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This research paper addresses the inaccuracies in the current methods for estimating the capacity value of photovoltaic (PV) plants, which rely heavily on large‐scale data and fail to represent the actual capacity value pattern accurately. The research conducts case studies in Belgium, Texas, and California to analyze the impact of different factors on capacity value. It proposes a new metric called the Marginal Moving‐Average Limited‐Hours (MMALH) Equivalent Load‐Carring Capability (ELCC) ‐ Based capacity value. The proposed metric reduces the dependence on hourly data and better represents capacity value. The results from real case studies validate the effectiveness of the new metric, highlighting its novelty and contribution to the assessment of capacity value in PV power systems. The study emphasizes the importance of accurately assessing the capacity value of PV compared to conventional units, considering environmental factors and system parameters. The study exposes the shortcomings in current metrics and advocates for the MMALH ELCC methodology as a more precise evaluation approach. The research suggests optimizing design, employing advanced tracking systems, enhancing maintenance practices, and ensuring effective grid integration to boost solar plant efficiency. Consistent monitoring and analysis of the utilization factor are vital for pinpointing improvement areas and augmenting productivity. [ABSTRACT FROM AUTHOR]

In heterogenous environments, predation risk from multiple predators and the availability of resources fluctuate both spatially and temporally. The various predators may include both aerial and terrestrial species that can facilitate each other and present qualitatively different risks to prey. Animals therefore forage across a complex landscape of fear, with areas of risks and relative safety where resources are generally asymmetrically distributed. Therefore, a trade-off exists between remaining safe and locating food. Animals make foraging decisions regarding where, when and for how long to forage by titrating marginal costs and benefits of foraging within and the marginal value of foraging across depletable resource patches. We conducted a series of titration experiments to determine how Allenby's gerbils (Gerbillus andersoni allenbyi) titrated food and safety when presented with predation risk from owls, vipers and the joint risk from both predators. We manipulated bush and open microhabitats by increasing food availability in the riskier patches. In response to the different levels of enrichment, gerbils titrated food and safety. Riskier open microhabitats needed to be four times as rich in food as bush patches to be of equal value when subjected to predation from owls and the joint risk from owls and vipers. In response to vipers alone, riskier bush patches needed to be 2–4 times as rich in food as safer open patches for the marginal value of foraging to equalize across microhabitats. Overall, predation risk from owls and the joint risk from owls and vipers resulted in the greatest foraging costs for gerbils in risky microhabitats. Thus, the combined overall risk from multiple predator species was equivalent to the risk presented by the gerbils' most dangerous predator (owls alone). Significance statement: Animals trade-off remaining safe with locating food by titrating the marginal costs and benefits of foraging. We assessed how foragers titrate these costs and benefits through behavioural titration experiments. In our study, gerbils titrated food and safety in response to owls and vipers, aerial and terrestrial predators known to facilitate one another. Riskier patches needed to be 2–4 times as rich in food as safer patches to be of equal value to foraging gerbils. From the gerbils' perspective, owls are more formidable predators than vipers; despite the facilitation that occurs between these predators, the combination of the two predators had little effect on the titration beyond that of the owls alone. Behavioural titrations are important for quantifying differences in foraging costs between microhabitats and in response to multiple predators with different hunting strategies. As single-predator systems are relatively rare, titration experiments provide the opportunity to gain insights into the foraging/safety trade-offs made by animals in response to multiple predators on the landscape. [ABSTRACT FROM AUTHOR]

Demand analysis requires aggregation of commodities. Some are imposed at the data collection level, leaving some for the estimation level. When data are collected, the implicit assumption underlying the aggregation is perfect substitutability: one gallon of gasoline is viewed by consumers as equivalent to another gallon; hence, the two are added together. While such aggregation can be carried out further by the data analyst, it is difficult to incorporate perfect substitutability into the estimation of direct demand systems. Perfect substitution in that context implies discontinuous demand functions, which are not nested within standard empirical demand systems. Perfect substitution is much more easily handled in a system of inverse demands, though an empirical method to impose perfect substitutability in an inverse demand system has not previously appeared in the literature. In this article, we develop such a method, which allows perfect substitutability to be imposed as a prior restriction. We use Leamer’s information contract curve as a tool to flexibly impose the substitution restriction and to investigate consistency between the data and prior. We illustrate the method with an application to inverse demands for fish in Korea. [ABSTRACT FROM PUBLISHER]

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Using a recent in-store stated choice survey, this study examines consumer preference and willingness to pay for blueberry jam with quality attributes not commonly seen on the market. A cluster analysis is first adopted to classify consumers into different groups based on a large number of consumer characteristic variables. A spilt sample analysis is conducted under each cluster and results indicate that consumers behave differently in separate clusters and the derived economic values associated with each attribute also depend on cluster membership. [ABSTRACT FROM AUTHOR]

Individuals within a population often differ considerably in size or resource status as a result of environmental variation. In these circumstances natural selection would favour organisms not with a single, genetically determined allocation, but with a genetically determined allocation rule specifying allocation in relation to size or environment. Based on a graphical analysis of a simple evolutionarily stable strategy (ESS) model for herbaceous perennial plants, we aim to determine how cosexual plants within a population should simultaneously adjust their reproductive allocation and sex allocation to their size. We find that if female fitness gain is a linear function of resource investment, then a fixed amount of resources should be allocated to male function, and to post-breeding survival as well, for individuals above a certain size threshold. The ESS resource allocation to male function, female function, and post-breeding survival positively correlate if both male and female fitness gains are a saturating function of resource investment. Plants smaller than the size threshold are expected to be either nonreproductive or functionally male only. [ABSTRACT FROM AUTHOR]

ISO 14041 requires that allocation by physical causality must reflect the quantitative changes in product outputs or functions and will not necessarily be in proportion to simple physical measure such as mass. This paper examines the instances where physical causality can be represented by mass. However, it also goes further than ISO to demonstrate that the type of causality in the system is not necessarily always the same and can change depending on the way the system is operated. Whole system modelling and the marginal allocation approach are used to identify the correct type of causality for different operating states of the system and the corresponding changes in the environmental burdens. This is generally not possible with the other allocation methods, also examined in this paper. Both process- and product-related burdens are considered and the approach is illustrated by a reference to an existing system producing five boron co-products [ABSTRACT FROM AUTHOR]

This paper uses an industrial case study of a boron system producing five co-products to examine different allocation methods recommended by ISO 14041 and compare them with the allocation methods most commonly used by LCA practitioners. In particular, allocation by physical causality is discussed. The paper illustrates how the use of whole system modelling can help to identify the correct type of causality for allocation. The case examined here concerns marginal changes of product-related parameters in the system, in this case represented by the output of boron co-products. The analysis shows that in some cases it can he correct to allocate the burdens on the basis of a simple physical quantity, such as mass, as long as the allocation parameter is based on physical causation and is not chosen arbitrarily. In whole system modelling, the correct causality is identified by the model itself, so that the possibility of allocation by an arbitrary parameter is avoided. However, as for system disaggregation and expansion, allocation through mathematical modelling may only be possible if detailed data for the system are available. [ABSTRACT FROM AUTHOR]

For a given optimization problem, P, considered as a function of the data, its marginal values are defined as the directional partial derivatives of the value of P with respect to perturbations in that data. For linear programs, formulas for the marginal values were given by Mills, [10], and further developed by the current author [16]. In this paper, the marginal value formulas are extended to the case of mixed integer linear programming (MIP). As in ordinary linear programming, discontinuities in the value can occur, and the analysis here identifies them. This latter aspect extends previous work on continuity by the current author, [18], Geoffrion and Nauss, [5], Nauss, [11], and Radke, [12], and work on the value function of Blair and Jeroslow, [2]. Application is made to model formulation and to post-optimal analysis. [ABSTRACT FROM AUTHOR]

Second-order necessary conditions in nonlinear programming are derived by a new method that does not require the usual sort of constraint qualification. In terms of the multiplier vectors appearing in such second-order conditions, an estimate, is obtained for the generalized subgradients of the optimal, value function associated with a parameterized nonlinear programming problem. This yields estimates for 'marginal values' with respect to the parameters. The main theoretical tools are the augmented Lagrangian and, despite the assumption of second-order smoothness of objective constraints, the subdifferential calculus that has recently been developed for nonsmooth, nonconvex functions. [ABSTRACT FROM AUTHOR]

Battery electric vehicles (BEV) provide an opportunity to balance supply and demand in future power systems with high shares of fluctuating renewable energy. Compared to other storage systems such as pumped-storage hydroelectricity, electric vehicle energy demand is highly dependent on charging and connection choices of vehicle users. We present a model framework of a utility-based stock and flow model, a utility-based microsimulation of charging decisions, and an energy system model including respective interfaces to assess how the representation of battery electric vehicle charging affects energy system optimization results. We then apply the framework to a scenario study for controlled charging of nine million electric vehicles in Germany in 2030. Assuming a respective fleet power demand of 27 TWh, we analyze the difference between power-system-based and vehicle user-based charging decisions in two respective scenarios. Our results show that taking into account vehicle users' charging and connection decisions significantly decreases the load shifting potential of controlled charging. The analysis of marginal values of equations and variables of the optimization problem yields valuable insights on the importance of specific constraints and optimization variables. Assumptions on fleet battery availability and a detailed representation of fast charging are found to have a strong impact on wind curtailment, renewable energy feed-in, and required gas power plant flexibility. A representation of fleet connection to the grid in high temporal detail is less important. Peak load can be reduced by 5% and 3% in both scenarios, respectively. Shifted load is robust across sensitivity analyses while other model results such as curtailment are more sensitive to factors such as underlying data years. Analyzing the importance of increased BEV fleet battery availability for power systems with different weather and electricity demand characteristics should be further scrutinized. [ABSTRACT FROM AUTHOR]

ISO 14041 requires that allocation by physical causality must reflect the quantitative changes in product outputs or functions and will not necessarily be in proportion to simple physical measure such as mass. This paper examines the instances where physical causality can be represented by mass. However, it also goes further than ISO to demonstrate that the type of causality in the system is not necessarily always the same and can change depending on the way the system is operated. Whole system modelling and the marginal allocation approach are used to identify the correct type of causality for different operating states of the system and the corresponding changes in the environmenta burdens. This is generally not possible with the other allocation methods, also examined in this paper. Both process- and product-related burdens are considered and the approach is illustrated by a reference to an existing system producing five boron co-products. [ABSTRACT FROM AUTHOR]