Net Present Value Research Articles

Public-private partnerships scheme of pioneer train case study in South Sumatera area

Pioneer trains in Indonesia have been fully funded by the government. The construction needs a lot of funding that would burden the state budget. One of the alternatives is the public-private partnership scheme. This study aims to analyze the most effective unbundling scenario for financing and maintaining the Indralaya-Tanjung Senai train. The life cycle costs and conducting sensitivity analysis according to applicable regulations. The scenarios are based on ticket price increases and government support for the operation and maintenance (O&M) for this pioneer train route, calculated net present value (NPV) and internal rate of return (IRR) value. Scenario 1 assumes that tickets do not receive subsidies; private companies are responsible for O&M costs. Scenario 2 assumes that ticket prices are set by private companies; the government is responsible for procurement and maintenance costs. Scenario 3 assumes that the government provides subsidies of IDR 10,000 per passenger as well as railway infrastructure; private companies bear the cost of procuring railbuses and operational expenses. Based on calculations with Scenario 1 NPV is IDR 0.73 billion; with Scenario 2 is IDR 4.64 billion and with Scenario 3 is IDR (–)1.34 billion. The analysis shows that increasing passenger fares according to price raises and inflation rates, and subsidies from governments for maintenance costs will make this railroad project financially feasible.

Pine needle gasification-based electricity production: Understanding the effect of supply chain.

Pine needles (pine tree leaves), found abundantly across continents such as North America, Asia, Europe, South America, Africa, and parts of the Southern Hemisphere, are a significant global concern due to their high susceptibility to catching fire, especially in dry and hot climates. The same issue persists in the Uttarakhand state of India, which boasts ample pine forests, yielding a substantial 1.67 × 109kg of pine needles annually. In the present study, the annual potential emissions from forest fires in Uttarakhand were estimated to be 58.37 × 109kg of CO2 equivalent. Therefore, the present research aims to unlock pine needles' potential via gasification for green electricity and biochar production, offering an alternative to coal-based plants while reducing forest fire frequencies. Nevertheless, obstacles hindering pine needle gasification include an unsteady supply chain, limited collection windows (100days), and plant expenses, including transportation and operational costs. The primary focus of the research is to design and assess the performance of a gasification-based supply chain for pine needles in the Almora District of Uttarakhand. Ten plant capacity scenarios were considered, ranging from 25 to 250kW. The study incorporated critical factors, encompassing diverse losses within the supply chain, selecting potential plant sites, minimizing transportation distance, and evaluating the supply chain's economic and environmental performance. The economic analysis revealed that the 250-kW plant scenario exhibited a minimum discounted payback period (DPP) of 3.93years, alongside an internal rate of return (IRR) of 19% and a net present value (NPV) of 653.32 million INR without government subsidies. With subsidies included, the DPP decreased to 1.30years, improving the IRR to 69% with an NPV of 916.17 million INR. The emission analysis indicated that gasification plant capacity scenarios could potentially reduce 44.63 × 106 to 46.16 × 106kg of CO2 equivalent emissions annually compared to grid electricity while meeting nearly 5.5% of the electricity demand of Almora district. The present study aligns with SDG-7 (Affordable and Clean Energy), SDG-13 (Climate Action), SDG-9 (Industry, Innovation, and Infrastructure), SDG-11 (Sustainable Cities and Communities), SDG-3 (Good Health and Well-being), and SDG-15 (Life on Land).

Subsidy Policies and Economic Analysis of Photovoltaic Energy Storage Integration in China

In the context of China’s new power system, various regions have implemented policies mandating the integration of new energy sources with energy storage, while also introducing subsidies to alleviate project cost pressures. Currently, there is a lack of subsidy analysis for photovoltaic energy storage integration projects. In order to systematically assess the economic viability of photovoltaic energy storage integration projects after considering energy storage subsidies, this paper reviews relevant policies in the Chinese photovoltaic energy storage market. It analyzes the cost and revenue composition of photovoltaic energy storage integration projects, and constructs a system dynamics model for the levelized cost of electricity (LCOE) of such projects. Taking a specific photovoltaic energy storage project as an example, this paper measures the levelized cost of electricity and the investment return rate under different energy storage scenarios. Combining energy storage allocation ratios and internal rate of return indicators, this paper analyzes the net present value of photovoltaic energy storage integration projects under different subsidy standards. The results indicate that, while the current energy storage subsidy policies positively stimulate photovoltaic energy storage integration projects, they exhibit a limited capacity to cover energy storage investment costs, thereby failing to incentivize capital market participation in the construction of such projects. Rational allocation of energy storage capacity and optimization of corresponding subsidy policies are crucial prerequisites for enhancing the economic viability and widespread adoption of photovoltaic energy storage integration projects. This study not only aids in investment decision making for photovoltaic power stations but also contributes to the formulation of energy storage subsidy policies.

The economics of farming expansion in the Brazilian Cerrado under possible effects of climate change

Abstract This analysis assesses the financial viability of legally investing in native Cerrado vegetation deforestation for crop production, considering climate change. The study uses data from twelve different crop models based on three different climate models to predict potential future crop yields in cleared land for growing soy and maize. The outcomes show that in many micro-regions, investments in clearing land for crop production would destroy economic value, that is, generate a negative net present value because of low/negative and volatile cashflows driven primarily by future yields as affected by climate. Our analysis was carried out based on present agricultural practices and technology. As climate changes, farmers may adapt their practices, which can lead to more resilient and productive crops, or grow different crops, which could provide better returns on investment in clearing land than the ones resulting from our analysis. Despite various uncertainties, farmers, policy makers and financial institutions should be aware of the climatic and financial risks associated with land clearing in Brazil, mainly in micro-regions in which all scenarios resulted in negative outcomes in the investment analysis.

A Net Present Value Analysis of Opportunity-Based Age Replacement Models in Discrete Time

Two important opportunistic age replacement models, under replacement first and last disciplines, are generalized in discrete time. The net present value (NPV) is applied to formulate the expected total costs. The priority of multiple replacement options is considered to classify the cost model with discounting into six cases. Since the NPV method accurately calculates the expected replacement costs over an infinite horizon in an unstable economic environment, we discuss some optimal opportunistic age replacement policies which minimize the expected total discounted costs over an infinite time horizon. Furthermore, we formulate a unified model under each discipline, merging six discrete time replacement models with probabilistic priority. Finally, a case study on optimal replacement first and last policies for pole air switches in a Japanese power company is presented.

Effects of the U.S. inflation reduction act on SMR economics

The U.S. Inflation Reduction Act (IRA) of 2022 provides a wide array of tax credits and other incentives for low-carbon energy. The technology-neutral clean generation production tax credit (PTC) (Section 45Y of the U.S. Internal Revenue Code) and the technology-neutral investment tax credit (ITC) (Section 48E) lower the net cost of new electricity generation projects with zero or negative greenhouse gas emission rates. We evaluate the impact of the IRA legislation—specifically the PTC and ITC—on the cost-competitiveness of small modular reactors (SMRs). We use the Argonne Low-carbon Energy Analysis Framework (A-LEAF) model to calculate the capacity factor of an SMR with a range of hypothetical variable operating and maintenance (O&M) costs in the Electric Reliability Council of Texas (ERCOT) electricity market. We selected ERCOT for market modeling because of its competitive structure, available data, and extensive use in prior literature. We use a discounted cash flow model to calculate the SMR’s net present value based on the market prices and capacity factors from A-LEAF, hypothetical ranges of capital and variable O&M costs, and other input parameters, with or without the IRA tax credits. We determine the SMR owner’s optimal choice of PTC or ITC for the hypothetical ranges of capital and variable O&M costs. We also evaluate potential shifts in the SMR owner’s optimal choice of PTC or ITC based on historical patterns of nuclear capital cost overruns in the United States. We also assess the sensitivity of our results to longer PTC period and electricity prices from the New England market, which tend to be higher than electricity prices in ERCOT. We find that even with the IRA tax credits, only SMRs with low capital and variable O&M costs would be economically feasible in the low-price ERCOT market scenario modeled. A longer PTC period and higher-price market such as New England, however, would significantly expand the economic feasibility of SMRs in the United States.

Techno economic analysis of the production of potato powder applying potato starch purification system in Japan

To implement the technology for producing potato powder, significant investment is required. This study evaluated the techno-economic feasibility of the dried potato powder production process, based on a scenario developed in a starch plant process in Japan. The simulation was performed with SuperPro Designer® software. The annual production volume and the unit production cost were estimated to be 15,786,585 kg and 1056 Japanese yen/kg, respectively. According to economic evaluation indicators—the gross margin, return on investment, payback time, internal rate of return, and net present value (at a 7% interest rate)—the scenario was profitable and investment worthwhile. A sensitivity analysis was conducted to evaluate the impact of the variable parameters (the purchasing price of raw potatoes, the selling price of potato powder, and labor and electricity costs) on the net present value (at the 7% interest rate). The analysis suggested that the purchasing price of raw potatoes and the selling price of potato powder had particularly large impacts on the net present value.

A novel green methanol – heat cogeneration system based on municipal solid waste plasma gasification and coke oven gas: Energy, exergy, economic, and environmental assessment

Burning municipal solid waste for disposal contributes significantly to atmospheric pollution. Utilizing municipal solid waste for green methanol production can alleviate environmental burdens. This study proposes a novel approach based on municipal solid waste plasma gasification, integrating coke oven gas catalytic reforming for green methanol synthesis. A comparative analysis is conducted against a conventional scheme involving water gas shift for syngas production. Simulation models of both approaches are constructed, revealing that the newly proposed system achieves higher methanol synthesis yield and energy utilization efficiency at 90.57 % and 61.28 %, respectively, with an exergy efficiency of 63.74 %. The project incurs an investment cost of 11,448.70 k$, with a dynamic payback period of 4.18 years after a 1-year construction cycle. The net present value over a 25-year operational span is 21,899.16 k$. Additionally, the proposed system emits less than 0.06 tons of carbon dioxide per ton of green methanol, significantly lower than the 0.72 tons emitted by the water gas shift-adjusted syngas synthesis scheme. It makes the proposed approach a potential negative carbon emitter compared to municipal solid waste incineration. Therefore, the system demonstrates favorable thermodynamic performance, coupling with substantial economic and environmental benefits.

Multi-aspect assessment of a novel geothermal-driven polygeneration arrangement using water electrolyzer, methanol synthesis unit, and Goswami cycle

Geothermal energy’s renewable nature with minimal emissions compared to fossil fuels has led to valuable polygeneration models in geothermal-rich regions, promoting energy sustainability. Key challenges include improving integrated structures due to these resources’ low/medium temperature nature and assessing the feasibility of producing essential products (e.g., hydrogen and methanol), typically produced in structures with substantial pollution. The proposed system’s innovations focus on reducing irreversibility through thermal integration, introducing a negative CO2 emission structure, and utilizing CO2 hydrogenation based on geothermal energy for methanol production. Hence, the system encompasses a geothermal power plant, a Goswami cycle, a direct hydrogenation methanol synthesis unit, and a proton exchange membrane electrolyzer. The findings show generating methanol at a rate of 0.85 kg/s, domestic hot water at a rate of 2.231 kg/s, chilled water at a rate of 3.931 kg/s, and electric power at a capacity of 21,530 kW. Hence, the system’s thermal, electrical, and exergy efficiencies are determined to be 7.54 %, 3.87 %, and 47 %, respectively. Furthermore, the sum unit cost of products and the levelized energy cost equal 0.0272 $/GJ and 0.17 $/kWh, correspondingly. Additionally, a net present value of 65.86 M$ and a total yearly cost of 37.52 M$ are the results of the economic assessment. The current research demonstrates a negative CO2 emission from an environmental standpoint. The attainment of negative CO2 emissions is due to using CO2 as input material in the system. Also, the system’s net present value surpasses the total annual cost by 1.75 times, mainly due to its ability to produce products like methanol, generating revenue to offset initial costs. The proposed system is ideal for geothermal energy sites near seawater, promoting environmental preservation by reducing pollutants. Finally, it is suggested that the system’s operation be optimized and an experiential setup be used for future research.

The Optimal Infrastructure Design for Grid-to-Vehicle (G2V) Service: A Case Study Based on the Monash Microgrid

The electrification of the transport sector has emerged as a game changer in addressing the issues of climate change caused by global warming. However, the unregulated expansion and simplistic approach to electric vehicle (EV) charging pose substantial risks to grid stability and efficiency. Intelligent charging techniques using Information and Communication Technology, known as smart charging, enable the transformation of the EV fleets from passive consumers to active participants within the grid ecosystem. This concept facilitates the EV fleet’s contribution to various grid services, enhancing grid functionality and resilience. This paper investigates the optimal infrastructure design for a smart charging system within the Monash microgrid (Clayton campus). We introduce a centralized Grid-to-Vehicle (G2V) algorithm and formulate three optimization problems utilizing linear and least-squares programming methods. These problems address tariff structures between the main grid and microgrid, aiming to maximize aggregator profits or minimize load fluctuations while meeting EV users’ charging needs. Additionally, our framework incorporates network-aware coordination via the Newton–Raphson method, leveraging EVs’ charging flexibility to mitigate congestion and node voltage issues. We evaluate the G2V algorithm’s performance under increasing EV user demand through simulation and analyze the net present value (NPV) over 15 years. The results highlight the effectiveness of our proposed framework in optimizing grid operation management. Moreover, our case study offers valuable insights into an efficient investment strategy for deploying the G2V system on campus.

Techno-economic assessment of renewable hydrogen production for mobility: A case study

Renewable hydrogen produced by water electrolysis from intermittent energy sources (i.e. sun and wind) is considered one of the most promising energy carriers for the decarbonisation of the so-called “hard-to-abate” sectors, especially heavy-duty transport and industry. To this reason, several new projects are currently under development and public fundings are widely available to boost the renewable hydrogen market. In this fast-changing scenario, this paper presents the techno-economic analysis of an integrated system where renewable power generation, electrolytic hydrogen production and final hydrogen use are closely integrated within a specific site, allowing higher efficiency as well as a containment of hydrogen production and handling cost. The analysis here presented considers a specific case study that includes a 12.5 MWP photovoltaic plant, a 5 MW electrolyser capable to produce nearly 300 t/yr. of renewable hydrogen, and a compression and storage system, all located in Sardinia (Italy). Differently from previous studies, this work faces the analysis from two opposite perspectives: on the one hand, it allows the assessment of the levelized cost of hydrogen during the whole project’s life, making the results comparable to those from other similar analyses; on the other hand, it presents the calculation of project’s profitability in terms of net present value, internal rate of return and payback time from the perspective of a potential investor. The analysis shows that a whole investment of about 20.3 M€ is required, which allows to achieve a levelised cost of hydrogen of 4.09 €/kg, which can decrease to 2.97 €/kg considering the revenues from selling oxygen and the overproduction of electricity. The potential use of renewable hydrogen in urban public transport (by means of fuel cell electric vehicles) has been considered as well, in comparison with conventional diesel buses. Despite the lower cost for fuel (0.41 €/km for hydrogen buses vs. 0.72 €/km for diesel buses) and maintenance and repair (0.20 €/km vs. 0.27 €/km), as well as the lower CO2 emission (some 76 t/yr. saved per bus), the very high investment cost for hydrogen-fuelled buses (up to 720,000 €) makes hydrogen still not competitive with diesel for urban transport, being hydrogen buses characterised by a whole specific transport cost of 1.45 €/km, to be compared with 1.04 €/km for diesel buses.

Modelling and analysis of heat pump integrated Photovoltaics-Wind systems for an agricultural greenhouse in Turkey

This study focused on modelling and analysing photovoltaics and wind systems to meet the heating demand of a commercial greenhouse. The aim is to evaluate technical, economic, and environmental performances of the related systems and to determine the optimum configuration. A novel approach was introduced by integrating hybrid energy systems with large-scale wind turbines and developing a dynamic heat transfer model. A large commercial greenhouse with an area of 26,640 m2 located in Izmir, Turkey was selected for considering Mediterranean climate, and a detailed heat transfer model of the greenhouse were developed considering heat transfers by convection, radiation, ventilation, and infiltration. A combination of air source heat pumps, photovoltaic panels and wind turbines were used for meeting the heating demand of the related greenhouse. Five different on-grid energy systems scenarios, namely (i) Photovoltaics-Heat Pump, (ii) Photovoltaics-Wind Turbine- Heat Pump, (iii) Wind Turbine- Photovoltaics- Heat Pump (iv) Wind Turbine- Heat Pump, and (v) only Heat Pump were considered. The system modelling with a detailed heat transfer analysis of the greenhouse was made by MATLAB. The energy analysis of the systems was performed on an hourly basis for one calendar year. The annual heating demand and the corresponding electricity consumption of the greenhouse were calculated as 497.37 and 114.07 kWh/m2, respectively. Net Present Value, Levelized Cost of Energy and CO2 savings were used to evaluate economic and environmental performances of the systems. Among five on-grid energy system scenarios, the first scenario, consisting of 5271 photovoltaic panels and 20 heat pumps, emerged as the most economically attractive choice with Net Present Value and Levelized Cost of Energy of $547,440.40 and 0.080146 $/kWh, respectively. Critical parameters affecting the economy of this scenario were found to be electricity prices, tomato yield, and photovoltaic panel prices. For environmental evaluation the fourth scenario, integrating wind turbines and heat pumps, achieves the highest CO2 savings of 2,064.73 tons due to increased renewable electricity production and lower life-cycle CO2 emissions of wind turbines compared to photovoltaic systems. This analysis enhanced the understanding of energy dynamics in greenhouse environments, contributing to the advancement of sustainable practices in agriculture.

Evaluating economic feasibility of liquid air energy storage systems in US and European markets

Liquid air energy storage is a clean and scalable long-duration energy storage technology capable of delivering multiple gigawatt-hours of storage. The inherent locatability of this technology unlocks nearly universal siting opportunities for grid-scale storage, which were previously unavailable with traditional technologies such as pumped hydro energy storage and compressed air energy storage. While the technical viability of liquid air energy storage has been established, its economic viability has not yet been rigorously assessed across diverse electricity markets. In this work, a mixed-integer linear program was used to conduct a high-level economic analysis of this technology in US and European markets. By simultaneously optimizing the design and operation of liquid air energy storage systems to maximize their net present value, a yes/no indication of their economic viability can be obtained. Using this approach, the economic viability of this technology was established for the West load zone of Texas through identification of a system with an optimal net present value of $10.4 million and a levelized cost of storage of $119/MWh. Sensitivity analyses were also performed to elucidate how improved technical performance and economic incentives might affect the economic feasibility and, consequently, the adoption of this technology more broadly in the future.

An enhanced refresher on discounted net present value computations with an additional focus on risk and uncertainty

AbstractDiscounted present value (DPV) calculations have appeared in textbooks as well as numerous peer‐reviewed journal articles. Such articles address a wide variety of topics/issues, ranging from migration to educational pursuit to investment in new plant and equipment to the NFL draft. Recognizing the remarkably versatile and useful tools that the DPV concepts are to valuation and intelligent decision‐making, some years ago, the Harvard Business Review published a discussion by Gallo of the derivation and uses of DPVs (and NPVs). This note extends and corrects the analysis in Gallo so as to make it more accurate and useful to the reader.

The new bond on the block — Designing a carbon-linked bond for sustainable investment projects

Over the last decade, the green bond market experienced strong growth rates fueled by the need to combat climate change. However, the discourse on enhancing the effectiveness of green bonds primarily revolves around regulatory measures, often overlooking the possibility of designing inherent incentives. We show that a green bond with a coupon structure positively related to the carbon price development stimulates (early) investment in an emission-reducing project and creates higher net present values (NPVs) when applied in project financing. In our simulation-based framework, we model carbon prices using a geometric Brownian motion, and create a general optimal stopping time problem regarding the start of the project. The green bond in our setting carries the risk of default, also mitigated by its carbon price-linked coupon structure.

Rice husk reuse as a sustainable energy alternative in Tolima, Colombia

Colombia has great potential to produce clean energy through the use of residual biomass from the agricultural sector, such as residues obtained from the life cycle of rice production. This document presents a mixed approach methodology study to examine the combustion of rice husks as a possible energy alternative in the Tolima department of Colombia. First, the physicochemical characteristics of the rice husk were analyzed to characterize the raw material. Next, System Advisor Model (SAM) software was used to model a bioenergy plant to obtain biochar, bio-oil, and biogas from the combustion of rice husks and generate performance matrices, such as thermal efficiency, heat rate, and capacity factor. Then, the project was evaluated for financial feasibility using a mathematical model of net present value (NPV) with a planning horizon of 5 years. Finally, a subset of the local population was surveyed to assess perspectives on the project in the region. The results of the rice husk physicochemical analysis were the following: nitrogen content (0.74%), organic carbon (38.04%), silica (18.39%), humidity determination (7.68%), ash (19.4%), presence of carbonates (< 0.01%), and pH (6.41). These properties are adequate for the combustion process. The SAM simulation showed that the heat transferred in the boiler was 3180 kW, maintaining an efficiency between 50 and 52% throughout the 12 months of the year, meaning that the rice husk can generate electricity and thermal energy. The financial analysis showed that the internal rate of return (IRR) was 6% higher than the opportunity interest rate (OIR), demonstrating economic feasibility of the project. The design and creation of a rice husk processing plant is socially and environmentally viable and has the potential to contribute to the economic development of the Tolima community and reduce greenhouse gases. Likewise, this activity has the potential to promote energy security for consumers and environmental sustainability while at the same time being economically competitive.

ТЕХНИКО-ЭКОНОМИЧЕСКИЕ И СОЦИАЛЬНЫЕ АСПЕКТЫ СИСТЕМЫ "УМНЫЙ ДОМ" ДЛЯ РАБОТНИКОВ АГРОПРОМЫШЛЕННОГО КОМПЛЕКСА РОССИИ

Ensuring the efficient operation of agricultural enterprises depends on many factors, including the availability of qualified specialists. An important condition for attracting personnel to rural areas is the creation of comfortable social and living conditions. The Smart house system makes it possible to create comfortable social and living conditions for young professionals to live in rural areas. At the same time, these systems are complex and expensive, so their implementation requires a comprehensive study of technical, economic and social aspects. The article presents the Smart House concept for a rural residential building with an area of 150 m2 in the Krasnoyarsk Region of the Russian Federation. An important issue is the development of a methodology for assessing the economic efficiency of a project. Efficiency criteria should consider not only cost indicators, but also assessment of social effects. A list of qualitative parameters has been compiled and a methodology for their calculation is given. Calculation of efficiency indicators has been carried out. According to the results of a feasibility study for the use of the automated Smart House system, the reduction in operating costs is 460 thousand rubles/year. By saving on electricity bills and reducing the risk of economic losses, as well as improving the standard of living of rural specialists, it is possible to recoup additional costs within 2 years. Net present value for 3 years will be 118 thousand rubles.

Comparison of different hydrogen-ammonia energy conversion pathways for renewable energy supply

Hydrogen and ammonia are considered promising energy carriers for renewable energy due to their environmental friendliness and medium- and long-term storage cost advantages. However, a single hydrogen or ammonia energy strategy generally cannot meet the demand, limiting widespread application. Here we consider the whole process of renewable energy generation-transmission-storage-consumption, and propose a hydrogen-ammonia combined operation strategy. Assuming a rated power of 40 MW for generation and 10 MW for demand, we compare five energy conversion pathways: hydrogen or ammonia pipeline transmission, high-voltage alternating current (HVAC) transmission with hydrogen or ammonia storage, and HVAC transmission with hydrogen-ammonia hybrid energy storage. Results indicate that for a transmission distance of 100 km, the most economical pathway is HVAC transmission with hydrogen-ammonia hybrid energy storage, with a net present value (NPV) of 39.31 M$ and a levelized cost of electricity (LCOE) of 0.081 $/kWh. Sensitivity analyses reveal that a 0.01 $/kWh increase in electricity price leads to NPV growths of 11.75–16.02 M$. This pathway achieves zero carbon footprint and saves 4.7 M$ annually in carbon taxes. Compared to traditional production methods, this pathway is equivalent to reducing emissions by 94,189 tons.

Sensitivity Analysis of the Cost Coefficients in Multiobjective Integer Linear Optimization

This paper considers sensitivity analysis of the cost coefficients in multiobjective integer linear programming problems. We define the sensitivity region as the set of simultaneous changes to the coefficients for which the efficient set and its structure remain the same. In particular, we require that the component-wise relation between efficient solutions is preserved and that inefficient solutions remain inefficient, and we show that this is sufficient for the efficient set to be the same upon changes. For a single coefficient, we show that a subset of the inefficient solutions can be excluded from consideration. More specifically, we prove that it suffices to inspect the inefficient solutions of a q-objective problem that are efficient in one of two related q + 1-objective problems. Finally, we show that the sensitivity region is a convex set (an interval). Our approach generalizes to simultaneous changes in multiple coefficients. For illustration, we consider mean-variance capital budgeting and determine the region for which the set of efficient portfolios remains the same, despite a misspecification or a change in the net present values of the projects. Further computational experience with multiobjective binary and integer knapsack problems demonstrates the general applicability of our technique. For instance, we obtain all sensitivity intervals for changes to single coefficients of biobjective problems with 500 binary variables in less than half an hour of CPU time by excluding a large number of inefficient solutions. In fact, the number of excluded solutions is above 100 orders of magnitude larger than the number of remaining solutions. This paper was accepted by Chung Piaw Teo, optimization. Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2021.01406 .

Integrated Optimization of Hybrid Steam-Solvent Injection in Post-CHOPS Reservoirs with Consideration of Wormhole Networks and Foamy Oil Behavior

Summary For this paper, integrated techniques have been developed to optimize the performance of the hybrid steam-solvent injection processes in a depleted post-cold heavy oil production with sand (CHOPS) reservoir with consideration of wormhole networks and foamy oil behavior. After a reservoir geological model has been built and calibrated with the measured production profiles, its wormhole network is inversely determined using the newly developed pressure-gradient-based (PGB) sand failure criterion. Such a calibrated reservoir geological model is then used to maximize the net present value (NPV) of a hybrid steam-solvent injection process by selecting injection time, soaking time, production time, injection rate, steam temperature, and steam quality as the controlling variables. The genetic algorithm (GA) has been integrated with orthogonal array (OA) and Tabu search to maximize the NPV by delaying the displacement front as well as extending the reservoir life under various strategies. Considering the wormhole network and foamy oil behavior and using the NPV as the objective function, such a modified algorithm can be used to allocate and optimize the production-injection strategies of each huff ‘n’ puff (HnP) cycle in a post-CHOPS reservoir with altered porosity and increased permeability within a unified, consistent, and efficient framework.