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At least 739 records · Page 41

Extracting Baseline Electricity Usage Using Gradient Tree Boosting

To understand how specific interventions affect a process observed over time, we need to control for the other factors that influence outcomes. Such a model that captures all factors other than the one of interest is generally known as a baseline. In our study of how different pricing schemes affect residential electricity consumption, the baseline would need to capture the impact of outdoor temperature along with many other factors. In this work, we examine a number of different data mining techniques and demonstrate Gradient Tree Boosting (GTB) to be an effective method to build the baseline. We train GTB on data prior to the introduction of new pricing schemes, and apply the known temperature following the introduction of new pricing schemes to predict electricity usage with the expected temperature correction. Our experiments and analyses show that the baseline models generated by GTB capture the core characteristics over the two years with the new pricing schemes. In contrast to the majority of regression based techniques which fail to capture the lag between the peak of daily temperature and the peak of electricity usage, the GTB generated baselines are able to correctly capture the delay between the temperature peak and the electricity peak. Furthermore, subtracting this temperature-adjusted baseline from the observed electricity usage, we find that the resulting values are more amenable to interpretation, which demonstrates that the temperature-adjusted baseline is indeed effective.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Sensitivity analysis of the technical and economic feasibility of converter-interfaced CHP System

The adoption of small-to-medium sized (1MW~20MW) combined heat and power (CHP) system is lagging, especially in industrial and commercial applications. Our prior research has proved that interfacing CHP with grid-ready converters can increase its economic value and technical benefits; this paper is focused on investigating the critical parameters impacting profitability of converter-interfaced CHP, including CHP sizing scenario, energy price, generator cost, converter cost, voltage support price, converter to engine size ratio and interconnection delay. An automatic toolkit for evaluating CHP return on investment (ROI) is developed to enhance the computation capability and efficiency. Based on varying the value of critical parameters, 975 use cases are analyzed. Results show that the profitability of converter-interfaced CHP over directly-coupled CHP is more sensitive to energy price, delays in interconnection process, converter cost and much less to generator cost or voltage support price.

converter, CHP, ROI, economic feasibility, sensiti↗

Bidding strategy for microgrid in day-ahead market based on hybrid stochastic/robust optimization

In this paper, we propose an optimal bidding strategy in the day-ahead market of a microgrid consisting of intermittent distributed generation (DG), storage, dispatchable DG and price responsive loads. The microgrid coordinates the energy consumption or production of its components and trades electricity in both the day-ahead and real-time markets to minimize its operating cost as a single entity. The bidding problem is challenging due to a variety of uncertainties, including power output of intermittent DG, load variation, day-ahead and real-time market prices. A hybrid stochastic/robust optimization model is proposed to minimize the expected net cost, i.e., expected total cost of operation minus total benefit of demand. This formulation can be solved by mixed integer linear programming. The uncertain output of intermittent DG and day-ahead market price are modeled via scenarios based on forecast results, while a robust optimization is proposed to limit the unbalanced power in real-time market taking account of the uncertainty of real-time market price. Numerical simulations on a microgrid consisting of a wind turbine, a PV panel, a fuel cell, a micro-turbine, a diesel generator, a battery and a responsive load show the advantage of stochastic optimization in addition to robust optimization.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Coordinated Market Design for Peer-to-Peer Energy Trade and Ancillary Services in Distribution Grids

A novel peer-to-peer (P2P) market design is proposed in this work for the distribution grid level. Envisioning that the grid constraints violations are the major challenge for P2P energy sharing, we propose they are handled through the ancillary service (AS) market. By calculating the decomposable distribution locational marginal prices (DLMPs), the essential price signals of procuring AS can be recovered to determine the grid usage prices (GUPs) to each P2P transaction. Hence, the GUPs, due to their decomposable properties, act as incentive signals for the P2P market to support the grid operation in terms of loss reduction, voltage support and congestion management. The proposed market design comprises: i) an interactive market design of P2P trade & AS and, ii) a fully decentralized peer-centric market clearing model for P2P energy trade. The duality analysis provides the composition of market equilibrium prices of P2P trading and their interpretations. The case studies demonstrate the effectiveness of the proposed P2P trade to support grid operational objectives.

Zhang, Kai↗

Automated Control of Transactive HVACs in Energy Distribution Systems

Heating, Ventilation, and Air Conditioning (HVAC) systems contribute significantly to a building’s energy consumption. In the recent years, there is an increased interest in developing transactive approaches which could enable automated and flexible scheduling of HVAC systems based on the customer demand and the electricity prices decided by the suppliers. Flexible and automated scheduling of the HVAC systems make it a prime source for participation in residential demand response or transactive energy systems. Therefore, it is of significant interest to identify an optimal strategy to control the HVAC systems. Here, reducing the energy cost while keeping the comfort level acceptable to the users, we argue that such a control strategy should consider both the energy cost and user comfort simultaneously. Accordingly, we develop the control strategy through the solution of an optimization problem that balances between the energy cost and consumer’s dissatisfaction. This optimization enables us to solve a decision-making problem through first price prediction and then choosing HVAC temperature settings throughout the day based on the predicted price, history of the price and HVAC settings, and outside temperature. More specifically, we formulate the control design as a Markov decision process (MDP) using deep neural networks and use Deep Deterministic Policy Gradients (DDPG)-based deep reinforcement learning algorithm to find the optimal control strategy for HVAC systems that balances between electricity cost and user comfort.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

BI-LEVEL OPTIMIZATION FOR ELECTRICITY TRANSACTION IN SMART COMMUNITY WITH MODULAR PUMP HYDRO STORAGE

Grid integration of the increasing distributed energy resources could be challenging in terms of new infrastructure investment, power grid stability, etc. To resolve more renewables locally and reduce the need for extensive electricity transmission, a community energy transaction market is assumed with market operator as the leader whose responsibility is to generate local energy prices and clear the energy transaction payment among the prosumers (followers). The leader and multi-followers have competitive objectives of revenue maximization and operational cost minimization. This non-cooperative leader-follower (Stackelberg) game is formulated using a bi-level optimization framework, where a novel modular pump hydro storage technology (GLIDES system) is set as an upper level market operator, and the lower level prosumers are nearby commercial buildings. The best responses of the lower level model could be derived by necessary optimality conditions, and thus the bi-level model could be transformed into single level optimization model via replacing the lower level model by its Karush-Kuhn-Tucker (KKT) necessary conditions. Several experiments have been designed to compare the local energy transaction behavior and profit distribution with the different demand response levels and different local price structures. The experimental results indicate that the lower level prosumers could benefit the most when local buying and selling prices are equal, while maximum revenue potential for the upper level agent could be reached with non-equal trading prices.

Chen, Yang↗

Revisiting Parabolic Trough Concentrators for Industrial Process Heat in the United States

After significant interest in the 1970s, but relatively few deployments, the use of concentrating solar collectors for thermal applications, including enhanced oil recovery, desalination, and industrial process heat (IPH), is again increasing in global interest. In particular, recent advances in collector design and manufacturing have led to reduced cost per square meter of aperture area. In this study, analysis of a modern parabolic trough that is suited for use in small solar IPH (SIPH) applications predicts that the installed solar field cost can be as low as $170/m2. A slightly higher cost of $200/m2 is estimated for facilities typical of a SIPH plant size. Full project costs will include additional costs for contingency, piping and heat exchanger interface, and project indirect costs. The cost for solar-generated heat by SIPH is quantified by defining the levelized cost of heat (LCOH). California offers a favorable environment for SIPH given its good insolation, gas prices typically higher than the national average, and policies promoting solar-thermal deployment. Given historically low gas prices, competing with natural gas remains the primary challenge to deployment. However, this study finds that the solar LCOH for many regions in California is lower than the LCOH from natural gas, using a representative installed solar hardware price and the average price for industrial natural gas in California. Lastly, modification are in progress to the parabolic trough model within NREL's System Advisor Model (SAM) to allow users to more easily predict performance for these steam-generation applications.

14 SOLAR ENERGY↗

A Global Food Demand Model for the Assessment of Complex Human-Earth Systems

Demand for agricultural products is an important problem in climate change economics. Food consumption will shape and shaped by climate change and emissions mitigation policies through interactions with bioenergy and afforestation, two critical issues in meeting international climate goals such as two-degrees. We develop a model of food demand for staple and nonstaple commodities that evolves with changing incomes and prices. The model addresses a long-standing issue in estimating food demands, the evolution of demand relationships across large changes in income and prices. We discuss the model, some of its properties and limitations. We estimate parameter values using pooled cross-sectional-time-series observations and the Metropolis Monte Carlo method and cross-validate the model by estimating parameters using a subset of the observations and test its ability to project into the unused observations. Finally, we apply bias correction techniques borrowed from the climate-modeling community and report results.

climate change, fo, in↗

Optimal Financing Decision in a Contract Food Supply Chain with Capital Constraint

To solve the financing problem of the food producers, we consider a two‐echelon contract food supply chain composed of a family farm with capital constraints and a food processing enterprise. With no capital constraints as the benchmark model, we analyze optimal decisions of the family farm and the food processing enterprise in the case of bank financing with bank participation only and bank financing with “government, bank, and insurance” coparticipation. Then, we discuss how the risk of yield uncertainty influences the optimal decisions and profits of the family farm and the food processing enterprise under different financing situation. Meanwhile, the reason why the government subsidizes agriculture is explored, and the policy of minimum purchase price of the food is initiated when the market price is too low. Finally, the numerical examples and sensitivity analysis are presented. The results show that the bank financing with “government, bank, and insurance” coparticipation improves the welfare of supply chain members more obviously than the bank financing with bank participation only; when the rice price is too low, the policy of minimum purchase price of food is initiated, which increases the revenue and the growing enthusiasm of the family farm; the profits of the family farm and the food processing enterprise will decrease as the risk of yield uncertainty increases in the case of bank financing, and the risk of yield uncertainty will be reduced for the family farm when bank financing with “government, bank, and insurance” coparticipation.

Luo, Ying (ORCID:0000000158101443)↗

CatCost™ (Catalyst Cost Estimation Tool) [SWR-18-74]

CatCost™ is a state-of-the-art cost estimation tool designed to reduce the cost uncertainty associated with pre-commercial catalyst materials. The tool combines industry-standard cost estimation methods and resources into an intuitive suite of tools to bring actionable cost insight to every step of catalyst research and development. CatCost™ allows the rapid development of comprehensive catalyst cost estimates. It incorporates detailed insight into manufacturing methods, especially for pre-commercial catalysts, without requiring any process design experience. The tool has been designed from the ground up with a number of user-selectable estimation methods, pricing libraries, and ease-of-use features to tailor an estimate to a user's skill level and need for customization, empowering researchers of all skill-levels to make better R&D decisions throughout the catalyst development cycle. Our costing methods are fully transparent and enable power-users the ability to adjust any estimate to the economic realities of their operation. The tool has been designed from the ground up with a number of user-selectable estimation methods, pricing libraries, and ease-of-use features to tailor an estimate to a user's skill level and need for customization, empowering researchers of all skill-levels to make better R&D decisions throughout the catalyst development cycle. Our costing methods are fully transparent and enable power-users the ability to adjust any estimate to the economic realities of their operation. Features include: Raw materials pricing: Libraries of common chemicals, cost scaling indices, guidance for obtaining bulk quotes, and methods for extrapolating laboratory-scale prices to bulk. Simplified step method for synthesis by a contract manufacturer: All-in hourly cost for process equipment using methods and data from tollers. (Excel-only in v1.0)

Baddour, Frederick↗

EFFORT (EFFectiveness Of Rate sTructure for enabling demand response)

This tool helps utilities evaluate potential time of use price-plans and find effective hours for price plan on peak periods and the potential price-elastic demand response. An optimization model can be used to find tiered prices for the time of use tariffs and analyze the impact on load profiles, energy consumption, utility, and customer savings. The tool is equipped with an optimization model to determine the energy consumption of electric appliances that can leverage survey data containing information on the number of appliances owned by customers. Lastly, a statistical model can be used to predict system-level load based on exogenous parameters such as weather, time of day, month, type of day, and year. The tool is scripted in Python and uses the Pyomo python optimization language.

Duwadi, Kapil↗

ADOPT (Automotive Deployment Options Projection Tool) [SWR-17-13]

NREL's Automotive Deployment Options Projection Tool (ADOPT) is a vehicle consumer choice and stock model. ADOPT estimates the impact of vehicle technology improvements on future U.S. vehicle sales, energy use, and emissions. It provides consumer choice estimates based on questions such as: -How much impact do lower battery prices have on electric vehicle sales? -How quickly would the market adopt a co-optimized engine/fuel combination that achieves a 10% efficiency improvement? -How do fuel prices impact the electric vehicle/plug-in hybrid electric vehicle sales mix? -How does vehicle lightweighting impact powertrain sales? Approach- Starting with the majority of existing vehicle makes, models, and trims to fully represent the market, ADOPT applies numerous inputs-technology improvements, fuel prices, and vehicle purchase incentives-over time. ADOPT then estimates sales based on the variable weighted value of key attributes, including vehicle price, fuel cost per mile, acceleration, size, and range. ADOPT also considers consumer income level as well as regulations and standards that influence sales and average fuel economy. ADOPT incorporates NREL's FASTSim™ (Future Automotive Systems Technology Simulator, https://www.nrel.gov/transportation/fastsim.html) to apply specified technology improvements to vehicles over time, and to create new model options by combining high-selling powertrains and high-selling vehicle platforms. NREL has extensively validated the tool and its consumer preference trade-offs to ensure confidence in the results.

Brooker, Aaron↗

Data from Biodiesel Production from Engineered Sugarcane Lipids under Uncertain Feedstock Compositions: Process Design and Techno-Economic Analysis

In this study, different process schemes were designed and evaluated for biodiesel production from engineered cane lipids with uncertain fatty acid compositions. Four different process schemes were compared under (i) thermal glycerolysis and (ii) enzymatic glycerolysis approaches. These schemes were based on the biodiesel yield and economic indicators such as the net present value (NPV) and the minimum selling price (MSP) of biodiesel. A scheme with polar lipid separation under thermal glycerolysis resulted in the maximum NPV ($96.5 million) and minimum MSP ($1107/ton biodiesel), respectively. Through local sensitivity analysis, it was concluded that the cane lipid percentage is the most significant factor influencing process economics. A conjoint analysis of the lipid procurement price and cane lipid percent suggested that 15% cane lipids with a low lipid procurement price ($0.536/kg) results in a positive NPV. When the cane lipid price is higher (>$0.80/kg), a 20% lipid content should be considered to achieve a positive NPV. At 20% cane lipids, the worst-case and best-case scenarios were evaluated by analyzing the interplay of the three most important parameters, The best-case scenario revealed that the minimum NPV under any process scheme could yield more than $100 million (or MSP: $0.80/L), and the worst-case analysis showed that losses incurred by the plant could be as high as $80 million (MSP: $1.36/L). A Monte Carlo simulation indicated that there is a 70% chance of the plant being profitable (NPV > 0).

Conversion↗

Solar Process Heat Potential in California, USA

The cost for solar industrial process heat (SIPH) is quantified by defining the levelized cost of heat (LCOH). The state of California, in the United States offers a favorable environment for SIPH given its excellent insolation, industrial gas prices typically higher than the national average, and policies promoting solarthermal deployment. Given historically low gas prices, competing with natural gas remains the primary challenge to deployment. However, this study finds that the solar LCOH from Concentrating Solar Power (CSP) collectors for many regions in California is expected to be lower than the LCOH from natural gas, using a representative installed solar hardware price and the average price for industrial natural gas in California. Lastly, modifications are in progress to the parabolic trough and Direct Steam Generation (DSG) trough and Linear Fresnel models within NREL's System Advisor Model (SAM) to allow users to more easily predict performance for these industrial heat and steam-generation applications.

14 SOLAR ENERGY↗

Membrane Purification Cell for Aluminum Recycling

Recycling mixed aluminum scrap usually requires adding primary aluminum to the scrap stream as a diluent to reduce the concentration of non-aluminum constituents used in aluminum alloys. Since primary aluminum production requires approximately 10 times more energy than melting scrap, the bulk of the energy and carbon dioxide emissions for recycling are associated with using primary aluminum as a diluent. Eliminating the need for using primary aluminum as a diluent would dramatically reduce energy requirements, decrease carbon dioxide emissions, and increase scrap utilization in recycling. Electrorefining can be used to extract pure aluminum from mixed scrap. Some example applications include producing primary grade aluminum from specific scrap streams such as consumer packaging and mixed alloy saw chips, and recycling multi-alloy products such as brazing sheet. Electrorefining can also be used to extract valuable alloying elements such as Li from Al-Li mixed scrap. This project was aimed at developing an electrorefining process for purifying aluminum to reduce energy consumption and emissions by 75% compared to conventional technology. An electrolytic molten aluminum purification process, utilizing a horizontal membrane cell anode, was designed, constructed, operated and validated. The electrorefining technology could also be used to produce ultra-high purity aluminum for advanced materials applications. The technical objectives for this project were to: - Validate the membrane cell concept with a lab-scale electrorefining cell; - Determine if previously identified voltage increase issue for chloride electrolytes holds for a fluoride-based electrolyte system; - Assess the probability that voltage change issues can be solved; and - Conduct a market and economic analysis to assess commercial feasibility. The process was tested using three different binary alloy compositions (Al-2.0 wt.% Cu, Al-4.7 wt.% Si, Al-0.6 wt.% Fe) and a brazing sheet scrap composition (Al-2.8 wt.% Si-0.7 wt.% Fe-0.8 wt.% Mn),. Purification factors (defined as the initial impurity concentration divided by the final impurity concentration) of greater than 20 were achieved for silicon, iron, copper, and manganese. Cell performance was measured using its current and voltage characteristics and composition analysis of the anode, cathode, and electrolytes. The various cells were autopsied as part of the study. Three electrolyte systems tested were: LiCl-10 wt. % AlCl3, LiCl-10 wt. % AlCl3-5 wt.% AlF3 and LiF-10 wt.% AlF3. An extended four-day run with the LiCl-10 wt.% AlCl3-5 wt.% AlF3 electrolyte system was stable for the entire duration of the experiment, running at energy requirements about one third of the Hoopes and the conventional Hall-Heroult process. Three different anode membranes were investigated with respect to their purification performance and survivability: a woven graphite cloth with 0.05 cm nominal thickness & > 90 % porosity, a drilled rigid membrane with nominal porosity of 33%, and another drilled rigid graphite membrane with increased thickness. The latter rigid drilled graphite was selected as the most promising membrane design. The economic viability of the membrane cell to purify scrap is sensitive to primary & scrap aluminum prices, and the cost of electricity. In particular, it is sensitive to the differential between scrap and primary aluminum price which is highly variable and dependent on the scrap source. In order to be economically viable, any scrap post-processing technology in the U.S. market must have a total operating cost well below the scrap price differential of $0.20-$0.40 per lb to the London Metal Exchange (LME), a margin of 65%-85% of the LME price. The cost to operate the membrane cell is estimated to be < $0.24/lb of purified aluminum. The energy cost is estimated to be $0.05/lb of purified aluminum with the remaining costs being repair and maintenance, electrolyte, labor, taxes and depreciation. The bench-scale work on membrane purification cell process has demonstrated technological advantages and substantial energy and investment savings against other electrolytic processes. However, in order to realize commercial reality, the following items need to be fully investigated: 1. Further evaluation of a pure fluoride electrolyte. 2. Investigate alternative non conductive, more mechanically robust and chemically inert membrane candidates. 3. Optimized membrane cell design to understand contribution of fluid flow patterns and the mass transfer conditions. 4. Improve current efficiency and total metallic aluminum recovery from the cell. All Tasks and Milestones were completed successfully.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Characteristics of Range Hoods in California Homes -- Data Collected from a Real Estate Web Site

Venting range hoods are important residential ventilation components that remove pollutants generated by cooking activities and natural gas cooking burners. To address the lack of data on range hood installations in California, we conducted a survey by examining photographs of homes for sale or rent listed on a popular real estate web site. The survey was conducted in November 2010 and April–May 2011. Posted photos of the homes were reviewed to determine if a hood was installed, the type of hood, and two installation details that can impact performance, namely the height above the cooktop and the degree to which the hood covers the cooktop burners. We additionally collected information about the homes, including asking price for purchase or rent, type of building (e.g. detached house, townhouse or apartment), building age, floor area, and cooktop fuel type. Listings were first sampled to focus on homes built since 2005, then randomly sampled to include varied prices and locations around the state. Data were obtained for 1002 homes built between 1865 and 2011 (median year built 1989). Homes for sale varied in asking price from $\$$16,000 to $\$$16,500,000 (median $\$$353,000) and homes for rent varied from $\$$500 to $\$$25,000 (median $\$$2125) per month. Approximately 74% of the sample had natural gas cooktops. In this sample, natural gas cooktops were more prevalent in more expensive homes than in less expensive homes. Across the entire sample, 7.4 % appeared to have no hood installed, 33% had a short hood, 13% had a deep hood and 47% had a microwave over the range. The percentage of these hoods that vent to the outdoors could not be determined. Hood type was related to coverage of the cooktop. For deep hoods, 76% appeared to cover most or all of the cooktop burners. For short hoods, 70% covered about three quarters of the cooktop. And for microwaves the vast majority (96%) covered the back burners but not the front burners. Hood type was also correlated with asking price or monthly rent, with deep hoods most common in the most expensive homes. Hood type was also correlated with home age, with microwave hoods more common in newer homes. Installation height was related to device type with microwaves installed lower (closer) to the cooktop (median 18 inches), and short hoods (median 28 inches) and deep hoods (median 30 inches) installed higher. Deep range hoods are more common with natural gas cooktops than with electric cooktops, and slightly fewer homes with natural gas cooktops lack a range hood (7%) than homes with electric cooktops (9%). This study provides limited but useful information about the characteristics of range hoods in California homes and demonstrates the potential value of non-traditional forms of data collection.

54 ENVIRONMENTAL SCIENCES↗

Annual Energy Outlook 2013 With Projections to 2040

The Annual Energy Outlook 2013 (AEO2013), prepared by the U.S. Energy Information Administration (EIA), presents long-term projections of energy supply, demand, and prices through 2040, based on results from EIA’s National Energy Modeling System. The report begins with an “Executive summary” that highlights key aspects of the projections. It is followed by a “Legislation and regulations” section that discusses evolving legislative and regulatory issues, including a summary of recently enacted legislation and regulations, such as: Updated handling of the U.S. Environmental Protection Agency’s (EPA) National Emissions Standards for Hazardous Air Pollutants for industrial boilers and process heaters; New light-duty vehicle (LDV) greenhouse gas (GHG) and corporate average fuel economy (CAFE) standards for model years 2017 to 2025; Reinstatement of the Clean Air Interstate Rule (CAIR) after the court’s announcement of intent to vacate the Cross-State Air Pollution Rule (CSAPR); and Modeling of California’s Assembly Bill 32, the Global Warming Solutions Act (AB 32), which allows for representation of a cap-and-trade program developed as part of California’s GHG reduction goals for 2020. The “Issues in focus” section contains discussions of selected energy topics, including a discussion of the results in two cases that adopt different assumptions about the future course of existing policies, with one case assuming the elimination of sunset provisions in existing policies and the other case assuming the elimination of the sunset provisions and the extension of a selected group of existing public policies—CAFE standards, appliance standards, and production tax credits. Other discussions include: oil price and production trends in AEO2013; U.S. reliance on imported liquids under a range of cases; competition between coal and natural gas in electric power generation; high and low nuclear scenarios through 2040; and the impact of growth in natural gas liquids production. The “Market trends” section summarizes the projections for energy markets. The analysis in AEO2013 focuses primarily on a Reference case, Low and High Economic Growth cases, and Low and High Oil Price cases. Results from a number of other alternative cases also are presented, illustrating uncertainties associated with the Reference case projections for energy demand, supply, and prices. Complete tables for the five primary cases are provided in Appendixes A through C. Major results from many of the alternative cases are provided in Appendix D. Complete tables for all the alternative cases are available on EIA’s website in a table browser at http://www.eia.gov/oiaf/aeo/tablebrowser. AEO2013 projections are based generally on federal, state, and local laws and regulations in effect as of the end of September 2012. The potential impacts of pending or proposed legislation, regulations, and standards (and sections of existing legislation that require implementing regulations or funds that have not been appropriated) are not reflected in the projections. In certain situations, however, where it is clear that a law or regulation will take effect shortly after the Annual Energy Outlook (AEO) is completed, it may be considered in the projection.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Livingston Parish Landfill Methane Recovery Project (Feasibility Study)

The Woodside Landfill is owned by Livingston Parish, Louisiana and is operated under contract by Waste Management of Louisiana LLC. This public owner/private operator partnership is commonplace in the solid waste industry today. The landfill has been in operation since approximately 1988 and has a permitted capacity of approximately 41 million cubic yards. Based on an assumed in-place waste density of 0.94 ton per cubic yard, the landfill could have an expected design capacity of 39.3 million tons. The landfill does have an active landfill gas collection and control system (LFGCCS) in place because it meets the minimum thresholds for the New Source Performance Standards (NSPS). The initial LFGCS was installed prior to 2006 and subsequent phases were installed in 2007 and 2010. The Parish received a grant from the United States Department of Energy in 2009 to evaluate the potential for landfill gas recovery and utilization at the Woodside Landfill. This includes a technical and economic feasibility study of a project to install a landfill gas to energy (LFGTE) plant and to compare alternative technologies. The LFGTE plant can take the form of on-site electrical generation, a direct use/medium Btu option, or a high-Btu upgrade technology. The technical evaluation in Section 2 of this report concludes that landfill gas from the Woodside landfill is suitable for recovery and utilization. The financial evaluations in sections 3, 4, and 5 of this report provide financial estimates of the returns for various utilization technologies. The report concludes that the most economically viable project is the Electricity Generation option, subject to the Parish’s ability and willingness to allocate adequate cash for initial capital and/or to obtain debt financing. However, even this option does not present a solid return: by our estimates, there is a 19 year simple payback on the electricity generation option. All of the energy recovery options discussed in this report economically stressed. The primary reason for this is the recent fundamental shift in the US energy landscape. Abundant supplies of natural gas have put downward pressure on any project that displaces natural gas or natural gas substitutes. Moreover, this shift appears long-term as domestic supplies for natural gas may have been increased for several hundred years. While electricity prices are less affected by natural gas prices than other thermal projects, they are still significantly affected since much of the power in the Entergy cost structure is driven by natural gas-fired generation. Consequently, rates reimbursed by the power company based on their avoided cost structure also face downward pressure over the near and intermediate term. In addition, there has been decreasing emphasis on environmental concerns regarding the production of thermal energy, and as a result both the voluntary and mandatory markets that drive green attribute prices have softened significantly over the past couple of years. Please note that energy markets are constantly changing due to fundamental supply and demand forces, as well as from external forces such as regulations and environmental concerns. At any point in the future, the outlook for energy prices may change and could deem either the electricity generation or pipeline injection project more feasible. This report is intended to serve as the primary background document for subsequent decisions made at Parish staff and governing board levels.

09 BIOMASS FUELS↗