income groups. Models generally agree that direct energy expenditures for many households will likely decline over time with reference and net-zero policies. However, there is variation in the extent of changes relative to current levels, energy burdens relative to reference levels, and electricity expenditures. Policy design, primarily how climate policy revenues are used, has first-order impacts on distributional outcomes. Net-zero policy costs, in both absolute and relative terms, are unevenly distributed across households, and relative increases in energy expenditures are higher for lowest-income households. However, we also find that recycled revenues from climate policies have countervailing effects when rebated on a per-capita basis, offsetting higher energy burdens and potentially even leading to net progressive outcomes. Model results also show carbon Laffer curves, where revenues from net-zero policies increase but then decline with higher stringencies, which can diminish the progressive effects of climate policies. We also illustrate how using annual income deciles for distributional analysis instead of expenditure deciles can overstate the progressivity of emissions policies by overweighting revenue impacts on the lowest-income deciles.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Optimized, Budget-constrained Monitoring Well Placement Using DREAM

Defining the ideal suite of monitoring technologies to be deployed at a carbon capture and storage (CCS) site presents a challenge to project developers, financers, insurers, regulators and other stakeholders. The monitoring, verification, and accounting (MVA) toolkit offers a suite of technologies to monitor an extensive range of parameters across a wide span of spatial and temporal resolutions, each with their own degree of sensitivity to changes in the parameter being monitored. Understanding how best to optimize MVA budgets to minimize the time to leak detection could help to address issues around project risks, and in turn help support broad CCS deployment. This paper presents a case study demonstrating an application of the Designs for Risk Evaluation and Management (DREAM) tool using an ensemble of CO 2 leakage scenarios taken from a previous study on leakage impacts to groundwater. Impacts were assessed and monitored as a function of pH, total dissolved solids (TDS), and trace metal concentrations of arsenic (As), cadmium (Cd), chromium (Cr), and lead (Pb). Using output from the previous study, DREAM was used to optimize monitoring system designs based on variable sampling locations and parameters. The algorithm requires the user to define a finite budget to limit the number of monitoring wells and technologies deployed, and then iterates well placement and sensor type and location until it converges on the configuration with the lowest time to first detection of the leak averaged across all scenarios. To facilitate an understanding of the optimal number of sampling wells, DREAM was used to assess the marginal utility of additional sampling locations. Based on assumptions about monitoring costs and replacement costs of degraded water, the incremental cost of each additional sampling well can be compared against its marginal value in terms of avoided aquifer degradation. Applying this method, DREAM identified the most cost-effective ensemble with 14 monitoring locations. Here, while this preliminary study applied relatively simplistic cost and technology assumptions, it provides an exciting proof-of-concept for the application of DREAM to questions of cost-optimized MVA system design that are informed not only by site-specific costs and technology options, but also by reservoir simulation results developed during site characterization and operation.

47 OTHER INSTRUMENTATION↗

Is the ecosystem service concept improving impact assessment? Evidence from recent international practice

Considering ecosystem services (ES) could foster innovation and improve environmental and social impact assessment (ESIA) practice, but is the potential being fulfilled? In order to investigate how ES have been treated in recent international practice, three questions are asked: (i) were the tasks of an ES analysis carried out? (ii) how is such analysis integrated with other analysis presented in the ESIA? (iii) does ES analysis result in additional or improved mitigation or enhancement measures? These research questions were unfolded into 15 auxiliary questions for reviewing five ESIA reports prepared for mining, hydroelectric and transportation infrastructure projects in Africa, Asia and South America. All cases incorporated ES into ESIA to meet a requirement of the International Finance Corporation's Performance Standards on Environmental and Social Sustainability. It was found that: (i) in only three cases most tasks recommended by current guidance were adopted (ii) all reports feature a dedicated ES chapter or section, but in three of them no evidence was found that the ES analysis was integrated within impact assessment (iii) in the two ESIAs that followed guidance, ES analysis resulted in specific mitigation measures. Few evidence was found that the ES concept is improving current ESIA practice. Key challenges are: (i) integrating ES analysis in such a way that it does not duplicate other analysis; (ii) adequately characterizing the beneficiaries of ES; and (iii) quantifying ES supply for impact prediction. - Highlights: • Incorporating ecosystem services analysis in impact assessment can improve results. • Additional impacts and mitigation were identified. • Challenges include developing appropriate indicators for impact prediction. • A key challenge is integrating the concept in such a way that it does not duplicate other analysis.

54 ENVIRONMENTAL SCIENCES↗

Progressing quality control in environmental impact assessment beyond legislative compliance: An evaluation of the IEMA EIA Quality Mark certification scheme

The effectiveness of Environmental Impact Assessment (EIA) systems is contingent on a number of control mechanisms: procedural; judicial; evaluative; public and government agency; professional; and development aid agency. If we assume that procedural and judicial controls are guaranteed in developed EIA systems, then progressing effectiveness towards an acceptable level depends on improving the performance of other control mechanisms over time. These other control mechanisms are either absent, or are typically centrally controlled, requiring public finances; this we argue is an unpopular model in times of greater Government austerity. Here we evaluate a market-based mechanism for improving the performance of evaluative and professional control mechanisms, the UK Institute of Environmental Management and Assessments' EIA Quality Mark. We do this by defining dimensions of effectiveness for the purposes of our evaluation, and by identifying international examples of the approaches taken to delivering the other control measures to validate the approach taken in the EIA Quality Mark. We then evaluate the EIA Quality Mark, when used in combination with legal procedures and an active judiciary, against the effectiveness dimensions and use time-series analysis of registrant data to examine its ability to progress practice. We conclude that the EIA Quality Mark has merit as a model for a market-based mechanism, and may prove a more financially palatable approach for delivering effective EIA in mature systems in countries that lack centralised agency oversight. It may, therefore, be of particular interest to some Member States of the European Union for ensuring forthcoming certification requirements stemming from recent amendments to the EIA Directive. - Highlights: • Quality control mechanisms in EIA are identified. • Effectiveness of EIA is conceptualised for evaluation purposes. • The UK IEMA EIA Quality Mark is introduced as a market-based mechanism. • The EIA Quality Mark is found to progress quality in many, but not all, areas.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Developing energy flexibility in clusters of buildings: A critical analysis of barriers from planning to operation

This paper examines building energy flexibility at an aggregated level and addresses the main barriers and research gaps for the development of this resource across three design and development phases: market and policy, early planning and design, and operation. We review methodologies and tools and discuss barriers, challenges, and opportunities, incorporating policy, economic, technical, professional, and social perspectives. Although various legal and regulatory frameworks exist to foster the development of energy flexibility for small buildings, financing mechanisms are limited with a significant number of perceived risks undermining private investment. For the early planning and design phase, planners and designers lack appropriate tools and face interoperability challenges, which often results in insufficient consideration of demand response programs. The review of the operational phase highlighted the socio-technical challenges related to both the complexity of deployment and communication, as well as privacy and acceptability issues. Finally, the paper proposes a number of targeted research directions to address challenges and promote greater energy flexibility deployments, including capturing building demand side dynamics, improving baseline estimations and developing seamless connectivity between buildings and districts.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Technoeconomic Analysis of Steel Production with Electric Thermal Energy Storage

The iron and steel industry is an important manufacturing sector and one of the largest energy consumers in the United States and globally. Hydrogen direct reduction of iron ore (H2DRI) is considered a promising process that could enhance domestic steel production. This process requires hydrogen inlet temperatures up to 950 degrees C to drive the endothermic reduction of the iron ore pellets. In this work we investigate the technoeconomic performance of an H2DRI plant using electric thermal energy storage (ETES) technologies for the hydrogen heating, compared to conventional natural gas fired heaters, hydrogen fired heaters, and electric hydrogen heaters. A technoeconomic analysis framework for the plant is developed and used in multiple case studies, covering different hydrogen prices, grid electricity profiles, and financing scenarios. The levelized cost of steel production is found out to be in the range of $775-950/mt, which is mostly inside the benchmarked steel price of $941/mt. ETES-based hydrogen heating is found to be in par with conventional natural gas fired heaters, and cheaper than hydrogen fired heaters and electric hydrogen heaters. The major cost drivers are the iron ore and hydrogen feedstock, followed by the hydrogen compression and heating capital. Several insights and suggested future directions are identified.

08 HYDROGEN↗

Climate Mitigation in Latin America: Implications for Energy and Land Use: Preface to the Special Section on the findings of the CLIMACAP-LAMP Project

The CLIMACAP-LAMP project, completed in December 2015, was an inter-model comparison exercise that focused on energy and climate change economics issues in Latin America. The project partners – co-financed by the EC / EuropeAid (CLIMACAP part) and EPA / USAID (LAMP part) and co-coordinated by respectively the Energy research Centre of the Netherlands (ECN) and the Pacific Northwest National Laboratory (PNNL) – report their main and detailed findings in this Special Issue of Energy Economics, exclusively dedicated to climate mitigation, low-carbon development and implications for energy and land use in Latin America. Our research endeavor included several of the most prominent regional energy modeling groups from Latin America, as well as a representative set of global integrated assessment modeling groups from a number of institutions from Europe and the US. About two dozen universities, research groups and environmental or consulting organizations took part in the CLIMACAP-LAMP cross-model comparison project, from both sides of the Atlantic. Over a handful of workshops were organized over the past four years in several countries in Latin America, attended by between 30 and 50 participants from, amongst others, Argentina, Brazil, Colombia, Mexico, the EU, and the US.

54 ENVIRONMENTAL SCIENCES↗

Soil contamination from lead battery manufacturing and recycling in seven African countries

Highlights: • Soil lead contamination was found at lead battery recycling facilities in Africa. • Mean lead concentrations were 2600 mg/kg in soil on the outside of plants. • Lead pollution at these sites poses significant health risks to the public. • Lead contamination at these plants suggest that extensive remediation is warranted. Lead battery recycling is a growing hazardous industry throughout Africa. We investigated potential soil contamination inside and outside formal sector recycling plants in seven countries. We collected 118 soil samples at 15 recycling plants and one battery manufacturing site and analyzed them for total lead. Lead levels in soils ranged from < 40–140,000 mg/kg. Overall mean lead concentrations were ~23,200 mg/kg but, average lead levels were 22-fold greater for soil samples from inside plant sites than from those collected outside these facilities. Arithmetic mean lead concentrations in soil samples from communities surrounding these plants were ~2600 mg/kg. As the lead battery industry in Africa continues to expand, it is expected that the number and size of lead battery recycling plants will grow to meet the forecasted demand. There is an immediate need to address ongoing exposures in surrounding communities, emissions from this industry and to regulate site closure financing procedures to ensure that we do not leave behind a legacy of lead contamination that will impact millions in communities throughout Africa.

54 ENVIRONMENTAL SCIENCES↗

Evolution of storage monitoring – update in response to commercial and regulatory drivers

Carbon Capture and Storage (CCS) is in transition from first-of-a kind projects and research-orientated pilots to commercially-motivated applications. Monitoring results from many newly developed and planned large scale commercial projects are limited; however, it is worthwhile to assess their evolution and consider new strategies as part of an effort to assess and document best practices. Commercial monitoring is targeted to activities that comply with regulatory drivers and de-risk investments. Commercial monitoring also supports accounting that storage has occurred and is tied to project financing. It deals with long time frames and large volumes injected into multiple wells and multiple projects in favorable areas. We see developing trends toward reproducible workflows that systematically reduce risks and clarify expectations for oversight and long-term surveillance. Monitoring techniques showing increasing trends include injection zone pressure as a history-matching and compliance tool. To reduce cost and environmental impact of time-lapse seismic data collection, deploying new approaches and tools, such as use of fibre and installed sources are increasingly applied. Concern over the risk of induced seismicity by regulatory bodies and the general public has increased, which has also resulted in increased monitoring. Some techniques used in the early research phases have been sidelined or used only in restricted applications. For example, geochemical analyses in the injection zone as well as the environment are now being deployed less than it was in research-oriented programs, except in the US where it is required by the permitting process. Expectations of frequent area-wide near surface monitoring have also decreased.

25 ENERGY STORAGE↗

Scaling up the energy service company business: market status and company feedback in the Russian Federation

Many energy efficiency professionals have proposed using Energy Performance Contracts (EPCs) as a mechanism to improve public sector energy efficiency in countries with restrictive government budgets. However, in practice, most middle-income countries have used this mechanism only in a limited way. Russia offers an interesting case study because of its huge energy savings opportunities, increasing energy prices, robust political backing for public sector energy efficiency, and evolving legislation that supports EPCs. In 2009, the Russian Federation launched a program to reduce the energy intensity of the country’s large public sector, which accounts for 9 percent of Russia’s total energy consumption. To achieve energy efficiency goals, Russia experimented with its public procurement rules, adjusting them to encourage EPCs. We conducted structured interviews with Energy Service Companies (ESCOs) in Russia and supplemented them with online research. Our review shows that, to date, nearly 50 ESCOs signed about 150 contracts in public facilities. Most ESCO contracts in Russia are for 5 years, and they generally are small (under $100,000). ESCOs in Russia face a challenging environment, which leads to smaller projects. ESCOs also are concerned about costly and risky tender procedures, uncertainty regarding repayment from public facilities, the inability to expand projects, and financing. We discuss these challenges and propose potential solutions at policy and company levels. The ESCOs feedback regarding Russia’s experimental model can inform the country’s program for public sector energy efficiency and offer lessons for other countries attempting to develop the EPC mechanism.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Power demand risk models on milling machines

The measurement of power demand risks in manufacturing power systems will benefit manufacturers and the wider society. If the risks can be characterized using manufacturing parameters, manufacturers can better control risks originating in those parameters, select less power-risky production plans, and reduce utility costs and resource consumption. The measurement of risk can also help manufacturers and power suppliers to protect their power systems from unexpected disturbances. Existing measures of risk, however, do not consider time duration, and thus cannot accurately quantify the risks in manufacturing power systems; the risks of a period of high power demand must be evaluated with the duration of the surge. Therefore, new methods of measuring power demand risks are proposed, adapting measures drawn from the field of finance. With a focus on milling operations, processing power is shown to be a function of processing amount and processing time, and a power demand distribution is directly derived as a joint distribution of and A and T. A bivariate random variable model with copulas is applied to examine the correlation in the joint distribution. Then, based on evaluation of a probability distribution of power demand from and, new risk measures are introduced. Herein illustrative examples are provided to show how the proposed measures can quantify the power demand risks from milling machines, based on manufacturing parameters. Certain manufacturing parameters are found to affect overall power demand risks, including i) raw material type, ii) variability in processing time, and iii) correlation between and. In the examples, these three factors increase power demand risks by up to 108%, 67%, and 1% respectively.

42 ENGINEERING↗

Multilevel Monte Carlo for two phase flow and Buckley–Leverett transport in random heterogeneous porous media

Monte Carlo (MC) is a well known method for quantifying uncertainty arising for example in subsurface flow problems. Although robust and easy to implement, MC suffers from slow convergence. Extending MC by means of multigrid techniques yields the multilevel Monte Carlo (MLMC) method. MLMC has proven to greatly accelerate MC for several applications including stochastic ordinary differential equations in finance, elliptic stochastic partial differential equations and also hyperbolic problems. In this study, MLMC is combined with a streamline-based solver to assess uncertain two phase flow and Buckley–Leverett transport in random heterogeneous porous media. The performance of MLMC is compared to MC for a two dimensional reservoir with a multi-point Gaussian logarithmic permeability field. The influence of the variance and the correlation length of the logarithmic permeability on the MLMC performance is studied.

97 MATHEMATICS AND COMPUTING↗