Production Cost Model Research Articles

Utility-scale photovoltaics and storage: Decarbonizing and reducing greenhouse gases abatement costs

This study explores the performance of the Duke Energy Carolinas/Progress (DEC/DEP) electric power system under one hundred forty-one configurations combining different capacities of utility-scale photovoltaics (PV) and battery energy storage (lithium-ion batteries or BES). The different configurations include PV installations capable of providing 5–25% of the systems energy and batteries with varying duration (energy-to-power ratio) of 2, 4, and 6 h. A production cost model comprised of a day-ahead unit commitment and a real-time economic dispatch simulates the optimal operation of all the generation resources necessary to supply hourly demand and reserve requirements during the year 2016. The model represents in detail the generation fleet of the system, including 221 nuclear, natural gas, coal and hydro power generators with a combined installed capacity of 37.8 GW. Results indicate that: 1) adding BES to a power system that includes PV further reduces carbon dioxide emissions while also lowering the cost of carbon abatement. 2) The optimal power rating of a BES system that supports PV seems to be lower than 25% of the capacity of the PV. 3) BES of short duration (2-h) are more cost-effective (i.e., result in a lower cost of abatement) when the level of PV penetration is low (lower than ~12.5%), while BES of longer duration (6-h) are more cost-effective when there are larger shares of PV. 4) The installation of optimal configurations of PV + BES to reduce carbon emissions in the DEC/DEP system by ~14–57% would increase the levelized cost of electricity (LCOE) ~8–65%. 5) If projections of declining costs for the next decade materialize, the installation of up to 15 GW of PV + 1.88 GW / 3.76 GWh of BES would reduce the LCOE while achieving up to 33% reduction in carbon emissions.

Modeling the Future California Electricity Grid and Renewable Energy Integration with Electric Vehicles

This study focuses on determining the impacts and potential value of unmanaged and managed uni-directional and bi-directional charging of plug-in electric vehicles (PEVs) to integrate intermittent renewable resources in California in the year 2030. The research methodology incorporates the utilization of multiple simulation tools including V2G-SIM, SWITCH, and GridSim. SWITCH is used to predict a cost-effective generation portfolio to meet the renewable electricity goals of 60% in California by 2030. PEV charging demand is predicted by incorporating mobility behavior studies and assumptions charging infrastructure and vehicle technology improvements. Finally, the production cost model GridSim is used to quantify the impacts of managed and unmanaged vehicle-charging demand to electricity grid operations. The temporal optimization of charging sessions shows that PEVs can mitigate renewable oversupply and ramping needs substantially. The results show that 3.3 million PEVs can mitigate over-generation by ~4 terawatt hours in California—potentially saving the state up to about USD 20 billion of capital investment costs in stationary storage technologies.

The value of storage in electricity generation: A qualitative and quantitative review

Abstract Electricity storage (ES) is a technology that can complement variable renewable generation in the widely sought low-carbon future. Given the several unique features of ES, it is important for utilities, investors, and regulators to understand how ES evaluation is conducted for effective deployment. Thus, this paper reviews how the literature associates a monetary value to ES technologies. It was found that evaluation has been done via the levelized cost of storage (LCOS) calculation, production-cost models, and market-based models. Each of these methods results in a monetary value different in nature: the LCOS provides a standalone average break-even cost, production-cost models provide overall cost savings gained for the entire power system from ES deployment, and market-based models provide the compensation that storage would receive if it were to compete in the market. Advantages and disadvantages of each method were discussed. The review revealed also that storage finds the most value in providing ancillary services. Given current market/regulatory restrictions, it is argued that in the near-term ES will be more valuable in vertically-integrated utilities as opposed to market environments. Finally, current ES deployment efforts can benefit from the previous renewables uptake that occurred in the past two decades.

Recovery of energy losses using an online data-driven optimization technique

This paper investigates the energy loss due to rotor aging for a wind turbine and its recovery. Energy loss for a wind turbine is caused by formation of dust and bugs, and corrosion and erosion of the surface of the rotor by sand and rain. We present a real-time data-driven optimization algorithm that uses dither and demodulation signals to recover the energy loss by extracting online the sensitivity of the function of interest to optimize. We use a viscid–inviscid model to represent aerodynamic performance loss of the rotor due to aging. We employ time-domain aeroservoelastic simulation of the CART3 wind turbine of the National Renewable Energy Laboratory to provide a comprehensive assessment of aging and its recovery. We also investigate the impact of aging on structural loads and levelized cost of energy. Using annual energy production and WindPACT cost models of the National Renewable Energy Laboratory, the levelized cost of energy enables an overall assessment of aging and its recovery. To evaluate the impact of the energy loss recovery on structural loading, ultimate and fatigue loads for power production design load case are used. The results of this study show 6.9% reduction in the annual energy production due to aging for a class C wind condition based on IEC61400 standard. This energy loss increases the levelized cost of energy by 7.5%. Our online optimization algorithm can recover 1.7% of the energy losses, and it results in 2.0% reduction in the levelized cost of energy. Results of the ultimate loads indicate that an aged rotor reduces structural loading on most components except the main shaft where the bending moment shows an increase of 5.3%. Rotor aging also reduces the fatigue loads in most components except the tower bottom fore-aft moment with an increase of 5.5%. The statistical inference of the results shows that the proposed optimization algorithm is effective in recovering aging related energy losses of wind turbines with a confidence level of 84% based on the sampled data in this study.

A review of power system planning and operational models for flexibility assessment in high solar energy penetration scenarios

This article reviews power system flexibility assessment, which is necessary to ensure both instantaneous stability and long-term security of supply under high penetrations of variable, uncertain, and asynchronous renewable energy resources, such as solar photovoltaics. This article reviews the concept of flexibility and summarizes metrics for evaluating power system flexibility, which is not yet available in the literature. Power system planning and operational models applicable for flexibility assessment, including net load analysis, capacity expansion, production cost, and dynamic models, are reviewed in a comprehensive literature survey, with a focus on high solar and other variable renewable energy penetrations. Each of these models applies different methodological approaches and feasibility criteria appropriate at different timescales. Finally, this article presents a conceptual integrated framework to combine these models for a holistic assessment of power system flexibility requirements across all timescales, from multiyear to sub-cycle.

Real earnings management practices for meeting earnings benchmarks: Indian evidence

This study examines whether managers of Indian companies engage in earnings-increasing real earnings management practices, i.e., overproduction and reduction in discretionary expenses, viz., research and development (R&D) expenses and selling, general, and administrative (SG&A) expenses, to meet two important earnings benchmarks, i.e., avoiding losses and sustaining last year’s earnings. It further examines reduction made in three components of SG&A expenses, viz., marketing (MRK) expenses, welfare and training (W&T) expenses, and other general and administrative (OG&A) expenses, with respect to the same. This study analyses large samples from panel data of Indian companies listed on National Stock Exchange of India during the period 2000 to 2016. The analysis is based on the production cost model of Roychowdhury (J Account Econ 42(3):335–370, 2006), the R&D expense model of Gunny (Contemp Account Res 27(3):855–888, 2010), the SG&A expense models of Roychowdhury (2006), Cohen and Zarowin (J Account Econ 50(1):2–19, 2010), Gunny (2010), and Badertscher (Account Rev 86(5):1491–1518, 2011). Additionally, the study based its analysis on modified estimation models recently developed by Srivastava (Rev Account Stud 24:1277–1316, 2019) of production cost and discretionary expenses. The modified estimation models of Srivastava (2019) provide control for firm’s strategy which is an important determinant of firm’s investing decisions, especially for discretionary expenses. Consistent with Srivastava (2019), the modified estimation models exhibit substantially higher explanatory power for SG&A expenses and its components in comparison with other models. The results indicate that managers are likely to overproduce to avoid losses and to sustain last year’s earnings. This insight, however, is not supported when control is provided for firm’s strategy. Managers do not reduce spending on R&D expenses to meet earnings benchmarks. They do reduce spending on SG&A expenses for the same, which again, however, is not supported after controlling for firm’s strategy. The results pertaining to components of SG&A expenses suggest that managers reduce spending on all of its three components, i.e., MRK expenses, W&T expenses, and OG&A expenses, to avoid losses. The evidence of reduction in spending on the latter two components for the same is reinforced when control for firm’s strategy is taken into consideration. To sustain last year’s earnings, managers appear to reduce spending only on W&T expenses. This evidence, however, is not supported after controlling for firm’s strategy. Overall, the findings indicate that managers in India are more likely to manage W&T expenses to show earnings in line with desired benchmark level.

Cost implications of increased solar penetration and time-of-use rate interactions

Abstract Electricity-grid operators are facing new challenges in matching load and generation due to increased solar generation and peak-load growth. This paper demonstrates that time-of-use (TOU) rates are an effective method to address these challenges. TOU rates use price differences to incentivize conserving electricity during peak hours and encouraging use during off-peak hours. This strategy is being used across the USA, including in Arizona, California and Hawaii. This analysis used the production-cost model PLEXOS with an hourly resolution to explore how production costs, locational marginal prices and dispatch stacks (type of generation used to meet load) change due to changes in load shapes prompted by TOU rates and with additional solar generation. The modelling focused on implementing TOU rates at three different adoption (response) levels with and without additional solar generation in the Arizona balancing areas within a PLEXOS model. In most cases analysed, implementing TOU rates in Arizona reduced reserve shortages in the Western Interconnect and, in some cases, very substantially. This result is representative of the interactions that happen interconnection-wide, demonstrating the advantage of modelling the entire interconnection. Production costs were decreased by the additional solar generation and the load change from TOU rates, and high response levels reduced the production costs the most for high-solar-generation cases. Load change from TOU rates decreased locational marginal prices for a typical summer day but had inconsistent results on a high-load day. Additional solar generation decreased the usage of combustion turbines, combined cycles and coal-fired generation.

Impact of climate change on water availability and its propagation through the Western U.S. power grid

Climate change is expected to affect the availability of water for electricity generation, yet the propagation of climate impacts across a large and diverse power grid remains unexplored. In this study, we evaluate how projected changes in water availability affect electricity generation at hydroelectric and thermal power plants and how the coincident impacts propagate locally and throughout the interconnected power grid of western United States. We also evaluate whether the prospect of climate-driven change could affect regional power dependencies. Hydrologic simulations derived from three Global Circulation Models (CCSM4, INMCM4, and GFDL-CM3), two radiative scenarios (RCP4.5 and RCP8.5) and the VIC hydrology model are used to force a large-scale, distributed water management model (MOSART-WM), which translates water availability into power generation constraints at hydropower plants and water-dependent thermoelectric plants. Power system dynamics are evaluated using the production cost model PLEXOS. We find that the interregional connections across the contemporary Western U.S. electricity infrastructure play an essential role in managing variations in regional generation due to hydrological variability. Projected WECC-scale changes in mean annual precipitation ranging from −3.8% to +17% are moderated to −6% to +4% in mean annual production cost changes. Climate change impacts on water availability in the Northwest drive future changes in other regions’ generation and in regional power flows. Northwest total generation influences interannual variability in other regions’ net generation, explaining about 40%, 50%, and 35% of the variability in Southwest, Rockies, and Southern California regions respectively. The propagation of Northwest climate change impact throughout the grid is exacerbated by the occurrence of dry years in Northern California. Generation from the Desert Southwest emerges as a critical resource to compensate for variations in water availability, and generation, in these regions. Though the regional power flow directions seem insensitive to long-term variations in water availability, our analysis highlights the need to consider other compounding regional factors, such as changes in Southern California’s net load and changes in regional fuel prices.

Climate change adaptation cost and residual damage to global crop production

Adaptation will be essential in many sectors, including agriculture, as a certain level of warming is anticipated even after substantial climate mitigation. However, global adaptation costs and adaptation limits in agriculture are understudied. Here, we estimate the global adaptation cost and residual damage (climate change impacts after adaptation) for maize, rice, wheat and soybean using a global gridded crop model and empirical production cost models. Producers require additional expenditures under climate change to produce the same crop yields that would be achieved without climate change, and this difference is defined as the adaptation cost. On a decadal mean basis, the undiscounted global cost of climate change (adaptation cost plus residual damage) for the crops are projected to increase with warming from 63 US$ billion (B) at 1.5°C to $80 B at 2°C and to $128 B at 3°C per year. The adaptation cost gradually increases in absolute terms, but the share decreases from 84% of the cost of climate change ($53 B) at 1.5°C to 76% ($61 B) at 2°C and to 61% ($8 B) at 3°C. The residual damage increases from 16% ($10 B) at 1.5°C to 24% ($19 B) at 2°C and to 39% ($50 B) at 3°C. Once maintaining yields becomes difficult due to the biological limits of crops or decreased profitability, producers can no longer bear adaptation costs, and residual damages increase. Our estimates offer a basis to identify the gap between global adaptation needs and the funds available for adaptation.

Impacts of storage dispatch on revenue in electricity markets

Abstract As electricity storage deployments grow—due to decreasing costs and increasing grid flexibility requirements—market frameworks governing their dispatch and remuneration are a growing area of interest and importance. For example, the recent Federal Energy Regulatory Commission Order 841 instructs independent system operators to remove barriers of entry for storage assets. This paper reviews electricity market rules to inform an accurate representation of storage bidding behavior in day-ahead (DA) and real-time (RT) electricity markets. Storage dispatch strategies are explored using production cost and price-taker models to address two related research questions: (1) will storage assets receive the highest remuneration by bidding into DA markets, bidding into RT markets, or redispatching bids in both markets and (2) how accurate must forecast information be for a redispatch strategy to improve remuneration? Results show that with sufficient ability to forecast prices, redispatching a DA schedule in the RT takes advantage of both markets: a longer dispatch horizon as well as more volatile prices.

Demand response for variable renewable energy integration: A proposed approach and its impacts

As electricity systems integrate increasing penetrations of variable renewable energy, system operators are seeking technologies and strategies that increase their system’s flexibility. Despite obstacles around hardware, market structure, and lack of experience, demand response is an important source of flexibility that complements more conventional supply-side flexibility resources. However, accurate representations of demand response in production cost models employed for grid systems analyses have been limited by incomplete formulations, inadequate real-world data, case studies with narrow applicability, and a finite list of end uses and sectors. This paper proposes a suite of demand response constraints that capture more-realistic demand response operational limitations including uptimes and downtimes, numbers of starts per day, allowable power limits, and required recovery periods. The proposed demand response implementation is tested with real-world load data for Bangalore, India. The results show that demand response reduces production costs primarily by facilitating the substitution of high-marginal-cost thermal generators with near-zero-marginal-cost renewables. Overall, demand response utilization rates are most constrained by their maximum allowable daily deployment, but intraday recovery constraints govern their operational behavior. In addition to the significant value that demand response provides to the grid, demand response aggregators can expect substantial revenues from price arbitrage.

The Moderate Operation Scales of Apples Based on Output, Profit, and Unit Production Costs in the Shaanxi Province of China

In the Shaanxi province, small and scattered plots impede an increase in the efficiency of apple production. Developing a moderate operation scale is a proper tool to solve inefficiencies in apple production, as it enables improving the factor allocation efficiency, resulting in higher yields, higher profit, or lower production costs. However, the moderate operation scales, based on output, profit, and production costs, may be different. This paper aimed to evaluate the moderate operation scale of apples from three perspectives of increasing yields and profits and reducing unit production cost. The study was based on survey data collected from 661 randomly selected apple farmers in eight counties of the Shaanxi province, China. The collected data were analyzed quantitatively by the input-output model, the net profit model, and unit production cost model. The findings show that: (1) The moderate operation scale oriented to increasing apple yields in the Shaanxi province should be 0.87–1.53 ha. (2) The moderate operation scale oriented to increasing the net profit of farmers in the Shaanxi province should be over 1.53 ha. (3) The moderate operation scale oriented to reducing the unit cost of apple production in the Shaanxi province should be 0.20–0.53 ha. The study provides evidence that policymakers should grasp the balance point and find the intersection of the operation scale based on output, profit, and unit production cost when guiding apple growers to carry out the moderate scale. We propose that 0.87–1.53 ha may be a suitable operation scale for apple production in the Shaanxi province at the current stage.

Cycle-oriented approach to building a model of production costs

Modern science and practice does not have a sufficient set of cost management tools, taking into account the duration of the production cycle, characteristic of agricultural activity. The implementation of a cycle-oriented approach to building a model of production costs was based on studying the existing options for classifying production costs, which were supplemented with features from the perspective of managing long production cycles. As a result of the study, a model of production costs was built from the point of view of a cycle-oriented approach, as well as a model of production costs from the standpoint of features of a long production cycle. The model can serve as the basis for the formation of the information space of cost management, control and cost analysis in the economy of agricultural enterprises.

Optimization of Part Consolidation for Minimum Production Costs and Time Using Additive Manufacturing

AbstractThis research presents a method of optimizing the consolidation of parts in an assembly using metal additive manufacturing (MAM). The method generates candidates for consolidation, filters them for feasibility and structural redundancy, finds the optimal build layout of the parts, and optimizes which parts to consolidate using a genetic algorithm. Results are presented for both minimal production time and minimal production costs, respectively. The production time and cost models consider each step of the manufacturing process, including MAM build, post-processing steps such as support structure removal, and assembly. It accounts for costs affected by part consolidation, including machine costs, material, scrap, energy consumption, and labor requirements. We find that developing a closed-loop filter that excludes consolidation candidates that are structurally redundant with others dramatically reduces the number of candidates, thereby significantly reducing convergence time. Results show that when increasing the number of parts that are consolidated, the production cost and time at first decrease due to reduced assembly steps, and then increase due to additional support structures needed to uphold the larger, consolidated parts. We present a rationale and evidence justifying that this is an important tradeoff of part consolidation that generalizes to many types of assemblies. Subsystems that are smaller, or can be oriented with very little support structures or have low material costs or fast deposition rates can have an optimum at full consolidation; for other subsystems, the optimum is less than 100%. The presented method offers a promising pathway to minimize production time and cost by consolidating parts using MAM. In our test-bed results for an aircraft fairing produced with powder-bed electron beam melting, the solution for minimizing production cost (time) is to consolidate 17 components into four (two) discrete parts, which leads to a 20% (25%) reduction in unit production cost (time).

Exponentially Convergent Receding Horizon Strategy for Constrained Optimal Control

Receding horizon control has been a widespread method in industrial control engineering as well as an extensively studied subject in control theory. In this work, we consider a lag L receding horizon strategy that applies the initial L optimal controls from each quadratic program to each receding horizon. We investigate a discrete-time and time-varying linear-quadratic optimal control problem that includes a nonzero reference trajectory and constraints on both state and control. We prove that, under boundedness and controllability conditions, the solution obtained by the receding horizon strategy converges to the solution of the full problem interval exponentially fast in the length of the receding horizon for some lag L. The exponential rate of convergence provides a systematic way of choosing the receding horizon length given a desired accuracy level. We illustrate our theoretical findings using a small, synthetic production cost model with real demand data.

Climate change and future power systems: the importance of energy storage in reduced-hydropower systems in the American Southwest

Abstract Power systems are responding to climate change both through efforts to reduce greenhouse-gas emissions and through adaptive responses to the effects of climate change, such as changes in hydroelectric generation. These changes, experienced together, may cause new patterns in plant operations or pollutant emissions. Various scenarios representing future climate change mitigation and adaptation in the power sector were explored using the PLEXOS production-cost model, with a focus on plant utilization and behaviour, total system-operating costs and total CO2 emissions. Further, the effect of introducing widespread utility-scale energy storage into these scenarios was quantified in terms of these same parameters. Large increases in variable renewable penetration combined with extreme reduction of hydroelectric generation in the American Southwest (based on climate modelling in the Colorado River basin and actual drought experience in California) caused significant increases in thermal plant start-up/shutdown cycling. The introduction of storage significantly reduced this cycling, without a material increase in CO2 emissions. Storage introduced on even a modest scale can provide considerable flexibility under a range of future power-system circumstances that might be experienced due to climate change.

Evaluating resource adequacy impacts on energy market prices across wind and solar penetration levels

This study evaluates market impacts of excess capacity across various wind and solar system penetrations. First, different fleet compositions are simulated in a production cost model to yield price outputs. Price statistics reveal a strong relationship between scarcity price events, resource adequacy, and the mean and standard deviation of prices. Next, a method is presented for adjusting resource adequacy to a chosen level, which links a capacity expansion model with a probabilistic resource adequacy model.

PSII-22 Impact of stocking density and number of pigs per feeder space with wet/dry feeders: an economic analysis

Abstract The objective of this study was to evaluate the economically most profitable stocking density (SDEN) and the number of pigs per feeder space (PF) with a Crystal Springs wet/dry single-space double-sided feeder model F1-115. Data from a trial was used to model the optimal value. The initial trial included 3182 pigs from three consecutive grow-finish groups. The experimental treatments were designed as a two by three factorial (SDEN of 0.65 or 0.78 m2/pig with PF of 10, 13, or 16). Each pen was equipped with one double-sided wet/dry feeder, 37.5 cm wide, with one nipple drinker. Pigs with less floor space allowance had reduced ADG (1.00 versus 1.02 kg/d, P = 0.002) with improved G:F (0.402 versus 0.397, P = 0.039). Overall, ADG had a quadratic relationship (P = 0.005) with PF with means of 1.03, 1.01, and 1.01 kg/d for 10, 13, and 16 respectively. The G:F had a quadratic relationship (P = 0.005) with the number of pigs PF with means of 0.395, 0.404, and 0.400 for 10, 13, and 16 respectively. The G:F and ADG data were fitted to a regression equation including SDEN (linear) and PF (linear –quadratic). A pork production cost model was used to evaluate the impact of a range of SDEN (0.65 to 0.758 m2/pig) and PF (10 to 16) on annual profit of a grow-finish barn including feeder cost. Annual profit for a 1200 head grow-finisher was fitted to linear and quadratic regression of SDEN and PF (R2= 0.999). The optimal SDEN was 0.65 m2 per pig and 13 to 14 (13.26) PF. The differences between the maximum and the minimum net income year values for PF and PF were $4055 and $21667 USD respectively. Stocking density had a greater impact than the number of pigs per feeder space.

The IEEE Reliability Test System: A Proposed 2019 Update

The evolving nature of electricity production, transmission, and consumption necessitates an update to the IEEE's Reliability Test System (RTS), which was last modernized in 1996. The update presented here introduces a generation mix more representative of modern power systems, with the removal of several nuclear and oil-generating units and the addition of natural gas, wind, solar photovoltaics, concentrating solar power, and energy storage. The update includes assigning the test system a geographic location in the southwestern United States to enable the integration of spatio-temporally consistent wind, solar, and load data with forecasts. Additional updates include common RTS transmission modifications in published literature, definitions for reserve product requirements, and market simulation descriptions to enable benchmarking of multi-period power system scheduling problems. The final section presents example results from a production cost modeling simulation on the updated RTS system data.

Sensitivity of Western U.S. power system dynamics to droughts compounded with fuel price variability

The energy sector is heavily dependent on surface water availability for reliable electricity generation. Power system operations are usually evaluated through system reliability and economic perspectives, with assumptions based on market prices and normal water availability. As natural gas technologies continue to dominate new thermal capacity, replacing retiring coal and nuclear generators, natural gas price stability becomes increasingly important and the impact of price volatility on grid operations must be understood. Here, we explore the range of Western Electricity Coordinating Council (WECC) regional power operations, which represents the electric interconnection over the western half of the continental United States, using a production cost model driven by different fuel prices and an integrated hydrology model to simulate historical water availability. Our results show system-wide operation costs increasing in drought years or when gas prices increase, as expected. In addition, we found those system-wide increases can be of the same magnitude. Regional analysis of the responses to compounded droughts and price volatility highlight differences in magnitude and direction depending on regional generation technology portfolios. The Pacific Northwest is most sensitive to drought conditions, Southern California is most sensitive to gas prices, and the Desert Southwest is sensitive to both with the same magnitude. This analysis motivates further research in combined hydrology and power system modeling to characterize regional dynamics and associated uncertainties across scales, which is an important underpinning for the development of more resilient energy and water systems.