Measures of reconfigurability and its key characteristics in intelligent manufacturing systems

\In recent years, the fields of reconfigurable manufacturing systems, holonic manufacturing systems, and multi-agent systems have made technological advances to support the ready reconfiguration of automated manufacturing systems. While these technological advances have demonstrated robust operation and been qualitatively successful in achieving reconfigurability, limited effort has been devoted to the measurement of reconfigurability in the resultant systems. Hence, it is not clear (1) to which degree these designs have achieved their intended level of reconfigurability, (2) which systems are indeed quantitatively more reconfigurable and (3) how these designs may overcome their design limitations to achieve greater reconfigurability in subsequent design iterations. Recently, a reconfigurability measurement process based upon axiomatic design knowledge base and the design structure matrix has been developed. Together, they provide quantitative measures of reconfiguration potential and ease. This paper now builds upon these works to provide a set of composite reconfigurability measures. Among these are measures for the key characteristics of reconfigurability: integrability, convertibility, and customization, which have driven the qualitative and intuitive design of these technological advances. These measures are then demonstrated on an illustrative example followed by a discussion of how they adhere to requirements for reconfigurability measurement in automated and intelligent manufacturing systems

Architecting a System Model for Personalized Healthcare Delivery and Managed Individual Health Outcomes

In recent years, healthcare needs have shifted from treating acute conditions to meeting an unprecedented chronic disease burden. The healthcare delivery system has structurally evolved to address two primary features of acute care: the relatively short time period, on the order of a patient encounter, and the siloed focus on organs or organ systems, thereby operationally fragmenting and providing care by organ specialty. Much more so than acute conditions, chronic disease involves multiple health factors with complex interactions between them over a prolonged period of time necessitating a healthcare delivery model that is personalized to achieve individual health outcomes. Using the current acute-based healthcare delivery system to address and provide care to patients with chronic disease has led to significant complexity in the healthcare delivery system. This presents a formidable systems’ challenge where the state of the healthcare delivery system must be coordinated over many years or decades with the health state of each individual that seeks care for their chronic conditions. This paper architects a system model for personalized healthcare delivery and managed individual health outcomes. To ground the discussion, the work builds upon recent structural analysis of mass-customized production systems as an analogous system and then highlights the stochastic evolution of an individual’s health state as a key distinguishing feature

Impacts of Industrial Baseline Errors on Costs and Social Welfare in the Demand Side Management of Day-Ahead Wholesale Markets

Demand Side Management (DSM) has been recognized for its potential to counteract the intermittent nature of renewable energy, increase system efficiency, and reduce system costs. While the popular approach among academia adopts a social welfare maximization formulation, the industrial practice in the United States electricity market compensates customers according to their load reduction from a predefined electricity consumption baseline that would have occurred without DSM. This paper is an extension of a previous paper studying the differences between the industrial & academic approach to dispatching demands. In the previous paper, the comparison of the two models showed that while the social welfare model uses a stochastic net load composed of two terms, the industrial DSM model uses a stochastic net load composed of three terms including the additional baseline term. That work showed that the academic and industrial optimization method have the same dispatch result in the absence of baseline errors given the proper reconciliation of their respective cost functions. DSM participants, however, and very much unfortunately, are likely to manipulate the baseline in order to receive greater financial compensation. This paper now seeks to study the impacts of erroneous industrial baselines in a day-ahead wholesale market context. Using the same system configuration and mathematical formalism, the industrial model is compared to the social welfare model. The erroneous baseline is shown to result in a different and more importantly costlier dispatch. It is also likely to require more control activity in subsequent layers of enterprise control. Thus an erroneous baseline is likely to increase system costs and overestimate the potential for social welfare improvements

An Enterprise Control Assessment Method for Variable Energy Resource-Induced Power System Imbalances--Part II: Parametric Sensitivity Analysis

In recent years, renewable energy has developed to address energy security and climate change drivers. However, as energy resources, they possess a variable and uncertain nature that significantly complicates grid balancing operations. As a result, an extensive academic and industrial literature has developed to determine how much such variable energy resources (VERs) may be integrated and how to best mitigate their impacts. While certainly insightful with the context of their application, many integration studies have methodological limitations because they are case specific, address a single control function of the power grid balancing operations, and are often not validated by simulation. The prequel to this paper presented a holistic method for the assessment of power grid imbalances induced by VERs based upon the concept of enterprise control. This paper now systematically studies these power grid imbalances in terms of five independent variables: 1) day-ahead market time step; 2) real-time market time step; 3) VER normalized variability; 4) normalized day-ahead VER forecast error; and 5) normalized short-term VER forecast error. The systematic study elucidates the impacts of these variables and provides significant insights as to how planners should address these independent variables in the future

An Enterprise Control Assessment Method for Variable Energy Resource-Induced Power System Imbalances--Part I: Methodology

In recent years, an extensive academic and industrial literature has been developed to determine how much such variable energy resources (VERs) may be integrated and how to best mitigate their impacts. While certainly insightful within the context of their application, many integration studies have methodological limitations in that they are case specific, address a single control function of power grid balancing operations, and are often not validated by simulation. This paper presents a holistic method for the assessment of power grid imbalances induced by VERs based upon the concept of enterprise control. It consists within a single package a three-layer enterprise control simulator which includes most of the balancing operation functionality found in traditional power systems. The control layers include a resource scheduling layer composed of a security-constrained unit commitment, a balancing layer composed of a security-constrained economic dispatch, and a regulation layer. The proposed method is validated by a set of numerical simulations. The sequel to this paper submitted to the same issue provides a set of extensive results that demonstrate how power grid balancing operations systematically address VER integration

A Hybrid Dynamic System Assessment Methodology for Multi-Modal Transportation-Electrification

In recent years, electrified transportation, be it in the form of buses, trains, or cars have become an emerging form of mobility. Electric vehicles (EVs), especially, are set to expand the amount of electric miles driven and energy consumed. Nevertheless, the question remains as to whether EVs will be technically feasible within infrastructure systems. Fundamentally, EVs interact with three interconnected systems: the (physical) transportation system, the electric power grid, and their supporting information systems. Coupling of the two physical systems essentially forms a nexus, the transportation-electricity nexus (TEN). This paper presents a hybrid dynamic system assessment methodology for multi-modal transportation-electrification. At its core, it utilizes a mathematical model which consists of a marked Petri-net model superimposed on the continuous time microscopic traffic dynamics and the electrical state evolution. The methodology consists of four steps: (1) establish the TEN structure; (2) establish the TEN behavior; (3) establish the TEN Intelligent Transportation-Energy System (ITES) decision-making; and (4) assess the TEN performance. In the presentation of the methodology, the Symmetrica test case is used throughout as an illustrative example. Consequently, values for several measures of performance are provided. This methodology is presented generically and may be used to assess the effects of transportation-electrification in any city or area; opening up possibilities for many future studies

Opportunities for Energy-Water Nexus Management in the Middle East & North Africa

Electric power is required to produce, treat, distribute, and recycle water while water is required to generate and consume electricity. Naturally, this energy-water nexus is most evident in multi-utilities that provide electricity and water but still exists when the nexus has distinct organizations as owners and operators. Therefore, the sustainability question that arises from energy-water trade-offs and synergies is very much tied to the potential for economies of scope. Furthermore, in the Middle East and North Africa (MENA) region, multi-utilities are not only common, but also the nexus is particularly exacerbated by the high energy intensity of the water supply due to limited fresh water resources. The goal of this paper is to identify and motivate several opportunities for enhanced integrated operations management and planning in the energy-water nexus in multi-utilities in the MENA. It proceeds in four parts. First, an exposition of the energy-water nexus especially as it applies to the MENA is given. This discussion focuses on the electric power system, the potable water distribution system, and thirdly, the wastewater distribution system. Second, the paper shifts to opportunities in integrated operations management highlighted by an energy-water nexus supply- side economic dispatch illustration. Thirdly, the discussion shifts to planning opportunities for the energy-water nexus for the sustainable development of water and energy resources. A concluding section summarizes the policy implications of the identified opportunities