Cost Minimization Model Research Articles

Quantifying the economic effects of ravulizumab versus eculizumab treatment in patients with atypical hemolytic uremic syndrome

Aims This study compared the aggregate duration of treatment administration of approved eculizumab and ravulizumab treatment regimens and resultant productivity implications for patients with atypical hemolytic uremic syndrome (aHUS) and their caregivers. Methods The aggregate duration of treatment administration (which includes waiting time for medication preparation and time for infusion, recovery, and travel to and from the clinic) was determined for a hypothetical population of patients with aHUS treated with eculizumab (10 mg/mL) or ravulizumab (10 or 100 mg/mL), in the clinic or at home, for 1 year, in Germany, Italy, the UK, and the US. The data for US patients treated in the clinic was used to extend a previously published cost-minimization model (CMM) to estimate the annual lost productivity associated with treatment administration and to compare the overall annual treatment costs for hypothetical adult and pediatric patients in the US. Results The aggregate duration of treatment administration associated with ravulizumab 10 mg/mL and 100 mg/mL was reduced by 44–52% and 69–74%, respectively, compared with eculizumab 10 mg/mL, across all four countries. Using the CMM, the adult and pediatric US patient lost productivity costs due to treatment were reduced by 56–60% and 73–76% with ravulizumab 10 mg/mL and 100 mg/mL, respectively, compared with eculizumab 10 mg/mL, and overall discounted annual treatment costs (direct and lost productivity costs owing to treatment) were reduced for ravulizumab (10 mg/mL and 100 mg/mL) vs eculizumab 10 mg/mL for adult and pediatric patients. Limitations This study was based on hypothetical patients, and assumptions were made regarding caregiver involvement, patient characteristics, and treatment patterns. Conclusions Compared with eculizumab, ravulizumab reduces the lost productivity costs associated with treatment. This reduction in costs is greater with the ravulizumab 100 mg/mL formulation, compared with ravulizumab 10 mg/mL, owing to shorter infusion times with this more concentrated formulation.

Myanmar's Optimal Power Generation Mix and Grid Interconnection Considering Climate Policies: A Quantitative Analysis Using a Cost Minimization Model

Myanmar's Optimal Power Generation Mix and Grid Interconnection Considering Climate Policies: A Quantitative Analysis Using a Cost Minimization Model

POSB73 Cost-Minimization Analysis for Subcutaneous Daratumumab in the Treatment of Multiple Myeloma in Italy

Daratumumab administered via an intravenous infusion (dara-IV) is currently approved for the treatment of patients with multiple myeloma, both newly diagnosed (NDMM) and relapsed/refractory (RRMM). A daratumumab formulation for subcutaneous administration (dara-SC) was developed with the goal of shortening treatment duration without compromising safety and efficacy. Dara-SC was licensed in 2020 and is expected to be reimbursed in the Italian setting for the same indications as dara-IV. A cost-minimization model (CMM) was developed to evaluate the economic implications of using dara-SC instead of dara-IV in Italy.

Post pandemic strategic planning of food catering production and distribution networks: A regional case study

Due to the Covid19 outbreak, the food catering industry faces disruption of demand traits and great uncertainty about the future development of market segmentation. The need for a re-design of production and logistic networks faces the lack of knowledge about cost drivers, rendering the application of mathematical optimization models challenging. In this paper, a cost components analysis is carried out to quantify each cost item's impact on the full meal cost. Cost analysis aims to formalize the relationship between meal cost and parameters such as productivity, meal conservation regime, customer typology, portioning method, and customer-plant distance. The cost parameters are adjusted through empirically driven correction factors to include operational and management complexities that would otherwise be neglected. The obtained parameters feed a total cost minimization model for a productive and distributive catering network. The location-allocation model chooses the production capacity to activate in each production plant for every meal-type and achieves the customer-production plant pairing. The framework is applied in an Italian regional case study to compare the BAU scenario to two different To-Be scenarios. The As-Is scenario considers four different production facilities serving the pre-pandemic demand of 2019, while the To-Be scenarios are based upon a demand forecast enforcing a more resilient network. The analysis shows how re-designing production and distribution networks enables meeting uncertain demand while keeping FMCs under control within a regional environment.

Machine Learning Applications in Fleet Electrification: Optimizing Vehicle Maintenance and Energy Consumption

The electric vehicle (EV) market has been growing not only for passenger vehicles, where we witness high adoption of these cleaner cars, divided into Hybrid Electric Vehicles (HEVs), Plug-In Electric Vehicles (PHEVs), and Battery Electric Vehicles (BEVs), but also in buses, trucks, and vans, with an increasing conversion pressure due to regulations. In last-mile delivery, powerful optimization tools combining machine learning with operations research have become the subject of several studies, aiming to achieve efficient energy consumption in EVs by predicting drivers’ behaviors or track charts. Moreover, new strategies have been developed for something known as fleet electrification, i.e., when a carrier company aiming mainly to decrease its environmental footprint combines the operation of conventional fuel-powered vehicles with electric ones; this is not a complete switchover, but an intermediate stage. Since computational methods converged, fleet electrification attracted researchers’ interest as a techno-economical optimization question related to three main research lines with a strong potential impact on environmental electricity: energy mix-related carbon emissions. The first category of services that impacted fleet electrification before the advent of machine learning was related to condition-based maintenance. As commercial gas, electricity, heating oil, and water consumption can be budgeted across a year’s worth of monthly payments, fixing a price through the year could help these fleets include commercial formulations that account for released corporate emissions through approved carbon offsetting. In concrete numbers, our technical paper has two key goals: firstly, we investigate whether and to what extent the Vehicle Misuse Factor, as defined, and the initial state of relevant vehicle parts (tires, gearbox, motor, etc.) affect the electric energy consumption of EVs; secondly, we propose and solve the cost minimization model arising from this energy consumption prediction.

Cost-minimization and opportunity cost analysis of fully-liquid hexavalent and meningococcal vaccines in Spain

IntroductionSimplification of vaccine preparations saves time and reduces potential immunization errors. This study aimed to perform a cost-minimization analysis (CMA) and to assess the opportunity cost of fully-liquid versus non-fully liquid vaccines requiring reconstitution for the hexavalent (DTaP-IPV-HB-Hib) and MenACWY vaccines. MethodsA cost-minimization model based on the time required to prepare and administer vaccines, considering preparation errors, was developed. The number of administered hexavalent and MenACWY vaccines in one year was calculated, and the time required for the vaccination visit was obtained from a time-and-motion study. The percentage of preparation errors was obtained from the EUDRAVIGILANCE database. The vaccines unitary cost and nurse's salary were obtained from the Spanish Ministry of Health. Deterministic sensitivity analyses (scenarios and univariate) were performed. A panel multidisciplinary of experts was consulted to assess the opportunity cost associated with the use of fully-liquid vaccines. ResultsThe use of fully-liquid vaccines would save 62.92 healthcare-hours in one year per 100,000 inhabitants (41.68 and 21.23 healthcare-hours with the hexavalent and MenACWY vaccines, respectively), which translate into a expenditure reduction of € 2220.5 per 100,000 inhabitants. The deterministic analysis confirmed the robustness of these base-case results. The experts consulted concluded that improving parental health education during consultation would be the main action that could be implemented to employ the extra-time saved by healthcare professionals when fully-liquid vaccines are used. ConclusionsThe use of fully-liquid hexavalent and MenACWY vaccines instead of non-fully liquid presentations would reduce healthcare professionals' working hours that could be reinvested in improving the quality of the consultation.

Scope for pair-wise factor substitution strategies in US rural transit operations when factor prices change

Rural transit providers face unique challenges beyond those of their urban counterparts, including worse road conditions, access to trained labor, tighter budget constraints, and higher miles per rider. To date, transportation economics and policy research is scarce for this essential service in rural geographies due to data paucity. Employing the Generalized Translog Cost-minimization model, the core innovation in this paper is presenting the first illustration of the cost-minimization strategies available to transit providers when faced with the constraints of sparsely populated geographic settings. Using a rich dataset of 42 U.S. rural transportation providers across 17 years, we estimate the operational factor (fuel, labor, materials and maintenance) substitution capabilities for the typical provider. The estimated production factor input elasticities of substitution (own, cross-price, Morishima, and Shadow) differ substantially across price changes for the three input factors. Following, this study sheds new operational cost-minimization policy insights for rural public transportation operations.

Cost-minimization and opportunity cost analysis of fully-liquid hexavalent and meningococcal vaccines in Spain

IntroductionSimplification of vaccine preparations saves time and reduces potential immunization errors. This study aimed to perform a cost-minimization analysis (CMA) and to assess the opportunity cost of fully-liquid versus non-fully liquid vaccines requiring reconstitution for the hexavalent (DTaP-IPV-HB-Hib) and MenACWY vaccines. MethodsA cost-minimization model based on the time required to prepare and administer vaccines, considering preparation errors, was developed. The number of administered hexavalent and MenACWY vaccines in one year was calculated, and the time required for the vaccination visit was obtained from a time-and-motion study. The percentage of preparation errors was obtained from the EUDRAVIGILANCE database. The vaccines unitary cost and nurse's salary were obtained from the Spanish Ministry of Health. Deterministic sensitivity analyses (scenarios and univariate) were performed. A panel multidisciplinary of experts was consulted to assess the opportunity cost associated with the use of fully-liquid vaccines. ResultsThe use of fully-liquid vaccines would save 62.92 healthcare-hours in one year per 100,000 inhabitants (41.68 and 21.23 healthcare-hours with the hexavalent and MenACWY vaccines, respectively), which translate into a expenditure reduction of € 2220.5 per 100,000 inhabitants. The deterministic analysis confirmed the robustness of these base-case results. The experts consulted concluded that improving parental health education during consultation would be the main action that could be implemented to employ the extra-time saved by healthcare professionals when fully-liquid vaccines are used. ConclusionsThe use of fully-liquid hexavalent and MenACWY vaccines instead of non-fully liquid presentations would reduce healthcare professionals' working hours that could be reinvested in improving the quality of the consultation.

Minimization of multiproduct fabrication cost featuring rework, commonality, external provider, and postponement

This study presents a multiproduct fabrication cost-minimization model featuring external providers, commonality, rework, and postponement in the supply chain environment. Customers’ requirements simultaneously emphasize quality, variety, and fast response time in current markets. To satisfy customer needs, most manufacturers in various industries (e.g., clothing, household goods, automotive, etc.) plan their multiproduct fabrication by incorporating a postponement strategy, rework process, and an outsourcing option. Motivated by the viewpoints above, this study offers a decision support system to address customers’ external expectations while optimizing internal operating expenses and machine utilization. We propose a single-machine, two-stage delayed differentiation system under a rotation cycle policy. All needed common parts are made in stage one, and stage two fabricates different end products. An external provider is hired to supply partially needed common parts to shorten uptime. The defective items are inevitably produced in both stages. They are categorized and reworked to maintain the desired product quality. Finally, we derive an optimal cost-minimization rotation cycle for our model and use a numerical example to investigate the collective and individual influences of reworking, postponement, and outsourcing to external providers on the multiproduct fabrication problem. In summary, this study can offer an optimization solution for production planning in various modern industries.

COVID-19 Disruption Strategy for Redesigning Global Supply Chain Network across TPP Countries

Background: COVID-19 has disrupted and adversely affected supply chains worldwide. A global supply chain network that considers disruptions is needed. This study strategically analyzes the economic and structural effects of disruption on a global supply chain network with customs duty and the trans-pacific partnership (TPP) agreement. Methods: We present a cost minimization model which helps in understanding the difficulty of supplying materials or products to factories or customers if the supplier’s cities are facing disruption. This enables us to model and evaluate simultaneous considerations of supplier disruption, customs duty, and TPP in redesigning a global supply chain network. This network is modeled and formulated using integer programming, disruption scenarios, and a sensitivity analysis for customs duty. Results: Regarding the impact of disruptions on suppliers, two patterns emerge in the reconfigured network: direct changes due to supplier disruptions and indirect changes due to factory relocation. The sensitivity analysis for customs duty shows that the TPP has a positive impact on cost maintained, even in the presence of disruptions. Conclusions: Suppliers should be switched depending on the scale of disruption; when many distant suppliers need to be switched, the factory should be relocated to the country where these suppliers are located.

Design of Clean Steel Production with Hydrogen: Impact of Electricity System Composition

In Europe, electrification is considered a key option to obtain a cleaner production of steel at the same time as the electricity system production portfolio is expected to consist of an increasing share of varying renewable electricity (VRE) generation, mainly in the form of solar PV and wind power. We investigate cost-efficient designs of hydrogen-based steelmaking in electricity systems dominated by VRE. We develop and apply a linear cost-minimization model with an hourly time resolution, which determines cost-optimal operation and sizing of the units in hydrogen-based steelmaking including an electrolyser, direct reduction shaft, electric arc furnace, as well as storage for hydrogen and hot-briquetted iron pellets. We show that the electricity price following steelmaking leads to savings in running costs but to increased capital cost due to investments in the overcapacity of steel production units and storage units for hydrogen and hot-briquetted iron pellets. For two VRE-dominated regions, we show that the electricity price following steel production reduces the total steel production cost by 23% and 17%, respectively, as compared to continuous steel production at a constant level. We also show that the cost-optimal design of the steelmaking process is dependent upon the electricity system mix.

Maintenance cost minimization models for offshore wind farms: A systematic and critical review

Feasible and sustainable source of power is a burning question nowadays. The offshore wind farms can be a solution to power generation problem, but it is relatively more expensive. Its installation cost is more than twice of its similar size onshore counterpart. The cost that matters most is the operations and maintenance (O&M) cost. Expensive and sophisticated transfer vehicles as well as highly skilled technicians are needed to conduct O&M activities, which results in a remarkably higher O&M cost for an offshore wind farm project. Few researchers proposed some strategies that could resolve the problem nicely, although there is no universal maintenance strategy, which will fit all the conditions. Optimal maintenance strategy depends on a lot of factors such as cost of energy, level of reliability needed, weather conditions, availability of skilled technicians, availability of crew transfer vehicles, and to mention a few. Total 190 research articles related to offshore maintenance have been reviewed, and some prominent models have been discussed in detail. Some risk and reliability-based models reduced annual maintenance cost by 23%, whereas some other opportunistic maintenance strategy was able to minimize 32% of production loss and transportation cost. Compatibility and usability of different models and results are highlighted. This critical review is aimed at identifying the relevant research outcomes and comparing their critical aspects to provide a good guideline about optimal maintenance strategy to the maintenance managers.

Investment decisions in distributed renewable energy considering economic performance and life-cycle environmental impact

Using renewable energy is suggested as an environmentally superior strategy in lots of recent literature. However, the life-cycle effect of using distributed renewable energy (DRE) on the environment is still not well understood. In this paper, we adopt a perspective of life-cycle environmental impact and analytically investigate investment decisions in DRE with the consideration of both profit and environmental impact. According to the presence or absence of electricity from the utility firm, we build a cost minimization model respectively. The established models can capture uncertainty in both the supply of and demand for electricity. We make comparisons on the total environmental impact and profit between different investment choices in DRE. The result shows that an increase in the DRE generation can lead to environment improvement only under some certain conditions. We find that the intermittency of renewable energy sources and the high-emission and high-operating-cost of backup energy sources affect the investment decisions in DRE. We also investigate the impact of the utility firm on investment decisions in DRE from economic and environmental perspectives. We provide the distributed generator’s selling price range and the utility firm’s retail price range such that the incentive compatible region is nonempty.

Cost-minimization analysis of immunoglobulin treatment of primary immunodeficiency diseases in Spain

Primary immunodeficiency diseases (PID), which are comprised of over 400 genetic disorders, occur when a component of the immune system is diminished or dysfunctional. Patients with PID who require immunoglobulin (IG) replacement therapy receive intravenous IG (IVIG) or subcutaneous IG (SCIG), each of which provides equivalent efficacy. We developed a cost-minimization model to evaluate costs of IVIG versus SCIG from the Spanish National Healthcare System perspective. The base case modeled the annual cost per patient of IVIG and SCIG for the mean doses (per current expert clinical practice) over 1 year in terms of direct (drug and administration) and indirect (lost productivity for adults and parents/guardians of pediatric patients) costs. It was assumed that all IVIG infusions were administered in a day hospital, and 95% of SCIG infusions were administered at home. Drug costs were calculated from ex-factory prices obtained from local databases minus the mandatory deduction. Costs were valued on 2018 euros. The annual modeled costs were €4,266 lower for patients with PID who received SCIG (total €14,466) compared with those who received IVIG (total €18,732). The two largest contributors were differences in annual IG costs as a function of dosage (– €1,927) and hospital administration costs (– €2,688). However, SCIG incurred training costs for home administration (€695). Sensitivity analyses for two dose-rounding scenarios were consistent with the base case. Our model suggests that SCIG may be a cost-saving alternative to IVIG for patients with PID in Spain.

Optimal fleet size for a shared demand-responsive transport system with human-driven vs automated vehicles: A total cost minimization approach

Vehicle automation is expected to reduce the cost of shared demand-responsive transport (DRT) services. In this context, questions regarding the conditions under which fixed-route public transport can be replaced with shared on-demand services have emerged. The expected increase in competitiveness between fixed-route and on-demand services requires the development of frameworks that enable the analysis of transportation costs of alternative modes. In this research, we develop a total cost minimization model for demand-responsive door-to-door shared transportation services, including operator and user costs. Optimization variables are vehicle size and fleet size for operation with human-driven and automated vehicles. A hybrid approach is used in which the relevant variables are analytically and numerically modeled, using data from a large-scale agent-based simulation applied to the city of Munich. We compare the case in which all trip requests must be served with the case in which request rejections are allowed, based on waiting and travel times. Different demand levels and alternative scenarios for vehicle automation are analyzed. The results indicate that the performance of door-to-door on-demand shared systems depends on the operational scheme selected. For the DRT setup and vehicle assignment strategy studied, we find that if the system is forced to have no trip rejections, economies of scale are not present, and the high user costs hinder the system’s competitiveness even under the assumption of automated vehicles. In contrast, in a system that allows for trip rejections, economies of scale are present, and vehicle automation can especially reduce operator costs, increasing the system’s competitiveness against other transportation modes. Therefore, in our setting, the efficiency of the demand-responsive service depends on the ability to reject customers, which is against the spirit of a truly public transportation service. On scenario analysis, we show that a theoretical improvement in the performance of the real-time vehicle assignment strategy can significantly reduce total cost, with economies of scale under no-rejection operation. Future research needs to address whether the actual application of more complex vehicle assignment strategies can indeed make DRT systems more cost competitive while serving all trip requests.

A Minimal System Cost Minimization Model for Variable Renewable Energy Integration: Application to France and Comparison to Mean-Variance Analysis

The viability of Variable Renewable Energy (VRE)-investment strategies depends on the response of dispatchable producers to satisfy the net load. We lack a simple research tool with sufficient complexity to represent major phenomena associated with the response of dispatchable producers to the integration of high shares of VRE and their impact on system costs. We develop a minimization of the system cost allowing one to quantify and decompose the system value of VRE depending on an aggregate dispatchable production. Defining the variable cost of the dispatchable generation as quadratic with a coefficient depending on macroeconomic factors such as the cost of greenhouse gas emissions leads to the simplest version of the model. In the absence of curtailment, and for particular parameter values, this version is equivalent to a mean-variance problem. We apply this model to France with solar and wind capacities distributed over the administrative regions of metropolitan France. In this case, ignoring the wholesale price effect and variability has a relatively small impact on optimal investments, but leads to largely underestimating the system total cost and overestimating the system marginal cost.

PMD7 Budget Impact Analysis of Transcutaneous Afferent Patterned Stimulation Therapy for the Treatment of Essential Tremor in the United States

INTRODUCTION: Essential tremor (ET) is a chronic, progressive, and disabling neurological disease, managed with poorly tolerated, partially effective pharmacological treatments and, in some patients, costly surgical or non-reversible ablative procedures. Transcutaneous afferent patterned stimulation (TAPS), delivered by a novel personalized medical device, provides non-invasive, on-demand stimulation of the same key brain networks as the most effective surgery, deep brain stimulation, and has an extensive clinical program demonstrating its efficacy and safety in the treatment of ET. With TAPS device costs concentrated at treatment initiation, an economic analysis was conducted to assess the near-term budget impact of its introduction for the treatment of ET. A cost minimization model was developed to calculate the 3-year impact of introducing TAPS therapy for a healthcare plan cohort of 1,000,000 people. Prevalence of ET, as well as costs and incidence of surgical and non-reversible ablative procedures, were gathered from published literature. Acquisition costs and proportion of patients receiving pharmacological treatment options were sourced from Redbook and 24-month data from Truven databases. The economic impact of introducing TAPS was calculated based on an alternative scenario where 3% of patients from each treatment received TAPS therapy. Within the plan population, 2,992 patients were estimated to receive ET treatment. Introduction of TAPS therapy would have a 3-year budget impact of $62,126 (+0.25% compared with current costs; +$130,233 in the first year and approximately -$34,050 in subsequent years), or $20.56 per treated patient and $0.002 PMPM. Introduction of TAPS therapy for the treatment of ET had a modest budget impact in the near-term based on acquisition costs alone. TAPS therapy offers an additional, clinically meaningful option for the treatment of ET that is likely to be cost neutral or cost saving when pharmacological adverse event costs or surgical and procedure complication costs are considered.

Renewable energy investment study for electric power enterprise based on a time period with expected supply

ABSTRACT This paper discusses an investment problem by establishing a cost minimization model for an electric power enterprise. Two potentially investable energy sources are suggested: renewable and new conventional energy, and expected supply level in a coming period is assumed. Features of integrated power market are considered: the merit order effect, carbon emissions intensity, intermittency of renewable energy, carbon tax, loan interest and generation and investment costs. The model is transformed to one-dimensional programming, so the Golden Section Algorithm is adopted. Simulation results are demonstrated in two cases with different supply levels, and they confirm the validity of the model.

PIH10 Cost Comparison between Leuprolide 3-Month Formulation and Other Gonadotropin-Releasing Hormone Agonists As Therapy for Children with Central Precocious Puberty in China

To compare the treatment costs of three gonadotropin-releasing hormone agonists (GnRHa), leuprolide 11.25 mg 3-month (3M) depot, leuprolide 3.75 mg 1-month (1M) depot and triptorelin 3.75mg 1-month (1M) depot, as therapy for central precocious puberty (CPP) children in China. A 4-year cost-minimization model was developed from the societal perspective. Direct medical costs (drug costs, registration fees, injection fees and examination fees), direct non-medical cost (transportation and accommodation cost) and indirect costs (loss of salary for parents or other families) were analyzed. The main data sources were published literatures and physician survey. One-way sensitivity analyses were conducted to assess the uncertainty and result robustness. Compared to patients with leuprolide-1M and triptorelin-1M, those with leuprolide-3M was associated with 29.6 fewer injections and related hospital visits over 4 years per patient. Patients with leuprolide-3M saved a total cost of ¥17103.91 compared to patients with leuprolide-1M, including the savings of ¥380.09 (2.2%) in direct medical cost, ¥10684.96 (62.5%) in direct non-medical cost, and ¥6038.87 (35.3%) in indirect cost. Additionally, patients with leuprolide-3M saved a total cost of ¥14533.13 compared to patients with triptorelin-1M, including an incremental direct medical cost of ¥2190.69, a savings of ¥10684.96 in direct non-medical cost, and a savings of ¥6038.87 in indirect cost. The key driver of sensitivity analyses is the unit cost of leuprolide-3M. Using leuprolide-3M is a cost-saving strategy compared to leuprolide-1M and triptorelin-1M from the societal perspective in China. Besides the difference in direct treatment costs, less injection frequency of leuprolide-3M also reduces injection-related direct non-medical and indirect costs.

Grid-wide assessment of varying re-regulation storage capacity for hydropeaking mitigation

Hydropeaking affects downstream ecosystems and water uses. We assessed the effect of small re-regulation reservoirs (RRR) located downstream of hydropower plants to mitigate the impact of hydropeaking operations, in terms of the tradeoffs between flashiness of flows and power system cost. The study is performed on a hypothetical power system composed by one reservoir hydropower plant, one coal-fired plant, one diesel-fired plant, and one wind power plant. Hourly operations within a weekly horizon by each plant are prescribed by a system-wide cost-minimization model. Operations are constrained by minimum flows (MIF) and maximum ramping rates (MRR). The model was run for selected weeks, representative of the four seasons and three water year types. Results show that MIF and MRR constraints can achieve improvements in the flashiness of flows, from Richard-Baker index above 0.8 down to less than 0.1. However, without a RRR, these constraints can cause a power system cost increase of up to 70% with respect to the unconstrained case. The strongest effect on power system costs is observed under the dry hydrologic scenario. The cost increase is also significant in the summer weeks of the two normal scenarios. A half-hour capacity RRR keeps the cost increase below 8% and further reduces the flashiness to values below 0.1, on average for the dry scenarios. RRR storage capacities of one and 2 h can further reduce the cost increase below 5%, with flashiness as low as 0.01. No significant improvement is observed beyond this RRR size. In synthesis, this study shows that small re-regulation reservoirs, with capacities up to 2-h detention time, are a promising alternative for hydropeaking control at low power system cost.