Profit-Oriented False Data Injection on Electricity Market: Reviews, Analyses, and Insights
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Optimization of Operating Profit for the FEED of the PZAS Process for CO 2 Capture on a 460 MW NGCC
A rating model of PZAS (Piperazine with the Advanced Stripper) for a 460 MW natural gas combined cycle was developed from vendor-provided equipment performance data. Surrogate rating models were built and used to optimize variable profit of the system subject to natural gas and electricity price at a fixed value for CO 2 of $\$80$/tonne. Several process constraints were considered between ambient temperatures of 4.4 and 40.5 °C. Lower lean loading resulted in lower reboiler heat duty of about 2.2 GJ/tonne. Lean loading at 0.2 mol/equiv N was sufficient at an ambient temperature of 4.4 °C to maximize variable profit. Solvent precipitation was avoided even at low lean loading (0.18 mol/mol) in the absence of a trim cooler for the lean solvent between the absorber and the cold cross exchanger. Optimal CO 2 removal was always higher than the design case removal of 90% and achieved a peak of 93.6% for 4.4 ºC ambient temperature. Lean solvent rate was a significant driver of profitability. The maximum capacity of the compressor was a significant constraint on profitability. Increasing compressor capacity by 20–30% could increase variable profit by about 21% in the case of 0.18 lean loading at 4.4 °C ambient temperature. Furthermore, this increase in profit was lower at higher ambient temperature and higher lean loading. The breakeven gas price was $\$4.6$/MMBtu at high lean loading of 0.22 mol/mol. Below this value, profit was maximized by increasing the boiler heat rate. Above this value, profit could not be increased by burning additional natural gas, requiring a reduction in boiler heat rate and consequently, specific heat duty. At lower lean loading (0.2, 0.18 mol/mol), this transition in heat duty was not observed due to the lower heat duty. As the ambient temperature increased, a similar trend in heat duty was observed at 0.22 lean loading, but the transition to lower heat duty occurred earlier at $\$4$/MMBtu. This was because of the lower CO 2 production at higher ambient temperature, making the process unprofitable at a gas price higher than $\$3$/MMBtu unless the heat duty of the stripper and natural gas boiler is steeply decreased.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Determining spatially varying profit‐maximizing management practices for miscanthus and switchgrass production in the rainfed United States
Abstract Determining optimal management practices for the profitable production of perennial energy crops is critical for scaling up production beyond experimental levels. Although many experimental field studies have examined the effects of management practices on the performance of miscanthus and switchgrass, there are no recommendations for economically optimal nitrogen (N) application rates and how they should vary spatially and with the age of the energy crop as well as on optimal rotation age of the energy crop to maximize profits. We develop a modeling framework to determine economically optimal crop management decisions and simulate the variability under various scenarios for miscanthus and switchgrass production across 2287 counties in the rainfed United States. We find that profit‐maximizing N recommendations for these crops vary across maturity stages and regions and can increase the landowner's profits compared with a uniform N rate across ages and regions. We also find that the optimal rotation for these crops is shorter than the productive physical lifespan (15–20 and 10 years for miscanthus and switchgrass, respectively). Specifically, the N rate that maximizes the economic returns is negligible for miscanthus and 111 kg ha −1 for switchgrass production at age 2. The mean profit‐maximizing N rate increases with age for miscanthus, peaking at 151 kg ha −1 at age 11 before declining to 114 kg ha −1 at the optimal rotation age of 13 years while that for switchgrass is 150 kg ha −1 for middle‐aged stands and declines to 114 kg ha −1 at the optimal rotation of 8–9 years. We find that miscanthus is the most profitable energy crop in the northern region of the rainfed United States while switchgrass is most profitable in the south of the rainfed United States. Our findings are useful for improving assessments of the profitability of energy crops and guiding future management decisions by landowners.
54 ENVIRONMENTAL SCIENCES↗
How profitable is switchgrass in Illinois, USA? An economic definition of marginal land
Decisions regarding the conversion of land from an existing crop to bioenergy crops are critical for the sustainable production of both food and fuels. This study seeks to establish criteria for delineating land as “economically marginal”, and thus suited for growing switchgrass. In this case study of an Illinois agricultural field, the profitability of switchgrass, with farmgate prices of $\$44$ Mg –1 , $\$66$ Mg –1 , or $\$88$ Mg –1 , was compared to corn and soybean crop prices. Further, the study also evaluates the profitability of switchgrass when replacing corn-based yield estimates from the Soil Productivity Index (SPI) of Illinois. Based on a dry-matter yield of 10.45 Mg ha –1 , switchgrass can compete with soybeans only at the high price of $\$88$ Mg –1 , but depending on location, can compete with corn at $\$66$ Mg –1 . Across Illinois, at $\$88$ ha –1 , all Illinois land with SPI < 100% and 95% of land under SPI class C (SPI 100–116) is profitable under switchgrass. Switchgrass may not be profitable relative to corn grown in the SPI class A (SPI > 133) and only 7% of class B (SPI 117–132). Our results show that land with drainage and erosion limitations is economically marginal when corn and soybean yields are low, and the farmgate price for switchgrass is greater than $\$66$ Mg –1 . However, this may not be possible on land where switchgrass is replacing frequent soybean rotations (corn–soybean ratio ≤ 1). Land used to produce only soybeans may only be marginal at the farmgate price of $\$88$ Mg –1 . Further studies need to be conducted to identify how much land can be converted to switchgrass without harming corn production.
09 BIOMASS FUELS↗
Optimal scheduling for profit maximization of energy storage merchants considering market impact based on dynamic programming
This paper analyzes how electricity merchants' market impact affects merchants' profit. Energy storage has long been studied for its role in maximizing profit, and merchant decisions are assumed to have no impact on market prices. However, the trading decisions of large-scale energy storage merchants (e.g., pumped storage hydro) will affect the market prices. This paper employs dynamic programming theory to investigate merchants' optimal economic dispatch considering the market impact and physical characteristics of storage systems. Our findings show that the State-of-Charge (SOC) based analytical solution significantly facilitates energy storage merchants' decision-making. The SOC range is segmented into three regions by two optimal SOC reference points, which depend on the available energy in storage, given prices, and market impact. By comparing the current storage SOC with the reference points, the merchant can get the corresponding optimal actions. We analytically show that if the merchant neglects the market impact on the power market, she will exaggerate her expected profit when the price-taker and price-maker merchants have the same generating and pumping upper limits offered to Independent System Operators (ISOs). Furthermore, the profit-maximizing merchant must, therefore, assay to balance the trade-off correctly between the intensity of market impact and the dispatched power. Our findings are verified by numerical simulation, and results demonstrate the ramifications for electricity merchants in energy arbitrage decisions.
25 ENERGY STORAGE↗
Impoverishing Roots Will Improve Wheat Yield and Profitability Through Increased Water and Nitrogen Use Efficiencies
We report that more than a 60% increase in crop production is required by the 2050's to feed a growing world population. Understanding how plant functional traits and field management affect crop yields has the potential to improve agricultural productivity, minimize economic and environmental losses, and maximize food security. We explored the influence of winter wheat root characteristics and management on winter wheat growth, yield, and profit using a mechanistic and well-tested ecosystem and crop model, ecosys. We applied and further tested ecosys at an agricultural farm growing winter wheat in Ardmore, Oklahoma, United States. The model accurately predicted observed shoot carbon (R 2 = 0.95), soil moisture (R 2 = 0.67), soil temperature (R 2 = 0.91), and yield (percent error = 17%). Numerical optimization experiments were conducted to explore potential improvements of winter wheat yield and profit by modifying root characteristics, including root radius and root:shoot carbon transfer conductance, and fertilizer inputs. Our results show the potential for simultaneously improving winter wheat yields and profits. The optimum conditions were found to be in the range of root radius between 0.1 and 0.3 mm, carbon transfer conductance between 0.004 and 0.01 h -1 , and the currently applied fertilizer rate of 112 kg ha -1 . Under these conditions, improvements in yields and profits of up to approximately 25% and 110%, respectively, were modeled compared to those under baseline root traits. These improvements were achieved by impoverishing root structures, thereby increasing nutrient allocation to grains. Our results also demonstrate and motivate model structures that integrate the complex network of plant physiology, soil nutrient biogeochemistry, hydrology, and management.
54 ENVIRONMENTAL SCIENCES↗
An evaluation of electricity system technology competitiveness metrics: The case for profitability
In this work we develop standardized functional forms for electricity technology competitiveness metrics and show how the mathematical relationship between value and cost can affect the robustness of the metric. Here, we make the case to replace established metrics with economic profitability metrics – including a new profitability-based adjustment to LCOE. These profitability metrics are shown to be more robust for evaluating technology competitiveness by keeping comparisons on an equivalent monetary basis.
29 ENERGY PLANNING, POLICY, AND ECONOMY↗
Investigating the Efficacy of Integrating Energy Crops into Non-Profitable Subfields in Iowa
We present that within-field spatial variability reduces growers’ return on investment and overall productivity while potentially increasing negative environmental impacts through increased soil erosion, nutrient runoff, and leaching. The hypothesis that integrating energy crops into non-profitable segments of agricultural fields could potentially increase grain yield and biomass feedstock production was tested in this study using a statewide analysis of predominantly corn- and soy-producing counties in Iowa. Basic and rigorous controls on permissible soil and soil-carbon losses were imposed on harvest of crop residues to enhance year-to-year sustainability of crop and residue production. Additional criteria limiting harvesting costs and focus on large-area subfields for biomass production were imposed to reduce the impacts of energy crop integration on grain production. Model simulations were conducted using 4 years (2013–2016) of soil, weather, crop yield, and management practice data on all counties in Iowa. Miscanthus (Miscanthus x giganteus), switchgrass (Panicum virgatum), and crop-residue-based bioenergy feedstock systems were evaluated as biomass. Average energy crop and plant residue harvesting efficiencies were estimated at 50 and 60%, respectively. Because of higher potential yields, average logistics costs for miscanthus-based biomass production were 15 and 23% lower than switchgrass-based and crop residue-based biomass productions, respectively, under basic sustainability controls, and 17 and 26% lower under rigorous sustainability controls. Lastly, subfield shape, size, area, and harvest equipment size were the dominant factors influencing harvesting cost and efficiency suggesting that in areas where subfields are predominantly profitable or harvesting efficiencies low, other options such as prairie strips, buffer zones around fields, and riparian areas should be investigated for more profitable biomass production and sustainable farming systems.
09 BIOMASS FUELS↗
The dual-credit policy: Quantifying the policy impact on plug-in electric vehicle sales and industry profits in China
We report that the Passenger Cars Corporate Average Fuel Consumption and New Energy Vehicle Credit Regulation (dual-credit policy) was enacted by the Chinese government in 2017 to stimulate the fuel-efficient and electrification technologies in the China's passenger vehicle market. Here, this study summarizes the dual-credit policy and develops the New Energy and Oil Consumption Credits Model to quantify the impacts of this policy on consumer choices and industry profits, where internal subsidies as decision variables are used to represent industry responses to the policy. Scenarios in 2016–2020 are simulated and discussed. Key findings from the model results include: (1) the Corporate Average Fuel Consumption rules alone may stimulate more plug-in electric vehicle (PEV) sales than the dual-credit policy; however, (2) the dual-credit policy could stimulate more battery electric vehicles (BEVs) in market, compared to other policy scenarios; (3) the industry could “lose” approximately $2122/vehicle by 2020 under the dual-credit policy; (4) battery electric sedans with a range greater than 250 km and plug-in hybrid SUVs could be popular under the dual-credit policy; (5) credit allocations for BEVs in the dual-credit policy can influence the PEV production; and (6) reduction of the fuel-efficient technology costs helps to minimize profit losses impacted by the policy.
29 ENERGY PLANNING, POLICY, AND ECONOMY↗
Data for Determining Spatially Varying Profit-Maximizing Management Practices for Miscanthus and Switchgrass Production in the Rainfed United States
The compiled datasets include county-level variables used for simulating miscanthus and switchgrass production in 2287 counties across the rainfed US including 5-year (2012-2016) averaged growing season degree days (GDD), 5-year (2012-2016) averaged growing season cumulative precipitation, National Commodity Crop Productivity Index (NCCPI) values, regional dummies (only for miscanthus), the regional-level random effect of the yield response function, N price, land cash rent, the first year fixed cost (only for switchgrass), and separate datasets for simulating an alternative model assuming a constant N rate. The GAMS codes are used to run the simulation to obtain the main results including the age-varying profit-maximizing N rate, biomass yields, and annual profits for miscanthus and switchgrass production across counties in the rainfed US. The STATA codes are used to merge and analyze simulation results and create summary statistics tables and key figures.
Age↗
Cost and profit impacts of modifying stover harvest operations to improve feedstock quality
Biomass quality attributes, and the potential tractability of those attributes, are key to a successful biomass feedstock supply chain, in addition to quantity and price. Modifying harvest operations is one potential approach to managing biomass feedstock quality for corn stover. For example, eliminating raking from stover harvest operations is proposed as an approach to reduce ash content. However, changes in the stover harvest configuration cause changes in per acre profits, per ton costs, and available supply at specified prices. Here we evaluate sensitivity of profit, cost, and supply to conversion from a three–pass to a two–pass stover harvesting configuration as a means to reduce ash content. For all simulated yields, harvest costs are 2–3 per ton cheaper for three–pass versus two–pass systems wherever residue retention coefficients are less than 0.5, and per ton costs for both systems increase dramatically where residue retention coefficients are greater than 0.7. Per acre net returns are greater under all simulated yields wherever residue sustainability retention coefficients are less than 0.6. Under these conditions, farmers lose between 13 and 49 per acre by harvesting with a two–pass rather than a three–pass system. Where competing with stover markets with less stringent quality specifications, meeting ash targets by harvesting with a two–pass system may require higher grower payments of the order of 9–25 per ton to make up for the per acre lost revenue. Here, when solving for the least–cost supply, agronomic simulations suggest about 2/3 of stover is harvested with a three–pass system.
09 BIOMASS FUELS↗
A comparison study on trading behavior and profit distribution in local energy transaction games
With the increasing integration of distributed energy resources, localized peer-to-peer energy transactions are receiving more attention since they could absorb more distributed renewables locally and stabilize the power grid. To better study the trading behavior and provide guidance for a viable local market design, different game-theoretical frameworks including cooperative and non-cooperative games are established and compared here. For the cooperative grand coalition, the maximum social welfare is guaranteed, the Shapley value and bargaining based approaches are implemented for further profit redistribution. It is shown that the asymmetrical bargaining power can be critical in the final payment clearing and it is equivalent to the Shapley value allocation if prosumers bargain based on their marginal contributions. Non-cooperative trading is formulated by using a Stackelberg bilevel model in which the upper level has the privilege in internal price setting. However, system optimum is not obtained due to competition, and the selfish leader could take away 89% of the collective benefit by price-gap based arbitraging. Aiming for a long-lasting trading market, a virtual benevolent leader and a uniform price structure in which purchase price equals selling price are tested. Experimental results indicate that maximum social welfare and a fairer profit allocation can be achieved with a uniform price structure, regardless of the selfish or benevolent attitude.
29 ENERGY PLANNING, POLICY, AND ECONOMY↗
Smart household management systems with renewable generation to increase the operation profit of a microgrid
During the past few years, due to the growth of electric power consumption, generation costs as well as rises in the level of greenhouse gases efficiency bring special focus on distributed generation. Developing distributed generation resources, especially renewable energy resources, is one of the safest ways to solve such problem. These resources have been decentralised by being installed close to the houses producing few kilowatts. Therefore, there are no losses in transmission lines and provide response for demand. Based on their benefits, the use of such energy resources should be developed in the future, but its management and optimal use is a major challenge. This has become one of the main concerns ofenergy systems researchers. In the current study, an innovative model is provided as a strategic management. It is intended to optimise the operation in smart homes consisting of generation units such as a wind turbine, solar panels, storages, and un/controllable loads. The main objective of this optimisation management is to maximise microgrid profitability for 24 h. The overall results of the model proved that the profit of microgrid increased significantly.
Hakimi, Seyed Mehdi↗
Profitability of Cellulosic Biomass Production in the Northern Great Lakes Region
Producing bioenergy feedstocks on non‐crop land can largely avoid the food price feedbacks of energy biomass production on cropland. The U.S. northern tier grassland‐to‐forest ecotone offers large areas of marginal land that is not currently cropped. In this ecological transition zone, the relative profitability of grassy vs. woody sources of energy biomass is little studied. This paper reports an exploratory investment analysis of cellulosic biomass production in the northern Great Lakes region. It compares two short‐rotation tree crops, willow ( Salix sachalinensis F. Schmidt)and hybrid poplar ( Populus nigra L. X P. maximowiczii A. Henry), and switchgrass ( Panicum virgatum L.) (a native prairie grass) to conventional mixed hay. Because biomass markets are not yet well developed, this study calculates threshold prices and yields at which biomass crops become at least as profitable as mixed grass hay. At 2010–2012 prices and available production technologies, none of the cellulosic crops is competitive with the hay baseline system. The breakeven price of energy biomass ranges from $90–100 per oven‐dry Mg −1 for all three energy crops. Breakeven yields are much more variable, due to the high cost of harvesting woody biomass. At 2010–2012 prices, necessary biomass yield increases range from 3.5‐fold for switchgrass and willow to over 25‐fold for poplar. While the ratio of input costs to revenue remains relatively constant between the northern and southern Great Lakes regions, the opportunity cost of active cropland in the southern zone is much higher, implying an economic comparative advantage for marginal land of the northern tier of the Great Lakes region.
Kells, Bradley J.↗
Opportunities for Industry to Provide Flexibility While Increasing Profitability
Supply and demand flexibility will both be needed to ensure the electricity system functions properly as the share from variable renewable generation continues to grow. Industrial manufacturing currently consumes about a third of primary energy worldwide, and electricity is projected to supply an increasing share of this demand as the global economy decarbonizes. Therefore, the ability for industry to flex demand poses an enticing opportunity to enable grid flexibility. However, large capital outlays prevent industry from voluntarily altering demand. Here we show that as battery costs continue to fall, industry will soon be able to profitably alter demand in accordance with electricity price variations. Focusing on two established industries– chlor-alkali and electric arc furnaces – and two industries with large future potential – methane pyrolysis and atmospheric CO 2 capture, we use a linear program (LP) optimization to assess the technoeconomic feasibility of flexible industrial demand across both historical and future-looking wholesale day-ahead marginal prices for the Electricity Reliability Council of Texas (ERCOT). We find positive net present values (NPV) from $\$$400K to $\$$50M using projected 2050 battery prices for industrial purchase of behind-the-meter batteries, using only arbitrage as a source of value. These results indicate that, with projected battery prices, profit-seeking industrial players could voluntarily play a future role in stabilizing a high-renewables grid where electricity prices act as accurate signals of grid needs.
29 ENERGY PLANNING, POLICY, AND ECONOMY↗
Profitability, Scalability and Optimized Siting for Waste-to-Energy Supply Chains: A Case Study on Hydrothermal Liquefaction
Waste-to-Energy (WtE) conversion technologies have the potential to simultaneously reduce waste volumes, treatment-related emissions, and carbon intensity while producing valuable energy services. However, questions remain regarding under which conditions emerging WtE technologies are feasible to deploy. In this project, we develop an optimized siting method for WtE technologies to assess cost-effective WtE processor locations, throughput scales, and profitability. We apply the model using Hydrothermal Liquefaction (HTL) as an example WtE technology. We develop calibrated capital and operating expense cost curves based on literature data to study the techno-economic characteristics of WtE supply chains. Prior to solving the siting optimization, we analyze the model parameters to describe organic waste management system behavior under four different HTL deployment configurations: Co-Processing, where HTL plants send biocrude to existing conventional refineries via assumed pipelines; Co-Location, where biorefineries are co-located with HTL plants; and two alternative Standalone Biorefining cases, where distributed HTL plants transport biocrude intermediate via either assumed pipelines or trucking to centralized biorefineries. We also define and apply several feedstock gate fee calculations, representing different revenue distribution options, to investigate how bioproduct value could impact WtE supply chain economics in terms of waste producer and processor profit or cost reduction.
09 BIOMASS FUELS↗
Agro-IBIS/THMB Modeled Yield, Nitrogen Loss, and Profitability Maps for the Raccoon River Basin, Iowa, USA
This data was used to assess the potential for improving water quality in this watershed when integrating miscanthus, a bioenergy perennial grass, on to areas of low profit under current corn-soybean management and areas of high nitrogen leaching under both current and future climate conditions. This dataset includes all observations (yield, streamflow, nitrogen loads) and model simulation data used from Dr. Kelsie Ferin’s (former PhD student with Dr. Andy VanLoocke, ISU Dept. of Agronomy) dissertation and publication in Global Change Biology – Bioenergy (DOI: 10.1111/gcbb.13078). Modeled output included in this dataset includes corn, soybean, and miscanthus yields, nitrogen leaching rates, net mineralization rates, land use cover fractions with and without the inclusion of miscanthus, profitability maps, additional soil property maps, and simulated streamflow and nitrogen loads near the outlet of the Raccoon River Basin (Van Meter, Iowa) for both historical and future climate conditions. This dataset includes a mixture of netCDF, .tiff, .csv, and .xlsx files. See README.pdf for more information.
Ferin, Kelsie↗
Machine Learning for Solar Accessibility: Implications for Low-Income Solar Expansion and Profitability
The solar industry in the US typically uses a credit score such as the FICO score as an indicator of consumer utility payment performance and credit worthiness to approve customers for new solar installations. Using data on over 800,000 utility payment performance and over 5,000 demographic variables, we compare machine learning and econometric models to predict the probability of default to credit-score cutoffs. Here, we compare these models across a variety of measures, including how they affect consumers of different socio-economic backgrounds and profitability. We find that a traditional regression analysis using a small number of variables specific to utility repayment performance greatly increases accuracy and LMI inclusivity relative to FICO score, and that using machine learning techniques further enhances model performance. Relative to FICO, the machine learning model increases the number of low-to-moderate income consumers approved for community solar by 1.1% to 4.2% depending on the stringency used for evaluating potential customers, while decreasing the default rate by 1.4 to 1.9 percentage points. Using electricity utility repayment as a proxy for solar installation repayment, shifting from a FICO score cutoff to the machine learning model increases profits by 34% to 1882% depending on the stringency used for evaluating potential customers.
Davuluri, Sruthi↗