Economic Optimization Research Articles

Economic optimization scheduling of microgrid group based on chaotic mapping optimization BOA algorithm

Due to the intermittency and volatility of distributed power sources, the microgrid system has poor stability and high operation cost. Therefore, the study proposes an economic optimization scheduling strategy based on the chaotic mapping butterfly optimization algorithm and the mathematical model of microgrid group system. The study creates simulation trials of function poles and microgrid group operation to confirm the strategy’s efficacy. According to the experimental findings, the multimodal function of the enhanced butterfly optimization method had a variance of 0.0000E + 00, and the function’s optimal value was less than 10–30, and the calculation time is 4.5s. The variance on the fixed dimensional function was 0.0000E + 00 and the optimal value of the function was 10 − 3.5,and the calculation time is 4.7s. The algorithmic curve all digging depth was maximum and convergence speed was fastest. The microgrid group system had the lowest economic cost of 4029.32 yuan in the grid-connected mode and 3343.39 yuan in the off-grid mode. The study proves that the energy coordination and economic management of this strategy are greatly optimized, which can effectively protect the energy storage equipment and guarantee the smooth power consumption of the system. This provides an innovative theoretical basis for optimization scheduling of microgrid group.

Economic Analysis, Yield Optimization, and Competition Dynamics of Groundnut/Cereal Fodder Intercropping Systems in Pakistan's Semi Arid Tropics

This research focuses on the intercropping management options including aspects of yield performance, nitrogen contribution to groundnut and economical considerations through the usage of intercrop Maize, Sorghum and Pearl Millet under varying cuttings treatments. Intercropping is effective in increasing land productivity and efficiency in nutrient use and provides economic returns yet the best combinations have not been well explored. Randomised complete block design was used to assess the growth characteristics of plant height, modulation and nitrogen in sole cropping and intercropping treatments in which they make cuts. For sole crop, both, maize and pearl millet produced the highest green fodder yields of 13.40 t ha⁻¹ and 19.10 t ha⁻¹, respectively, and intercropping reduced the productivity for both crops but it was statistically significant, yield recorded in Maize (one cut) groundnut = 3.10 t ha⁻¹. Both nodulation and nitrogen content were maximum in sole groundnut, but they were lower when groundnut was grown in association with other crops. Among all competitive indices, the LER was the highest on maize (LER=1.72), pearl millet and sorghum indicated that intercropping enhances land use efficiency. This was facilitated by the Monetary Advantage Index (MAI) that provided much support to maize-groundnut intercrop, which was easily identified as the most appropriate option for inter-crop revenue generation with an MAI of Rs. 17,800. These results provide evidence for the suitability of maize as the best intercrop for the enhancement of productivity and profitability in groundnut based intercropping systems. This study adds valuable input to sustainable agriculture, particularly in that it expresses the yields and profits from distinct intercrop associations as numeral digits deemed useful by both the scientific and agricultural communities.

Feasibility Assessment of Hybrid Renewable Energy Based EV Charging Station in Libya

This study presents an assessment of the feasibility of implementing a hybrid renewable energy-based electric vehicle (EV) charging station at a residential building in Tripoli, Libya. Utilizing the advanced capabilities of HOMER Grid software, the research evaluates multiple scenarios involving combinations of solar and wind energy sources integrated with energy storage and the utility grid. This analysis provides a novel approach to enhancing urban energy systems with renewable technologies in a region traditionally reliant on fossil fuels. Key contributions of this study include the demonstration of an innovative integration strategy that combines solar and wind power with battery storage to ensure a reliable and efficient energy supply for EV charging. Furthermore, the study addresses the practical implications for local energy policy, suggesting that such hybrid systems can significantly enhance energy security and support sustainable urban development. The authors studied five scenarios using HOMER. The results reveals that the annual total costs and payback periods are as follows: for Scenario 1 (wind/utility grid), the expenditure totals US$1,554,416 and payback period of 4.8/5.8 years; for Scenario 2 (solar/wind/Utility grid), the amount is US$1,554,506 and payback period of 4.8/5.8 years; and for Scenario 3(solar/wind/storage/utility grid), it escalates slightly to US$1,554,731, all predicated on the utility grid tariffs and payback period of 4.8/5.8 years. Furthermore, in Scenario 4 (solar/utility grid), the annual total cost is significantly reduced to US$30,589 and a payback period of 8.1/14.3 years, while Scenario 5 (solar/storage/utility grid) incurs an even lower expenditure of US$28,572, again based on the utility grid tariffs and a payback period of 14.0 years. The findings contribute valuable insights into the scalability and adaptability of renewable energy solutions, providing a robust framework for policymakers and planners considering similar implementations in other regions. Overall, the research underscores the potential of integrated renewable energy systems to transform urban energy infrastructures, promoting a sustainable and resilient energy future. The HOMER Grid analysis shows that configurations with energy storage are more cost-effective in the long run, even though they require higher initial costs. It also offers important insights into the economic viability and optimization of hybrid renewable energy systems for an EV charging station in Tripoli, Libya. These results highlight the significance of making calculated investments in renewable energy infrastructure and supporting policies for the development of sustainable energy.

Capturing the effects of flower strips on natural pest control in agronomic land use models

ContextGiven policy objectives for pesticide reduction, functional biodiversity is increasingly important for agricultural production. However, economic land use optimisation models rarely account for the interplay between agricultural production and functional biodiversity, like natural pest control (NPC). ObjectiveWe present and discuss an approach to consider feedback effects between NPC and agricultural production in a geodata-based farm economic land use model. MethodsThe geodata-based land use model PALUD was extended to incorporate interactions between NPC and crop yields. This included linking a generic NPC model, based on semi-natural habitats, with an econometric approach to estimate yield gaps as a function of NPC potential. As a case study, the model was then applied to the German state Brandenburg, using permanent flower strips as example to promote NPC. Here, we analysed the impacts of enhancing NPC potential on food production and gross margins from arable land use. Results and conclusionsOur analysis revealed that a higher level of NPC through flower strips improved gross margins. by up to 6.4 % and crop production by up to 1.2 % within a pesticide-free environment in Brandenburg. Despite inherent limitations and uncertainties of the approach, our study provides a pivotal advancement in integrating NPC into economic land use models. Future refinements incorporating more detailed knowledge on context-specific interactions between crops, pests and predators will improve model robustness. Our approach and case study results provide valuable insights for policy-making on tailored sustainable landscape development and serve as a foundation for future modelling efforts. SignificanceTo our knowledge the interaction between NPC and crop yields has not yet been integrated into any geospatially based economic land use model before. Incorparating these interactions is vital for guiding policies towards sustainable agricultural systems. In this respect it is important to develop and discuss further methodological approaches.

Low-carbon economic optimization strategy for industrial loads in parks considering source-load-price multivariate uncertainty

A low-carbon economic optimization method is proposed for industrial loads in parks considering multivariate uncertainty. Model of dynamic load node carbon intensity is proposed considering the uncertainty of clean energy and dynamic conventional units carbon intensity based on system currents. The robustness is improved based on multi-interval uncertainty set. The gap is filled by hybrid copula model with Generalized Autoregressive Conditional Heteroskedasticity (GARCH) prices in the uncertainty model. The GARCH is used to built the marginal distribution function of prices, and a hybrid copula model is proposed to obtain the joint probability density function based on the weights calculated by Euclidean distance. The LNCI probability distributions of the regulation potential of loads are proposed with the virtual energy storage and the virtual power model to improve the descriptive ability of uncertainty based on the expansion and contraction functions. Finally, the typical scenarios are extracted based on Monte Carlo and Wasserstein measures. The Column sum Constraint Generation algorithm and strong duality theory are used to get the robust-stochastic optimization. The method proposed in the paper has a positive effect on enterprises to rationalize their production schedules, reduce electricity and carbon emissions costs and increase the revenue from participating in grid regulation.

Study on two‐stage optimal scheduling of DC distribution networks considering flexible load response

AbstractDue to the aim of developing sustainable energy systems, promoting the large‐scale accommodation of distributed renewable energy sources (DRESs) and flexible loads in DC distribution networks (DCDNs) is significant. The uncertainty of DRESs and the insufficient use of flexible loads pose a considerable challenge to the economical and safe operation of DCDNs. To address the challenge, this paper puts forward a two‐stage optimal scheduling model for the DCDNs considering flexible load response. The proposed model realises joint economic optimisation and reactive power optimisation, which is solved by the hybrid NSGAII‐MOPSO algorithm and the CPLEX. The performance of the proposed model in the modified Institute of Electrical and Electronics Engineers 33‐node system with the DCDNs is validated under different scenarios. The hybrid NSGAII‐MOPSO performs better in obtaining the Pareto front than the NSGA‐II and MOPSO individually. Compared to the traditional scheduling model, the proposed model can realise the power coordination of the flexible loads and energy storage systems to reduce the negative impact of uncertainty of DRESs while decreasing operating costs and carbon emissions by 3.94% and 36.4%. In addition, the proposed model can alleviate the network losses and ensure the node voltage for the DCDNs. Hence, the efficiency of the proposed model has been confirmed.

Quality Certification and Business Performance: The Portuguese Large Firms’ Case

Objective: Observe the existence of a relationship between quality certification, financial performance and bankruptcy prediction, as well as the supposed superiority of the quality certified Portuguese large companies. Theoretical Reference: In the continuous pursuit for quality, as well as its certification, the International Standard Organization (ISO), suggests, from a theoretical perspective, a possible relationship of the last one with the going concern, contributing to the companies’ economic and financial sustainability. Method: We selected Portuguese large companies (according to recommendation 2003/361/EC) with Economic Activity Codes (NACE) D and G, certified with ISO 9000 or 9001, totalling 91 companies, along with computed average company from each of these sectors. We used univariate and multivariate techniques (MDA), models of business failure prediction, considered in previous studies as the most effective for the Iberian economy (Peres and Antão, 2018; Peres and Antão, 2019), aiming to assess the companies’ performance, as well as the supposed superiority of those quality certified companies. Results and Discussion: In neither of the analysis, univariate and multivariate, was observed a superior performance of the certified companies compared to others, indicating that quality certification is not effectively related to the companies’ economic and financial performance optimization. Implications of the Research: Uncover the influence of quality certification on the economic-financial position of companies, allowing for deeper investigation into bankruptcy, sustainability and value creation. Originality/Value: The specificities of the sectors and business size, crises and the increasing of business closures make it vital to identify what will influence performance and sustainability, as no studies have been identified on this topic, focusing on Portuguese Large companies, certified via ISO 9000 or 9001.

Enhancing commercial building resiliency through microgrids with distributed energy sources and battery energy storage systems

Resilience analysis is gaining focus, but no extensive research exists for commercial buildings. This research presents the results of a novel analysis of the resiliency in commercial buildings by examining the relationship between electric microgrids, Distributed Energy Resources (DERs), and Battery Energy Storage Systems (BESS). As energy systems face increasing challenges, including extreme weather events and grid vulnerabilities, integrating microgrids, DERs, and BESS has emerged as a promising solution to strengthen the resilience of commercial buildings. Microgrids can harness renewable energy sources and reduce environmental impacts when integrated with DERs. Most literature studies focus on residential or commercial buildings with peak-valley tariffs and simplified electrical market models. In contrast, this study focuses on BESS’ pivotal role in DER output and ensuring uninterrupted power during grid disruptions and presents an innovative approach to analyzing resilience in commercial building microgrids and an economic optimization of commercial building microgrids with Time of Use tariffs utilizing DERS and BESS. The analysis includes the technical aspects of BESS integration and control strategies that optimize their operation. It also studies the economic and environmental benefits of microgrids, DERs, and BESS, focusing on cost savings, greenhouse gas emission reductions, and grid support services.

Two-Stage Optimal Scheduling Strategy of Microgrid Distribution Network Considering Multi-Source Agricultural Load Aggregation

With the proposed “double carbon” target for the power system, large-scale distributed energy access poses a major challenge to the way the distribution grid operates. The rural distribution network (DN) will transform into a new local power system primarily driven by distributed renewable energy sources and energy storage, while also being interconnected with the larger power grid. The development of the rural DN will heavily rely on the construction and efficient planning of the microgrid (MG) within the agricultural park. Based on this, this paper proposes a two-stage optimal scheduling model and solution strategy for the microgrid distribution network with multi-source agricultural load aggregation. First, in the first stage, considering the flexible agricultural load and the market time-of-use electricity price, the economic optimization is realized by optimizing the operation of the schedulable resources of the park. The linear model in this stage is solved by the Lingo algorithm with fast solution speed and high accuracy. In the second stage, the power interaction between the MG and the DN in the agricultural park is considered. By optimising the output of the reactive power compensation device, the operating state of the DN is optimised. At this stage, the non-linear and convex optimization problems are solved by the particle swarm optimization algorithm. Finally, the example analysis shows that the proposed method can effectively improve the feasible region of safe operation of the distribution network in rural areas and improve the operating income of a multi-source agricultural load aggregation agricultural park.

An Introduction to Lagrange Multipliers: Theory and Applications in Economics

The purpose of this paper is to explore the basic applications of the Lagrange multiplier method in economics and to help beginners build their understanding of this mathematical tool. Tesla Inc. is used as a case study to examine how it maximizes profits by optimizing pricing and marketing expenses under given market conditions and constraints. The context of the study includes the importance of maintaining Tesla’s leadership position as the world’s leading electric car manufacturer in a competitive market. In this paper, the Lagrange multiplier method is used to incorporate specific market share and marketing expense constraints into the profit function and to find the extreme values by constructing the Lagrange function and solving for the derivatives. However, the results of the study show that the solutions obtained are extreme minima rather than the expected maxima. This result highlights the possible limitations of the Lagrange multiplier method in economic optimization problems. Nonetheless, this paper provides valuable lessons for understanding and applying the Lagrange multiplier method and points the way for further research on the application of optimization methods in economic decision making.

Real-Time Control of Thermal Synchronous Generators for Cyber-Physical Security: Addressing Oscillations with ANFIS

This paper introduces a novel real-time ANFIS controller, specifically designed for thermal synchronous generators, to mitigate the risks associated with cyber-physical attacks on power systems. The controller integrates the dynamic model of the turbine’s thermomechanical components, such as the boiler and heat transfer processes, within the synchronous generator. In contrast to previous studies, this model is designed for practical implementation and addresses often-overlooked areas, including the interaction between electrical and thermomechanical components, real-time control responses to cyber-physical attacks, and the incorporation of economic considerations alongside technical performance. This study takes a comprehensive approach to filling these gaps. Under normal conditions, the proposed controller significantly improves the management of industrial turbines and governors, optimizing existing control systems with a particular focus on minimizing generation costs. However, its primary innovation is its ability to respond dynamically to local and inter-area power oscillations triggered by cyber-physical attacks. In such events, the controller efficiently manages the turbines and governors of synchronous generators, ensuring the stability and reliability of power systems. This approach introduces a cutting-edge thermo-electrical control strategy that integrates both electrical and thermomechanical dynamics of thermal synchronous generators. The novelty lies in its real-time control capability to counteract the effects of cyber-physical attacks, as well as its simultaneous consideration of economic optimization and technical performance for power system stability. Unlike traditional methods, this work offers an adaptive control system using ANFIS (Adaptive NeuroFuzzy Inference System), ensuring robust performance under dynamic conditions, including interarea oscillations and voltage deviations. To validate its effectiveness, the controller undergoes extensive simulation testing in MATLAB/Simulink, with performance comparisons against previous state-of-the-art methods. Benchmarking is also conducted using IEEE standard test systems, including the IEEE 9-bus and IEEE 39-bus networks, to highlight its superiority in protecting power systems.

Conceptual Design and Economic Optimization of Different Valorization Routes for Orange Peel Waste: The Application of the Biorefinery Concept for an Integral Use of Raw Material

Biorefineries are novel biotechnological routes designed to generate sustainable processes from renewable raw materials. The valorization of orange peel waste (OPW) provides high-value products based on their composition. The economic optimization of biorefineries through conceptual design and generation of superstructures based on the analysis of processing units is a topic of great interest. This work aimed to obtain the most profitable biorefinery through economic optimization strategies based on high-value-added products from OPW. Two stages were considered: The first stage consisted of the conceptual design of multiple OPW processing units (production of essential oil, mucic acid, phenolic compounds, biogas, among others). An OPW flow rate of 140 kg/h was selected as the base case. From the stand-alone units, a biorefinery superstructure (second stage) was designed. Finally, the units with the best mass and energy results were selected in order to maximize the net present value (NPV) and obtain an optimal biorefinery configuration. The results evidenced that the production of essential oil and biogas presented the best yields (2.61 mL and 0.028 m3 per kg OPW, respectively). This biorefinery configuration obtained an NPV of −7.7 mUSD from the base case. Through the evaluation of the different superstructure configurations, the combined production of essential oil, biogas, and mucic acid and a scale-up of over 22 times the base case generated the minimum processing scale. Under a Colombian context, the implementation of the biorefineries analyzed are promising since the minimum processing scale contemplated only 8.8% of the OPW production. Efforts to increase yields and decrease capital and operating expenses while keeping environmental impacts low should be pursued.

The economic optimization of lactation and fertility in dairy cows

The economic optimization of lactation and fertility in dairy cows

Study on the Economic Operation of a 1000 MWe Coal-Fired Power Plant with CO2 Capture

The flexible operation of carbon capture units is crucial for the economic performance of coal-fired power plants equipped with CO2 capture systems. This paper aims to investigate the impact of electricity, CO2, and fuel prices on the economic operation of such plants. A novel economic optimization model is proposed, integrating a static model of the carbon capture system with a particle swarm optimization algorithm. A new concept, the CO2 boundary price, is introduced as a key metric for determining the operating conditions of CO2 capture units. The CO2 boundary price rises when the power load decreases due to the decline in power generation efficiency, and it also increases with rising fuel prices, as the cost of steam for CO2 capture increases. Additionally, when the objective is to meet power load demand, CO2 prices have a great influence on the operation of CO2 capture units, assuming fixed coal and electricity prices. However, when the primary goal is to maximize plant profitability, the system’s operational conditions are strongly influenced by the relative prices of electricity and CO2. The proposed optimization model and the uncovered price-effect mechanisms provide valuable insights into the economic operation of carbon capture power plants.

Efficient utilization of enriched oxygen gas in residential PEMFC-CHP system with hydrogen energy storage

The oxygen byproduct generated from water electrolysis can be utilized on-site in residential combined heat and power (CHP) systems to enhance economic efficiency. This study explores solutions for optimizing the use of enriched oxygen gas (EOG) and determining the ideal oxygen fraction to maximize economic viability. A novel EOG supply system is designed to regulate oxygen fraction, oxygen excess ratio (OER), and humidity. A dynamic model of a PEMFC integrated with the EOG supply system is developed using MATLAB/Simulink® software and partially validated. The dual effects of EOG on system efficiency and remaining useful lifetime (RUL) are analyzed using a comprehensive economic optimization algorithm, leading to the identification of optimal oxygen fractions for various hydrogen production modes. Additionally, a feedforward static decoupling controller is designed to independently control the OER and oxygen fraction. The results indicate that, under rated conditions (10 kW), system power increased by 15 %, along with a 10 % improvement in system efficiency, from 48 % to 58 %. In conclusion, the efficient use of enriched oxygen gas demonstrates significant economic feasibility and practical viability, making it highly suitable for distributed power generation applications.

Economic and technical optimization of a tri-generation setup integrating a partial evaporation Rankine cycle with an ejector-based refrigeration system using different solar collectors

Three collector types, namely parabolic trough solar collector (PTSC), linear Fresnel collector (LFC), and dish collector, are employed to drive a tri-generation configuration composed of a partial evaporation Rankine cycle (PERC), a hot water production unit (HWPU), and a cascade ejector-based compression refrigeration system (ECRS) for electricity, cooling, and heating production. The ECRS is integrated with the topping PERC through an absorption refrigeration system (ARS). Moreover, the collector is indirectly connected to the system by a storage tank to increase the operating hours of the system. The performance of the system is evaluated by thermodynamic and economic analysis. The three-objective optimization result is a testament to the fact that utilizing PTSC brings about the best performance of the system. The system exergy efficiency (ηex) in the case of PTSC is 8.1 % and 24.9 % higher than in the case of LFC and dish collector, respectively. The economic performance of the system in the case of PTSC is superior to that of the dish collector. Furthermore, the PTSC case results in a relatively similar economic performance to the LFC case. The system produces power, cooling, and heating at rates of 200.8 kW, 564.9 kW, and 795.7 kW in the optimum case of utilizing PTSC, respectively. Moreover, ηex, total cost rate (C˙tot), and specific cost of tri-generation (ctri) are obtained as 11.48 %, 204.7 $h−1, and 44.91 $GJ−1, correspondingly. The results indicate that ηex of the proposed layout in the case of PTSC is superior to a comparable tri-generation configuration introduced in the field by 2.78 % points.

The Profound Nature of Derivatives and Integration: A Comprehensive Examination

This article delves into the fundamental concepts of derivatives and integration, two core principles of calculus that govern a wide range of mathematical and real-world applications. Derivatives, which measure the rate of change of a function, and integration, which calculates accumulation and areas under curves, are essential tools in fields such as physics, economics, engineering, and finance. The article offers a detailed exploration of their mathematical definitions, key properties—including linearity, the product and chain rules, and the Fundamental Theorem of Calculus—and the diverse techniques used in integration. The practical applications of these concepts are also examined, with special emphasis on their role in modeling dynamic systems, optimizing processes, and solving real-world problems such as motion analysis, financial modeling, and economic optimization. Through in-depth discussion and examples, this comprehensive article bridges the theoretical underpinnings of derivatives and integration with their vast and critical uses in various scientific and economic disciplines.

A practical approach to promoting sustainable development in the construction industry through the use of the LOTUS-Vietnamese green-building assessment tool

In the context of global climate change mitigation, building design optimization is crucial for effective and efficient resource management throughout a project’s life cycle. This study addresses the challenge of assessing green building levels using a Vietnamese perspective. A survey of over 220 participants, including investors, consultants, contractors, and other stakeholders, was conducted to identify factors influencing green building assessments. Data analysis, employing SPSS software, explored 57 factors encompassing life-cycle economic optimization, energy and water conservation, material selection, project management, and strategic market benefits. The findings highlight effective energy management as a key determinant shaping sustainable building approaches and assessments. These results offer valuable insights for life cycle cost assessments and environmental impact evaluations during project implementation. Furthermore, the study emphasizes the importance of project developers prioritizing factors that influence the achievement of green building goals based on LOTUS green building rating standards in Vietnam. The predicted results demonstrate that governments should enforce legislation and establish clear green construction regulations to promote environmentally friendly growth, and that construction companies should use environmentally friendly materials and practices in their projects. This research contributes to the knowledge base for scholars, designers, and sustainability experts by systematically identifying factors that influence green building assessments under LOTUS standards.

Rigorous design and economic optimization of reactive distillation column considering real liquid hold-up and hydraulic conditions of industrial device

The liquid hold-up in a reactive distillation (RD) column not only has a significant impact on the extent of reactions, but also affects the pressure drop and hydraulic conditions in the column. Therefore, the liquid hold-up would be a critical design factor for RD columns. However, the existing design methods for RD columns typically neglect the influence of considerable amount of liquid hold-up in downcomers owing to the difficulties of solving a large-scale nonlinear model system by considering downcomer hydraulics, resulting in significant deviations from actual situation and even operation infeasibility of the designed column. In this paper, a pseudo-transient (PT) RD model based on equilibrium model considering tray hydraulics was established for rigorous simulation and optimization of RD plate columns considering the liquid hold-up both in downcomers and column trays, and a steady-state optimization algorithm assisted by the PT model was adopted to robustly solve the optimization problem. The optimization results of either ethylene glycol RD or methyl acetate RD demonstrated that assuming all the liquid hold-up of a stage belonged to the tray will cause significant deviations in the column diameter, weir height, and the number of stages, which leads to not meeting the separation requirements and even operation hydraulic infeasibility. The rigorous model proposed in this study which considers the liquid hold-up both on trays and in downcomers as well as hydraulic constraints can be applied to systematically design industrial RD plate columns to simultaneously obtain optimal operating variables and equipment structure variables.

Economic optimization of sustainable soil management: a Dutch case study

Soil quality is pivotal for crop productivity and the environmental quality of agricultural ecosystems. Achieving sufficient yearly income and long-term farm continuity are key goals for farmers, making sustainable soil management an economic challenge. Existing bio-economic models often inadequately address soil quality. In this study, we apply the novel FARManalytics model, which integrates chemical, physical, and biological indicators of soil quality indicator, quantitative rules on how these indicators respond to farmers’ production management over time, and an economic calculation framework that accurately calculates the contribution of production management decisions towards farm income. This is the first study applying this model on existing arable farms. FARManalytics optimizes crop rotation design, cover crops, manure and fertilizer application and crop residue management. Nine Dutch arable farms were analyzed with a high variation in farm size, soil type, and cultivated crops. First, we assessed farm differences in soil quality and farm economics. Second, we optimized production management to maximize farm income while meeting soil quality targets using farm-specific scenarios. Third, we explored the impact of recent policy measures to preserve water quality and to increase the contribution of local protein production. The results show that the case farms already perform well regarding soil quality, with 75% of the soil quality indicators above critical levels. The main soil quality bottlenecks are subsoil compaction and soil organic matter input. We show that even in front-runner farms, bio-economic modeling with FARManalytics substantially improves economic performance while increasing soil quality. We found that farm income could be increased by up to €704 ha−1 year−1 while meeting soil quality targets. Additionally, we show that to anticipate on stricter water quality regulation and market shift for protein crops, FARManalytics is able to provide alternative production management strategies that ensure the highest farm income while preserving soil quality for a set of heterogenous farms.