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Traditional methods for assessing the resource adequacy (RA) of a power system are becoming obsolete due to emerging trends such as the increasing deployment of variable renewable energy and storage. Consequently, analysts are recommending that RA be assessed using a Monte Carlo simulation approach that models chronological power system operations over many instances of possible operating conditions. However, this approach is necessarily more complex and computationally demanding, which is an obstacle to real-world implementation. In this study, we investigate which operational details of power systems are important to capture in order to accurately evaluate a system's RA, versus details that add complexity but do not meaningfully affect RA results. To do so, we develop a probabilistic RA assessment framework by adapting an existing production cost model and apply it to a case study based on the IEEE Reliability Test System. Our results indicate that multi-year data, storage dispatch, and transmission limits are key details to incorporate. Accurate RA results can be obtained using non-economic dispatch strategies as long as they are coordinated with detailed operational strategies. We also demonstrate how popular expectation-based RA metrics can mask important differences in the characteristics of loss of load events.

Capacity calculations are essential for the long-term planning of railway infrastructure. Many of the methods currently used in practice calculate characteristic capacity values separately for the single elements (mainly lines and nodes) of a railway network. Approaches that consider the entire network to account for interactions between the elements often rely on many assumptions, which renders a direct practical application difficult. This paper therefore introduces a linear optimization model that comprises railway-specific constraints such as minimum headway times, line capacities, and route conflicts. Under the consideration of these constraints, the developed model permits the calculation of a network-wide capacity. The model is validated on a sample network that is based on a real network of the German railway infrastructure. [ABSTRACT FROM AUTHOR]

Cities stand at the focal point of vulnerability to heat waves (HWs) as they threaten urban livability and sustainability. National, regional, and local heat-health action plans (HHAPs) are vital for combating HWs and are increasingly crucial as adaptation measures to extreme heat. The present article highlights the most recent development on the working mechanism of HHAPs, its contemporary challenges, barriers to it and a range of operational heat management and planning strategies. It introduces the concept of ‘smartness’ to the existing mechanism of HHAPs which holds a significant potential to be intelligent, explicit and dynamic to address the growing and multifaceted impacts of extreme heat. It emphasizes urgent priorities including long-term heat planning, multisectoral heat-early warning systems, building urban heat resilience and recommends the application of eight core elements endorsed by the World Health Organization (WHO) for effective implementation of HHAPs. Collaboration among meteorological, epidemiological, public health, and urban planning experts is essential for addressing the multidimensional challenges of extreme heat. [ABSTRACT FROM AUTHOR]

Food systems are linked to multiple critical sustainability issues such as climate change, environmental degradation, and growing socioeconomic inequalities, and there is a clear need for transformative changes in how food systems are imagined and enacted. For transformations to occur, local governments and stakeholders must be able to consider achievable and desirable futures that involve radically different reconfigurations of space and land use. Based in Revelstoke, Canada, this study uses interactive visualization methods to engage local government and food systems stakeholders in an exploration of three future food systems scenarios that center on changes in food supply, food affordability, and food governance. An interactive visualization tool was developed using the Unity3D game engine, which visualizes how transformations of an underutilized railway site in Revelstoke may appear in 2100. The visualizations were presented to the study participants (n = 10) through an online, Zoom-based workshop, where 'walkthroughs' of the scenarios were performed by the researchers and the participants subsequently provided feedback. The results of this study indicate that visualization tools can elicit emotional responses, convey human relationships with food and nature, communicate power dynamics, and incorporate social justice considerations. The results also show that the visualization's representation of local infrastructure and services, the completeness of a virtual environment, and the plausibility of a depicted future affect the user assessment of the visualized scenarios. [ABSTRACT FROM AUTHOR]

Motivation: Being able to anticipate (foresight) and thus identify development pathways and make long‐term plans is crucial for the transformation of Africa. However, long‐term planning was abandoned as many African countries went into crisis, being mostly forced to adopt structural adjustment programmes in the 1980s. Although long‐term planning began to make a comeback in the 1990s, the resulting visions have tended to remain that— visions—not fully reflected in policy implementation. Purpose: The article explores the many cycles of foresight in Africa to gain insight into how foresight can become an opportunity to generate new development options and strategies for Africa. Various examples of foresight in Africa are examined to tease out the imperatives for African policy‐makers to embed foresight into development management. Approach and Methods: We review foresight in Africa, starting by mapping foresight exercises in the continent since independence. We identify three categories of foresight exercises: development partner‐led, government‐led, and civil society‐led. Given the involvement of the authors in some of the exercises, assessments are largely derived from personal communications, recollections, and reflections. Findings: Four insights emerge. First, foresight exercises have had little impact on leaders and decision‐makers, in large part because they have not been intimately engaged in the exercises. Two, foresight narratives tend to be challenging, raising difficult issues that may require substantial and difficult reforms. Faced with everyday challenges of government, leaders have usually chosen to ignore and disbelieve foresight exercises. Three, foresight analysts have not been sufficiently empathetic to the highly constrained systems of public governance and the ministers and civil servants that operate them. Four, futures initiatives can present the factors that may shape the future as overwhelming; and thereby discounting and undervaluing individual and collective agency. Policy implications: Exploring the future is not new in Africa. In traditional African societies, the need to explore the future has been recognized, as captured in proverbs and mythologies. The challenge facing African countries today is how to domesticate and democratize "modern" foresight so it becomes a way of life for decision‐makers and institutions. [ABSTRACT FROM AUTHOR]

Around 60% of households in Texas currently rely on electricity for space heating. As decarbonization efforts increase, non‐electrified households could adopt electric heat pumps, significantly increasing peak (highest) electricity demand in winter. Simultaneously, anthropogenic climate change is expected to increase temperatures, the potential for summer heat waves, and associated electricity demand for cooling. Uncertainty regarding the timing and magnitude of these concurrent changes raises questions about how they will jointly affect the seasonality of peak demand, firm capacity requirements, and grid reliability. This study investigates the net effects of residential space heating electrification and climate change on long‐term demand patterns and load shedding potential, using climate change projections, a predictive load model, and a direct current optimal power flow (DCOPF) model of the Texas grid. Results show that full electrification of residential space heating by replacing existing fossil fuel use with higher efficiency heat pumps could significantly improve reliability under hotter futures. Less efficient heat pumps may result in more severe winter peaking events and increased reliability risks. As heating electrification intensifies, system planners will need to balance the potential for greater resource adequacy risk caused by shifts in seasonal peaking behavior alongside the benefits (improved efficiency and reductions in emissions). Plain Language Summary: Electric heat pump adoption could help abate the impacts of climate change on overall power system reliability by reducing summer cooling demand in a warmer world because heat pumps are a more efficient alternative to standard air conditioning. It would also carry greenhouse gas emissions benefits in a decarbonized power grid. Yet widespread adoption of heat pumps (especially low‐efficiency heat pumps) could cause more extreme winter peaking events. During these extreme cold events, higher peak demand could result in an increased probability of outages. Higher efficiency heat pumps would help avoid these winter reliability impacts, but these more efficient heat pumps are also currently more expensive. From a grid planning perspective, planners need to account for a range of future peak demand dynamics across different heat pump adoption scenarios and climate futures. Key Points: Widespread electric heat pump adoption and climate change will increase uncertainty in seasonal peaking patterns and grid reliabilityFuture peaking behavior depends on the frequency and severity of extreme heat and cold events and the type of heat pumps widely adoptedShifts toward winter peaking could carry large resource adequacy risks, depending on pump efficiency and climate scenario [ABSTRACT FROM AUTHOR]

Agricultural policies play a critical role in determining the availability and stability of food supplies for individuals and communities. This study underscores the importance of incorporating social, economic, environmental, and political dimensions of food security when developing agricultural policy reforms. The study has two main objectives: (1) to disentangle the complexity surrounding food security by mapping policy reform decisions onto a suggested framework, and (2) to provide an empirical basis for analyzing food security using frame package analysis. To achieve these objectives, this study conducted an inductive frame analysis of agricultural policy reforms, using the theoretical framework of the "fractured consensus" regarding the CAP (Common Agricultural Policy). The case of Israel was chosen as an empirical example for the frame package analysis. The extended suggested theoretical framework can contribute to enhancing the research literature on the nexus between agricultural policy reforms and food security from both theoretical and empirical perspectives. Additionally, the proposed framework and its application can serve as a benchmark for evaluating agricultural policy reforms in the context of food security and developing practical strategies in the agri-food sector, considering the involvement of multiple players and interests. [ABSTRACT FROM AUTHOR]

Commercial electric vehicles (EVs) have increasingly gained interest from urban freight companies in the past decade due to the introduction of economic and policy drivers. Although these factors promote urban freight electrification, some barriers hinder the transition to fully electric fleets, such as the significant monetary investment required to replace the current internal combustion engine vehicles (ICEV) and the lack of readily available electric freight vehicles. Due to these barriers, for the foreseeable future, urban freight companies will operate mixed fleets with a combination of EVs and ICEVs to balance their cost/benefit trade-offs. This intermediate operational stage will allow companies to adjust their operations, test EVs, and decide if a fully electric fleet is the best choice. This paper focuses on urban last-mile deliveries in the USA and proposes a long-term planning model to explore the effects of external factors (i.e., fuel costs) on planning decisions (i.e., EV share) for a mixed fleet. In the context of this paper long-term planning is the planning for the infrastructure needed for the introduction of EVs (i.e., fleet composition and charging station location). The goal of the proposed model is to minimize the fuel, EV, ICEV, and EV charger costs. The results show that the EV share of a mixed fleet is affected by gasoline and electricity prices and the distances traveled in a given network. This paper shows that the EV share of a mixed fleet increases when the gasoline cost increases and the electricity cost decreases. [ABSTRACT FROM AUTHOR]

The integrated energy system is widely acknowledged as an effective method for advancing the adoption of renewable energy sources and reducing carbon emissions. To address economic issues caused by the inconsistency between traditional single-stage planning capacities of the park-level integrated energy system (PIES), the long-term planning model is proposed, which consists of multi-stage divisions and incorporates the ladder-type carbon trading mechanism. The model utilizes the long-term, multi-stage planning approach to determine the optimal installed capacity of equipment. Meanwhile, the ladder-type carbon trading mechanism is conducted considering the relationship between actual carbon emissions, carbon emission quotas, and carbon trading cost. The study assesses the impact of carbon trading mechanisms and various planning stage divisions on the economic feasibility of the PIES and its ability to reduce carbon emissions. The results indicate that compared to fixed carbon price trading strategies, the implementation of ladder-type carbon trading increases costs by 0.15 %–0.18 %, but reduces carbon emissions by 0.36 %–0.6 %; as the number of planning stages increases, carbon emissions significantly decrease, and lifecycle costs also significantly decrease. Compared to traditional single-stage planning, carbon emissions decrease by 14.6 % and lifecycle costs decrease by 15.17 % at number of planning stage K = 15; when the baseline price is set at 0.5 yuan/kg and the price growth rate is 0.5, the optimal values of carbon emissions and carbon trading cost are achieved. In conclusion, this study serves as references for the strategic implementations of PIES, emphasizing the importance of economic efficiency and low-carbon practices in line with the system's long-term development and sustainability objectives.

Capacity calculations are essential for the long-term planning of railway infrastructure. Many of the methods currently used in practice calculate characteristic capacity values separately for the single elements (mainly lines and nodes) of a railway network. Approaches that consider the entire network to account for interactions between the elements often rely on many assumptions, which renders a direct practical application difficult. This paper therefore introduces a linear optimization model that comprises railway-specific constraints such as minimum headway times, line capacities, and route conflicts. Under the consideration of these constraints, the developed model permits the calculation of a network-wide capacity. The model is validated on a sample network that is based on a real network of the German railway infrastructure.

Under the current geopolitical conditions and the economic sanctions imposed on Russia, there is an objective need to formulate a strategic development plan for the economy as a whole and for specific sectors of the economy. Various methods and tools can be used for strategic planning. One of the methods of strategic planning is the program-targeted method of planning, which has proved to be an effective method of foresight. It is possible to speak about failures of planning activities, but these failures were related not only to shortcomings and application of science-based planning methods but also to the efficiency of the managerial apparatus, which took decisions. It should be noted that it was in the period when science-based planning methods were applied that our country managed to form and develop industrial production in various sectors, and the issue of import substitution did not arise then, as all the stages of the product life cycle were represented at all the enterprises. Currently, the country is facing the problem of strategic development in the context of the imposed economic sanctions. The volume of sanctions is increasing day by day and one can only speculate on the future restrictions imposed. Therefore, there is a need to forecast activities at the level of the whole country, individual industries, and enterprises. One such method is cognitive modeling based on fuzzy logic. This approach involves the use of cognitive principles and methods to understand the behavior of individuals in the system, as well as the interactions and feedback loops between the various components. The purpose of this paper is to retrospectively analyze the application of the cognitive method to modeling. Information systems that have been developed in our country to implement the tasks of cognitive modeling are reviewed, and an assessment of existing software products is made. Also, theoretical materials on cognitive approach in modeling are presented in order to understand the application of this toolkit for modeling socioeconomic systems using elements of fuzzy logic. [ABSTRACT FROM AUTHOR]

In recent years, community microgrids have expanded their power systems with many aims. One of the most important goals of microgrids is to increase resiliency. The main objective of this paper is to develop effective planning tools for community microgrids within electrical distribution networks, with a specific focus on ensuring the provision of critical loads during natural disasters. Additionally, this paper emphasized emphasises long-term planning considerations by using DIgSILENT 15.2 tools. The primary goal of this issue is to create the best planning tools for community microgrids in order to increase the network's resilience to natural disasters, with a focus on important loads like hospitals and hotels. Also, the second goal is an optimization that seeks to reduce overall expenses. Finally, we'll talk about how to get two results: one is to choose a few microgrid-based loads to link to the electrical distribution network, and the other is to show that each microgrid has the power needed to support both its local loads and the system's vital loads in the event of a natural disaster. In this paper, the use of community microgrids for energy access against natural disasters in Indonesia is investigated by considering the case study of microgrids on Lombok Island. The study results, using the proposed framework, show that the presence of a microgrid structure in the distribution network expansion planning helps to improve operating conditions and supply critical loads in natural disasters. [ABSTRACT FROM AUTHOR]

With agriculture the primary driver of biodiversity loss, farmers are increasingly expected to produce environmental outcomes and protect biodiversity. However, lack of attention to the way farmers perceive native vegetation has resulted in conservation targets not being met. The Yorke Peninsula (YP), South Australia, is an agricultural landscape where < 5% of vegetation remains on private properties and roadsides. To identify YP farmers' barriers to vegetation conservation on the roadside and private properties, we interviewed 35 farmers representing 56,980 ha of farms (11% of the YP area) and three agronomists. We identified five barriers to conservation: (1) negative perceptions of roadside vegetation and (2) management bodies; (3) absence of effective conservation programs making use of farmers' motivations; (4) > 50% farmers perceived that long-term planning was for ≤ 30 years, not enough time to promote ecosystem conservation; (5) a lack of natural resource management information for farmers—as a result, farmers relied on their own experience to manage vegetation. Furthermore, most farmers depended on agronomists, who generally had no stake in biodiversity conservation. We recommend that (1) the Local Council restore social capital by liaising with farmers to promote roadside vegetation (2) long-term farmer-led conservation action be established and supported by Government and industry acting as facilitators rather than project managers; (3) a change in policy and training promote the involvement of agronomists in conservation and its management on private properties; (4) all levels of Government develop schemes to demonstrate the tangible benefits of native vegetation as habitat for wildlife; (5) on-farm conservation be celebrated as successful farming. [ABSTRACT FROM AUTHOR]

Agricultural policies play a critical role in determining the availability and stability of food supplies for individuals and communities. This study underscores the importance of incorporating social, economic, environmental, and political dimensions of food security when developing agricultural policy reforms. The study has two main objectives: (1) to disentangle the complexity surrounding food security by mapping policy reform decisions onto a suggested framework, and (2) to provide an empirical basis for analyzing food security using frame package analysis. To achieve these objectives, this study conducted an inductive frame analysis of agricultural policy reforms, using the theoretical framework of the “fractured consensus” regarding the CAP (Common Agricultural Policy). The case of Israel was chosen as an empirical example for the frame package analysis. The extended suggested theoretical framework can contribute to enhancing the research literature on the nexus between agricultural policy reforms and food security from both theoretical and empirical perspectives. Additionally, the proposed framework and its application can serve as a benchmark for evaluating agricultural policy reforms in the context of food security and developing practical strategies in the agri-food sector, considering the involvement of multiple players and interests.

Food systems are linked to multiple critical sustainability issues such as climate change, environmental degradation, and growing socioeconomic inequalities, and there is a clear need for transformative changes in how food systems are imagined and enacted. For transformations to occur, local governments and stakeholders must be able to consider achievable and desirable futures that involve radically different reconfigurations of space and land use. Based in Revelstoke, Canada, this study uses interactive visualization methods to engage local government and food systems stakeholders in an exploration of three future food systems scenarios that center on changes in food supply, food affordability, and food governance. An interactive visualization tool was developed using the Unity3D game engine, which visualizes how transformations of an underutilized railway site in Revelstoke may appear in 2100. The visualizations were presented to the study participants (n = 10) through an online, Zoom-based workshop, where ‘walkthroughs’ of the scenarios were performed by the researchers and the participants subsequently provided feedback. The results of this study indicate that visualization tools can elicit emotional responses, convey human relationships with food and nature, communicate power dynamics, and incorporate social justice considerations. The results also show that the visualization’s representation of local infrastructure and services, the completeness of a virtual environment, and the plausibility of a depicted future affect the user assessment of the visualized scenarios.

This article discusses the process of forming the General Plan of St. Petersburg. The short-comings of the existing General Plan of St. Petersburg are revealed. The concepts of the General Plan, territorial planning documents, the process of making changes to the General Plan of St. Petersburg are analyzed. Based on the conducted research, the author proposed a solution aimed at the optimal functioning of the General Plan.

Intra-company and strategic planning consider the organization from different sides, combining the results obtained to compile a comprehensive strategy based on planned indicators, based on the capabilities of the enterprise and the assessment of external competitive advantages. In addition, intra-company and strategic planning helps industrial enterprises to make rational decisions and control risks in a volatile business environment. At the output, the company receives a single plan with priority areas of business development. The purpose of the work is to analyze the use of intra-company and strategic planning tools at industrial enterprises. In the conducted research general scientific methods were used: analysis, synthesis, grouping, generalization. Project and process management becomes a solution in the implementation of the investment block of the business strategy (a key tool). In PJSC “Quadra” it was proposed to introduce a projectprocess approach to management. The modified life cycle management system of the investment project (within the framework of the project-process approach) will avoid the following losses: in the form of RUB 250 thousand of the working time fund of the engineering staff of the branch. Rosatom State corporation considered a Scrum methodology, where social and economic effect from its application is 70% of successfully realized tasks, 20% – experience exchange between employees, 10% – training development.

Long-term planning in all regions in Indonesia in 2025 provides a powerful opportunity to commit governments to community empowerment, an opportunity dependent on the intention of those who are elected to power in the 2024 elections, and their commitment to stress sustainable economic development in those long-term plans, and the regulations to implement the plan. As the culture of reglomania (gila peraturan) is a key inhibiter of empowerment there is a need to change that culture to one that empowers and directs development of the green economy. This paper identifies problems with legislation, including a failure to identify the public service of creating an ordered environment for community development, including regulations for economic linkages and collaboration while providing for diversity. This leads to a reconsideration of the role of provinces, further consideration of accessibility and management of land, and integrity in government. The paper concludes with changes needed in campaigning in 2024 in order to lay the foundation for medium-term and long-term plans for building community empowerment after the elections, and provides a set of recommendations.

Decarbonization of the power sector in China is an essential aspect of the energy transition process to achieve carbon neutrality. The power sector accounts for approximately 40% of China’s total CO2 emissions. Accordingly, collaborative optimization in power generation expansion planning (GEP) simultaneously considering economic, environmental, and technological concerns as carbon emissions is necessary. This paper proposes a collaborative mixed- integer linear programming optimization approach for GEP. This minimizes the power system’s operating cost to resolve emission concerns considering energy development strategies, flexible generation, and resource limitations constraints. This research further analyzes the advantages and disadvantages of current GEP techniques. Results show that the main determinants of new investment decisions are carbon emissions, reserve margins, resource availability, fuel consumption, and fuel price. The proposed optimization method is simulated and validated based on China’s power system data. Finally, this study provides policy recommendations on the flexible management of traditional power sources, the market-oriented mechanism of new energy sources, and the integration of new technology to support the attainment of carbon-neutral targets in the current energy transition process.

In asset management for energy portfolios, quantitative methodologies are typically employed. In Brazil, the NEWAVE computational model is universally used to generate scenarios of hydraulic production and future prices, which result in revenue distributions. These distributions are then used to estimate the portfolio's revenue and assess its risk. Although this is a well-established analysis, it has some shortcomings that are not always considered. The validity of the revenue series constructed by NEWAVE, especially in long-term analysis, is a real problem for agents concerning the acquisition of assets such as power plants. Another issue is the disregard for other objectives that are important for the operationality of the management task and are often ignored, such as operational risk. To address these limitations, this work combines the areas of multicriteria decision making under uncertainty and risk management and presents a methodology for evaluating the acquisition of long-term energy assets, as well as a practical application of the proposed method. Investment alternatives are evaluated in multiple developed scenarios, so it is possible to measure how robust a given option is. By analyzing several scenarios simultaneously, a larger region of uncertainties can be covered, and therefore, decision making becomes more secure. The proposed methodology includes six objectives, designed to address a wider range of stakeholder needs. This approach is applied to an illustrative portfolio, producing results that allow for a more comprehensive understanding of decision attributes. Therefore, this work not only addresses the current limitations in the field but also adds an original contribution by considering simultaneously several scenarios and integrating multiple objectives in a robust and secure decision-making framework. [ABSTRACT FROM AUTHOR]

Robustness analysis can support the design and operation of large‐scale water infrastructure projects confronting deeply uncertain futures. However, diverse actors, contextual specificities, sectoral interests, and risk attitudes make it difficult to identify an appropriate robustness metric to rank decision alternatives under deep uncertainty. Here, we clarify how methodological choices affect robustness evaluation using the multi‐actor, multi‐sector Inchampalli‐Nagarjuna Sagar water transfer megaproject in Southern India. We compare a suite of water transfer strategies discovered using evolutionary multi‐objective direct policy search (EMODPS), a strategy proposed by regional authorities and the status quo of no water transfer. We stress‐test these strategies across scenarios that capture climatic and socioeconomic uncertainties and rank them using robustness metrics representing sectoral perspectives and priorities of different actors with varying risk attitudes. Results show a considerable impact of metric choices on robustness rankings of strategies, with compromise solution discovered via EMODPS as robust. The no‐transfer strategy results in the worst water supply robustness with an average volumetric deficit of 17% of total historical demands but emerges as a robust alternative for 6 out of 12 combinations of actor‐sectors with high risk aversion. Also, changes in the amplitude of the Indian Summer Monsoon is identified as the most important uncertain factor determining the failure of strategies. Our findings highlight that the selection of robust solutions should be guided by an understanding of how assumed risk attitudes shape stakeholders' perceptions of vulnerabilities. These findings are generalizable to large infrastructure projects with diverse stakeholders and multisectoral impacts. Plain Language Summary: Climate change and growing multi‐sectoral competition for water resources are motivating the design and evaluation of infrastructure‐based adaptation actions. Here, we explore the Inchampalli‐Nagarjuna Sagar (INS) mega water transfer project; a multi‐actor and a multi‐sector project that aims to transfer water from the Godavari basin to the Krishna basin in Southern India. The project will affect multiple sectors including agriculture, domestic water supply, and downstream aquatic ecology of both rivers and involves multiple actors—the donor, recipient basin and the combined system. It is critical to understand if the INS mega water transfer can robustly meet its intended benefits while limiting unintended consequences in the future. We formally explore different combinations of actors and sectors' objectives, their risk attitudes, and scenario sampling strategies providing a rich context for understanding conflicts and limiting the unintended consequences of myopic analyses. Results show emergent tradeoffs between the ecological requirements of the donor and the water supply needs of the recipient. Our analysis indicates that large‐scale water infrastructure projects need to employ broad exploratory robustness analyses that better engage with conflicting stakeholder objectives and that help to clarify how differences in risk aversion shape the vulnerabilities of preferred actions. Key Points: Multi actor and sector robustness trade‐offs are often not explored due to narrowly defined robustness metricsRobustness rankings for decision alternatives across robustness metrics shed light on trade‐offs across actors, sectors, and risk attitudesClarify donor‐recipient conflicts between ecological needs and socio‐economic development for a proposed water transfer mega‐project [ABSTRACT FROM AUTHOR]

The field of strategic planning and decision-making is crucial for the success and sustainability of manufacturing organizations. This paper presents a combined methodological approach, using quantitative data analysis to support long-term planning through the Quantitative Strategic Planning Matrix (QSPM). The QSPM enables the identification of problems and supports effective decision-making by evaluating the ranking of alternatives and assessing the organization's internal and external factors. This study provides insights into the clearness of strategic planning and decision-making, as well as sustainable evaluation of alternatives for manufacturing organizations in Kosovo. The research identifies backward, forward, and horizontal integration as key strategic alternatives for achieving organizational longevity. By utilizing the QSPM, this study offers valuable guidance for decision-makers and strategic planning professionals in the manufacturing industry. [ABSTRACT FROM AUTHOR]

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In the context of the development of a new round of the global economic crisis, the growth of regional and global instability, the factor of importance of improving the tools for the integration development of the Eurasian Economic Union is extremely acute. Strategic planning is one of the most important mechanisms for improving integration processes. It is the long-term development documents that are able to foresee and successfully coordinate the problems of wealth inequality, the quality of living standards, the access of various social strata of society to financial services, etc. However, such program documents are doomed to failure without the presence of reasonable priorities, focused mainly on the implementation of structural changes in the economies of the EAEU and its potential new members, as well as today’s observers of the Eurasian Economic Union.Aim. The purpose of the study is to analyze the current state of long-term socio-economic planning and forecasting within the boundaries of the EAEU. A mechanism of “transinstitutional cooperation” is proposed, focused on strengthening integration ties through institutional transformations. The macro-regional approach is considered as an effective model of cooperation between states within the framework of various socio-economic tools.Task. Thus, the objectives of the study were: to demonstrate the tools for the development of “transinstitutional interaction” within the boundaries of the Eurasian Economic Union, to give examples of such cooperation based on the possible cooperation of the EAEU countries with potential members of the union (Uzbekistan), as well as to analyze the legislative framework and the accumulated experience of “strategizing” in borders of the Eurasian economic integration.Methods. The research methods are comparative analysis when comparing the standard and interregional approaches of “transinstitutional interaction” for the development of the EAEU states, the method of expert assessments — when developing recommendations for improving the mechanisms of strategic planning in the Russian Federation, methods of structural and logical analysis — when determining the priority tools in the development of the Russian Federation and the Republic of Uzbekistan.Results. As a result, the main challenges of the EAEU in terms of improving the strategic planning tool were identified. A mechanism of “transinstitutional cooperation” is proposed, focused on strengthening integration ties through institutional transformations. The macro-regional approach is considered as an effective model of cooperation between states within the framework of various socio-economic tools. The prospects for integration ties between the EAEU countries and the Republic of Uzbekistan are analyzed in order to analyze the possibilities of unifying strategic planning mechanisms within the framework of “transinstitutional cooperation”. Recommendations are given for improving the strategic planning of the Russian Federation as a locomotive state in the development of strategic planning in the EAEU.Conclusion. As the data presented in the paper show, the member states of the EAEU+ (Eurasian integration countries + observer countries + potential members of the union — Uzbekistan) face similar problems with regard to the strategic development of their territories. The “transinstitutional approach” presented by the authors will allow the members of the Eurasian Economic Union to unite in solving socio-economic challenges, to systematize efforts towards improving the mechanisms of socioeconomic development, significantly saving on the “scale effect” in the search for new socio-economic tools, testing its effectiveness and process control of achieved indicators.

A shipyard's production plan has a hierarchical structure comprising a long-term plan and a mid-term or short-term plan. The mid-term schedule is established based on the major schedules of the long-term plan. However, in the long-term planning stage, the mid-term schedule is not considered owing to timing discrepancies and the lack of data. Therefore, even if a major schedule is changed to achieve production goals – such as workload balancing in the mid-term scheduling process – this is not reflected in the long-term plan. To solve these discrepancy challenges in conventional production planning, the problems of an existing shipbuilding production planning process were derived, and an algorithm to optimize the berth schedule by reflecting the mid-term schedule when establishing a long-term plan was developed. The developed methodology and algorithm were installed in an existing planning system and applied to an actual shipyard production planning process. Results showed improvements in long-term and mid-term scheduling. [ABSTRACT FROM AUTHOR]

Decarbonization of the power sector in China is an essential aspect of the energy transition process to achieve carbon neutrality. The power sector accounts for approximately 40% of China's total CO2 emissions. Accordingly, collaborative optimization in power generation expansion planning (GEP) simultaneously considering economic, environmental, and technological concerns as carbon emissions is necessary. This paper proposes a collaborative mixedinteger linear programming optimization approach for GEP. This minimizes the power system's operating cost to resolve emission concerns considering energy development strategies, flexible generation, and resource limitations constraints. This research further analyzes the advantages and disadvantages of current GEP techniques. Results show that the main determinants of new investment decisions are carbon emissions, reserve margins, resource availability, fuel consumption, and fuel price. The proposed optimization method is simulated and validated based on China's power system data. Finally, this study provides policy recommendations on the flexible management of traditional power sources, the market-oriented mechanism of new energy sources, and the integration of new technology to support the attainment of carbon-neutral targets in the current energy transition process. [ABSTRACT FROM AUTHOR]

Abstract Robustness analysis can support the design and operation of large‐scale water infrastructure projects confronting deeply uncertain futures. However, diverse actors, contextual specificities, sectoral interests, and risk attitudes make it difficult to identify an appropriate robustness metric to rank decision alternatives under deep uncertainty. Here, we clarify how methodological choices affect robustness evaluation using the multi‐actor, multi‐sector Inchampalli‐Nagarjuna Sagar water transfer megaproject in Southern India. We compare a suite of water transfer strategies discovered using evolutionary multi‐objective direct policy search (EMODPS), a strategy proposed by regional authorities and the status quo of no water transfer. We stress‐test these strategies across scenarios that capture climatic and socioeconomic uncertainties and rank them using robustness metrics representing sectoral perspectives and priorities of different actors with varying risk attitudes. Results show a considerable impact of metric choices on robustness rankings of strategies, with compromise solution discovered via EMODPS as robust. The no‐transfer strategy results in the worst water supply robustness with an average volumetric deficit of 17% of total historical demands but emerges as a robust alternative for 6 out of 12 combinations of actor‐sectors with high risk aversion. Also, changes in the amplitude of the Indian Summer Monsoon is identified as the most important uncertain factor determining the failure of strategies. Our findings highlight that the selection of robust solutions should be guided by an understanding of how assumed risk attitudes shape stakeholders' perceptions of vulnerabilities. These findings are generalizable to large infrastructure projects with diverse stakeholders and multisectoral impacts.

Long-term production planning in open-pit mines is a precedence-constraint knapsack problem. A spatial representation of the mining region (called the block-model) is the primary input of mine planning models. One should note that as the number of blocks and periods to be planned increases, the number of decision variables increases. This paper presents a fast yet straightforward algorithm to reduce binary variables in open-pit mine production planning models. The algorithm considers mining capacity, processing capacity, and pit deepening rate to estimate the time span within which a block is mineable. This paper applies the algorithm in 12 different cases. The number of blocks varies from 1000 to 240000, and the mining periods range from 6 to 30 years. According to the results, this algorithm is helpful for problem size reduction.

In recent years, urban rail funding has become an increasing concern in some western cities. The underlying issues over ridership and funding has largely been driven by trends such as increasing teleworking and new transport modes like ridesharing, which are likely to further exacerbate funding issues in the aftermath of the worldwide health crisis. This paper contributes to the discussion through the examination of funding within urban rail transport, specifically the strengths and weaknesses of mechanisms that can be used to achieve sustainable, stable long-term funding. A unique, very long-term historical dataset of five large metros around the world was collected for this research, with the analysis based on evidence of actual practices, from a relatively rare organisational perspective. Key results include: i) appropriate fare-setting has been critical for long-term financial health, but is vulnerable to inflation effects and political interference; indexing is important but use of consumer prices has led to revenue erosion in real terms, since wage growth is typically higher. ii) How subsidies are generated can have varying impacts on funding stability and sustainability — dedicated taxes and cross-subsidies from road charges are typically better than direct grants as they are secured by legislation; they also reduce political changes and avoid competing claims from other types of government spending (health, education), as compared with grants. iii) Commercial revenue can be a valuable source for future growth, in light of increased resistance to taxation. Real estate-related revenues in particular can be substantial, as in Hong Kong and Tokyo, with historically faster growth than wages, while also capturing any further value increases from rail system improvements. • Strengths and weaknesses analysis of funding sources, using data from 5 large metros • Fare-setting with appropriate index (wages) is crucial for long-term financial health • How subsidies are generated – intrinsic impacts on funds stability and sustainability • Ideally, subsidies secured multi-year with legislation – avoids competing claims • Real estate enables long-term value capture and revenue growth from rail improvements [ABSTRACT FROM AUTHOR]

While climate change is often understood as a collective action and a market problem, we look at it as a problem of planning and coordination. Long-term planning is necessary to promote structural change, which will be required to keep the Paris Agreement's temperature goals. By encouraging states to develop a long-term climate strategy, the Paris Agreement invites countries to turn anticipatory governance into an international governance instrument. In this paper we explore how these strategies describe countries' climate plans and what the perceptions of government officials are about the potential for realization of these strategies. Using mixed methods, we explore both 1) planning dimensions (actions, actors and policies described in the strategies) by applying a topic modeling analysis to 50 documents; and 2) perceptions of the content and challenges to their realization among domestic policy professionals of four major emitters. Our results show that the strategies lack a detailed discussion on how decarbonization pathways could be materialized and who has the responsibility for implementation of long-term targets. Moreover, rather than being a steering instrument, the strategies are dominated by scenario planning and there is also a lack of attention to political issues. Taken together, we contend that strategies are limited in the way they present the future possibilities of low emissions development. To make them more effective in steering long-term decarbonization, greater attention needs to be placed on potential conflicts, barriers and stumbling blocks that may arise along the way. • Long-term climate planning has potential to shift the way we address climate change. • The language used in the strategies are dominated by technical terms and GHG emissions scenarios. • The strategies tend to reduce the political and social complexities of climate change. • As governance instruments, the strategies lack capacity to guide implementation and guidance on how to solve goal conflicts. • The strategies' main value is to provide a platform for alternative discussions. [ABSTRACT FROM AUTHOR]

In recent years, community microgrids have expanded their power systems with many aims. One of the most important goals of microgrids is to increase resiliency. The main objective of this paper is to develop effective planning tools for community microgrids within electrical distribution networks, with a specific focus on ensuring the provision of critical loads during natural disasters. Additionally, this paper emphasized emphasises long-term planning considerations by using DIgSILENT 15.2 tools. The primary goal of this issue is to create the best planning tools for community microgrids in order to increase the network’s resilience to natural disasters, with a focus on important loads like hospitals and hotels. Also, the second goal is an optimization that seeks to reduce overall expenses. Finally, we’ll talk about how to get two results: one is to choose a few microgrid-based loads to link to the electrical distribution network, and the other is to show that each microgrid has the power needed to support both its local loads and the system’s vital loads in the event of a natural disaster. In this paper, the use of community microgrids for energy access against natural disasters in Indonesia is investigated by considering the case study of microgrids on Lombok Island. The study results, using the proposed framework, show that the presence of a microgrid structure in the distribution network expansion planning helps to improve operating conditions and supply critical loads in natural disasters.

In this paper we evaluate different models and constraints to define strategic planning approaches. In addition, we analyze the best models to meet the expectations generated by the organization. A forest company situated in the province of Misiones, Argentina, provided the data. Hence, forest growth was simulated and, ultimately, optimized planning was used to evaluate different scenarios with 50-year horizon. The best results to stabilize log production were obtained when the harvest is relaxed in ±2 years. Relaxing the clear-cut age leads to a better balance in planting, thinning (1, 2, 3 and 4) and clear felling operations. We found that when maximizing the economic benefit, the NPV is slightly higher, however, this is not significant. In this sense, the planner chooses an economic or volumetric objective function. Furthermore, we demonstrated that model 1 presented better results than model 2 because it manages to stabilize production in the planning horizon. The results allow forest companies to see the implication of choosing the model for strategic planning.

Some aspects of the formation and realization of the modern maritime policy of Ukraine have been defined in the article. Its legal basis has been considered, its changes and updates have been monitored. The possibility and the ability to develop the documents of long-term planning in the maritime industry have been noted. At the same time, the belatedness and the lack of actual mechanisms for ensuring the execution of their norms lead to a stagnation of systemic reforms and a comprehensive update of public administration of the sphere. The attention is focused on the importance of a systematic approach to the transformation of legislative and law enforcement practices in the sphere of maritime and port activities in Ukraine, ensuring stability and continuity in their administration. The positive and negative practices in the exercise of powers by some subjects of realization of the maritime and port policy of Ukraine have been described. The pernicious practice of distance and situational intervention of a state in solving problems of the maritime and port industries as a strategic component of its political, social, and economic stability has been emphasized. Author suggests that introduction of modern methodology, such as maritime spatial planning may have positive impact on the effectiveness of Ukrainian maritime policy. When considering the development of the coastal regions as one of the directions of the maritime policy of Ukraine, it has been noted the advantages of creating and functioning the free economic zones in them. The characteristic of the experience of creation and work, as well as the specifics of such forms of trade facilitation (the preferential legal and financially-economic regimes, the presence of a particular specialization of entrepreneurial and investment activities, etc.), shows the economic expediency of granting such status to the port cities and the coastal regions. It has been noted that the free economic zones today are an active means of state policy, capable equally of reanimating depressed territory and giving an additional impetus to the regional points of growth.

Hydrogen energy leads us in an important direction in the development of clean energy, and the comprehensive utilization of hydrogen energy is crucial for the low-carbon transformation of the power sector. In this paper, the demand for hydrogen energy in various fields is predicted based on the support vector regression algorithm, which can be converted into an equivalent electrical load when it is all produced from water electrolysis. Then, the investment costs of power generators and hydrogen energy equipment are forecast considering uncertainty. Furthermore, a planning model is established with the forecast data, initial installed capacity and targets for carbon emission reduction as inputs, and the installed capacity as well as share of various power supply and annual carbon emissions as outputs. Taking Gansu Province of China as an example, the changes of power supply structure and carbon emissions under different scenarios are analysed. It can be found that hydrogen production through water electrolysis powered by renewable energy can reduce carbon emissions but will increase the demand for renewable energy generators. Appropriate planning of hydrogen storage can reduce the overall investment cost and promote a low carbon transition of the power system. [ABSTRACT FROM AUTHOR]

In asset management for energy portfolios, quantitative methodologies are typically employed. In Brazil, the NEWAVE computational model is universally used to generate scenarios of hydraulic production and future prices, which result in revenue distributions. These distributions are then used to estimate the portfolio’s revenue and assess its risk. Although this is a well-established analysis, it has some shortcomings that are not always considered. The validity of the revenue series constructed by NEWAVE, especially in long-term analysis, is a real problem for agents concerning the acquisition of assets such as power plants. Another issue is the disregard for other objectives that are important for the operationality of the management task and are often ignored, such as operational risk. To address these limitations, this work combines the areas of multicriteria decision making under uncertainty and risk management and presents a methodology for evaluating the acquisition of long-term energy assets, as well as a practical application of the proposed method. Investment alternatives are evaluated in multiple developed scenarios, so it is possible to measure how robust a given option is. By analyzing several scenarios simultaneously, a larger region of uncertainties can be covered, and therefore, decision making becomes more secure. The proposed methodology includes six objectives, designed to address a wider range of stakeholder needs. This approach is applied to an illustrative portfolio, producing results that allow for a more comprehensive understanding of decision attributes. Therefore, this work not only addresses the current limitations in the field but also adds an original contribution by considering simultaneously several scenarios and integrating multiple objectives in a robust and secure decision-making framework.

Climate change is affecting natural resources globally, altering ecosystems that support outdoor recreation. In the western United States, effects such as warming temperatures, increased drought, reduced snowpack, and widespread wildfires will change the outdoor recreation landscape. In this article, we synthesize the state of science regarding the effects of climate change on outdoor recreation in the western US and summarize adaptation options that can reduce the consequences of climate change, considering the adaptive capacities of recreationists and managers. We draw from a series of climate change assessments in which researchers and managers collaborated to understand recreation vulnerability to climate change and develop effective adaptations. We conclude that building climate resilience requires a shift in planning and resource allocation decisions, including (1) longer-term planning timeframes, (2) interdisciplinary teams, and (3) collaboration among agencies, recreation providers, and communities. Study Implications: Outdoor recreation in the western US is changing due to the effects of climate change. Organized by five recreational categories, this study describes the vulnerability of outdoor recreation to climate change and synthesizes strategies to adapt recreation management to these vulnerabilities. Multiple direct and indirect factors influence individual recreationists' and land managers' capacities to adapt to climate change, as we describe through a diagram. Climate-resilient land management requires long-term planning, integration of multiple resource areas, and collaboration across agencies, recreation providers, and communities. [ABSTRACT FROM AUTHOR]

Solving the ultimate pit problem remains an important and relevant task in open pit mine planning as a subroutine in sophisticated decision processes, parametric analysis, quantifying the impact of geologic uncertainty, approaching more complicated problems such as production scheduling, or as a subproblem in decomposition. Ultimate pit models often contain dozens of millions of blocks and hundreds of millions of precedence constraints, and they may need to be solved hundreds or even thousands of times. These requirements can quickly overwhelm existing ultimate pit solvers. This paper introduces MineFlow: an open-source C++ library providing efficient and flexible precedence schemes and a stripped down pseudoflow-based solver. In a computational comparison with five modern commercial packages, we show that MineFlow computes consistently identical results in a fraction of the time; for example, with MineFlow a block model containing 16 million blocks is processed in nine seconds, whereas the fastest commercial alternative takes two and a half minutes. These improvements are realized by using implicit precedence schemes and by modifying slightly the conventional pseudoflow algorithm. Additionally, we present a compact notation for the pseudoflow algorithm to assist educators in presenting the latest in ultimate pit optimization. [ABSTRACT FROM AUTHOR]

Large and irregular movements of forcibly displaced people are an escalating global issue today. As a result, forced displacement has become an international problem. It requires planning for the relocation and integration of displaced people. However, forced displacement is not a one-time event. On the contrary, it is an ongoing, long-term process with dynamic parameters. We are interested in the long-term displacement problem, especially for climate-driven cases in which people will be forced to leave uninhabitable regions to escape slow-onset climate change impacts. Creating an optimization model that could cover all the requirements and considerations of such a problem would encounter many challenges. Nonetheless, planning in advance for the upcoming climate-change-driven displacement crisis is critical. Unfortunately, this topic has not been explored sufficiently, especially in the operations research literature. To fill this gap, we focus on developing a mathematical model for the long-term relocation planning of people displaced due to climate change. In this model, uncertainty in demand is represented with various demand scenarios, demand and capacity are managed dynamically, and integration outcomes and related costs are optimized. Ultimately, the purpose of this paper is to provide decision-makers with an initial resource for preparing for upcoming movements under uncertainty. To this end, we propose a two-stage stochastic model to determine optimal flow and location decisions. We run this model under three different demand scenarios with and without considering societal impacts measured by diversity indicators. The results show how profoundly the uncertainty in demand and differences in our focus change the future steps that should be taken. • This work proposes an initial planning model for relocating individuals impacted by the impending unlivable conditions brought about by climate change • A two-stage stochastic programming model is developed to assist in planning for movements under relocation demand uncertainty • Cultural distances measures are integrated to guide relocating individuals into new destination locations [ABSTRACT FROM AUTHOR]

Renewable energies are increasingly playing an important role in the energy mix in Southeast Asia, but many challenges remain before they can compete with fossil fuels. The article examines the current development in the renewable energy in Southeast Asia. The article also analyses feed‐in tariff policy to further support the development of the renewable energy sector in Indonesia, Malaysia, Philippines, Thailand, and Viet Nam. More investments in renewable energy could be attracted given the same level of feed‐in tariff rates, contract length, and capacity cap by improving feed‐in tariff policy predictability. Southeast Asian countries could consider modification of their feed‐in tariffs suggested by the literature, such as for renewable energy generation accompanied with energy storage, tariff degression, caped capacity per region or grid, capacity‐augmentation‐tariff that are differentiated across different types and locations of intermittent power. Few of these features of feed‐in tariff policy are already implemented in some Southeast Asian countries. This article is categorized under:Energy Policy and Planning > Economics and PolicyEnergy and Climate > Economics and Policy [ABSTRACT FROM AUTHOR]

According to the objectives of the Paris Agreement on climate change, the European energy supply must be fully decarbonised by 2050. For the power sector, a massive deployment of decentralised renewable technologies will be required to provide carbon-free electricity. However, other energy-intensive sectors such as gas, heat, transport, and the industrial sectors are more challenging to decarbonise, since they rely mostly on liquid and gaseous fuels. Consequently, exploiting the synergies between energy vectors in an integrated, multi-energy system represents an opportunity for a cost-effective transition towards a carbon-free economy. The objective of this study is to provide insights on the coupling of power and residential heat supply systems in a centralised multi-energy system by developing a linear program that optimises the interactions between energy carriers such as electricity, heat, hydrogen, biomass, and methane to minimise the long-term investments in generation and storage assets. The tool was then applied to a case study for a carbon-neutral energy supply in the Brussels-Capital Region in 2050, and conclusions were drawn on the potential of sector coupling to determine the optimal supply system configuration. The conclusions were that the central planning and operation of a coupled system could induce an annual cost reduction of ownership and operation of more than 23% compared to the individual management of the power and residential heat sectors. The cost reduction reaches 30.9% if one further considers centralised, district-level storage and distribution of heat in district heating systems. Finally, it was concluded that the intermittent renewable energy infeed required along biomass to meet the total energy demand is significantly reduced in the optimal scenario. Indeed, the installed capacities of PV and wind onshore can be respectively reduced by 31.9% and 55.8%. [ABSTRACT FROM AUTHOR]

Long-term production planning in open-pit mines is a precedence-constraint knapsack problem. A spatial representation of the mining region (called the block-model) is the primary input of mine planning models. One should note that as the number of blocks and periods to be planned increases, the number of decision variables increases. This paper presents a fast yet straightforward algorithm to reduce binary variables in open-pit mine production planning models. The algorithm considers mining capacity, processing capacity, and pit deepening rate to estimate the time span within which a block is mineable. This paper applies the algorithm in 12 different cases. The number of blocks varies from 1000 to 240000, and the mining periods range from 6 to 30 years. According to the results, this algorithm is helpful for problem size reduction. [ABSTRACT FROM AUTHOR]

Global warming has reduced the extent of permafrost, increased permafrost temperatures, and deepened the active layer across the Arctic. Permafrost degradation has detrimental effects on infrastructure and negative impacts on ecosystem services for many Arctic communities. This study examines the adaptive capacity for managing permafrost degradation in Northwest Greenland. The methods are based on questionnaire and interview data from fieldwork, frozen ground temperature records and published data forecasting the deepening of the active layer. Results illustrate the impact of permafrost degradation on the physical environment, hunting and harvesting, housing, and the economy in Northwest Greenland. House owners are mending damage caused by ground movement, and local institutions are concerned with the maintenance of roads and other public infrastructure impacted by permafrost. The scientific knowledge needed to inform decision-making is useful for identifying overall changes, but existing data sources are scarce, and more detailed permafrost maps are needed for long-term town planning. The study concludes that many individuals and institutions engage in autonomous adaptation on an ad hoc basis, rather than pursuing an overall strategy to increase the adaptive capacity in advance of future permafrost degradation in Northwest Greenland. [ABSTRACT FROM AUTHOR]