Search

Abstract Recently, hetero-functional graph theory (HFGT) has developed as a means to mathematically model the structure of large-scale complex flexible engineering systems. It does so by fusing concepts from network science and model-based systems engineering (MBSE). For the former, it utilizes multiple graph-based data structures to support a matrix-based quantitative analysis. For the latter, HFGT inherits the heterogeneity of conceptual and ontological constructs found in model-based systems engineering including system form, system function, and system concept. These diverse conceptual constructs indicate multi-dimensional rather than two-dimensional relationships. This paper provides the first tensor-based treatment of hetero-functional graph theory. In particular, it addresses the “system concept” and the hetero-functional adjacency matrix from the perspective of tensors and introduces the hetero-functional incidence tensor as a new data structure. The tensor-based formulation described in this work makes a stronger tie between HFGT and its ontological foundations in MBSE. Finally, the tensor-based formulation facilitates several analytical results that provide an understanding of the relationships between HFGT and multi-layer networks.

Since its first formulation in 1962, the Alternating Current Optimal Power Flow (ACOPF) problem has been one of the most important optimization problems in electric power systems. Its most common interpretation is a minimization of generation costs subject to network flows, generator capacity constraints, line capacity constraints, and bus voltage constraints. The main theoretical barrier to its solution is that the ACOPF is a non-convex optimization problem that consequently falls into the as-yet-unsolved space of NP-hard problems. To overcome this challenge, the literature has offered numerous relaxations and approximations of the ACOPF that result in computationally suboptimal solutions with potentially degraded reliability. While the impact on reliability can be addressed with active control algorithms, energy regulators have estimated that the sub-optimality costs the United States ~ $\$ $ 6–19B per year. Furthermore, and beyond its many applications to electric power system markets and operation, the sustainable energy transition necessitates renewed attention towards the ACOPF. This paper contributes a profit-maximizing security-constrained current-voltage AC optimal power flow (IV-ACOPF) model and globally optimal solution algorithm. More specifically, it features a convex separable objective function that reflects a two-sided electricity market. The constraints are also separable with the exception of a set of linear network flow constraints. Collectively, the constraints enforce generator capacities, thermal line flow limits, voltage magnitudes, power factor limits, and voltage stability. The optimization program is solved using a Newton-Raphson algorithm and numerically demonstrated on the data from a transient stability test case. The theoretical and numerical results confirm the globally optimal solution.

Recently, electric vehicles (EV) have gained much attention as a potential enabling technology to support CO2 emissions reduction targets. Relative to their internal combustion vehicle counterparts, EVs consume less energy per unit distance, and add the benefit of not emitting any carbon dioxide in operation and instead shift their emissions to the existing local fleet of power generation. However, the true success of EVs depends on their successful integration with the supporting infrastructure systems. Building upon the recently published methodology for the same purpose, this paper presents a “systems-of-systems” case study assessing the impacts of EVs on these three systems in the context of Abu Dhabi. For the physical transportation system, a microscopic discrete-time traffic operations simulator is used to predict the kinematic state of the EV fleet over the duration of one day. For the impact on the intelligent transportation system (ITS), the integration of EVs into Abu Dhabi is studied using a multi-domain matrix (MDM) of the Abu Dhabi Department of Transportation ITS. Finally, for the impact on the electric power system, the EV traffic flow patterns from the CMS are used to calculate the timing and magnitude of charging loads. The paper concludes with the need for an intelligent transportation-energy system (ITES) which would coordinate traffic and energy management functionality.

As climate change takes hold in the $21^{st}$ century, it places an impetus to decarbonize the American Electric Power System with renewable energy resources. There is a broad technical consensus that these renewable energy resources cannot be integrated alone but rather require a host of profound changes in the electric grid’s architecture; including meshed distribution lines, and energy storage solutions. One question that arises is whether these three types of mitigation measures required by decarbonization will also serve as adaptation measures when the climate changes and extreme weather phenomena become more prevalent. Consequently, this paper presents a structural resilience analysis of the American electric power system that incrementally incorporates these architectural changes in the future. Building upon a preliminary study, the analysis draws on an emerging hetero-functional graph theory based upon the inter-connectedness of a system’s capabilities. The hetero-functional graph analysis confirms our formal graph understandings from network science in terms of cumulative degree distributions and traditional attack vulnerability measures. The paper goes on to show that hetero-functional graphs relative to formal graphs more precisely describe the changes in functionality associated with the addition of distributed generation and energy storage as the grid evolves to a decarbonized architecture. Finally, it demonstrates that the addition of all three types of mitigation measures enhance the grid’s structural resilience; even in the presence of disruptive random and targeted attacks. The paper concludes that there is no structural trade-off between grid sustainability and resilience enhancements and that these strategic goals can be pursued simultaneously.

The current healthcare system is facing an unprecedented chronic disease burden. This paper develops a dynamic mathematical simulation model for personalized healthcare delivery and managed individual health outcomes. It utilizes a highly novel hetero-functional graph theory, most easily understood as an ontological convergence of model-based systems engineering and network science, along with Petri nets. The dynamics of the model builds upon a recently developed systems architecture for healthcare delivery, which bears several analogies to the architecture of mass-customized production systems. At its essence, the model consists of two synchronized Petri nets; one for the healthcare delivery system and another for individuals’ health state evolution. The dynamic model links logistical and medical phenomena using a combination of a deterministic Petri net model for the former and a fuzzy Petri net for the latter. The model is demonstrated on two clinical case studies; acute and chronic. Together, the case studies show that the model applies equally to the care of both acute and chronic conditions, transparently describes health outcomes and links them to the evolution of the healthcare delivery system and its associated costs.

The bulk electric power system in New England is fundamentally changing. The representation of nuclear, coal and oil generation facilities is set to dramatically fall, and natural gas, wind and solar facilities will come to fill their place. The introduction of variable energy resources (VERs) like solar and wind, however, necessitates fundamental changes in the power grid’s dynamic operation. VER forecasts are uncertain, and their profiles are intermittent; thus requiring greater quantities of operating reserves. This paper describes the methodology and the key findings of the 2017 ISO New England System Operational Analysis and Renewable Energy Integration Study (SOARES). This study was commissioned by the ISO New England stakeholders to investigate the effect of several scenarios of varying generation mix on normal operating reserves. The project was conducted using the holistic assessment approach called the Electric Power Enterprise Control System (EPECS) simulator. The study finds a minimal impact on current normal operating conditions in the ISO-NE system for scenarios with relatively low penetration of VERs. Nevertheless, for scenarios with a significant presence of VERs, the system may require additional amounts of both upward and downward load following reserves and upward and downward ramping reserves to effectively maintain reliable operations. In these scenarios, the curtailment of semi-dispatchable resources also becomes an integral part of balancing performance; in part to complement operating reserves and in part to mitigate the topological limitations of the system. Indeed, the integration of significant amounts of VERs in relatively remote regions significantly increases the potential of congestion on several key interfaces. In many of these scenarios, the system experiences heavy saturations of regulation reserves and their increase would enhance the response to residual imbalances. The concludes with final insights into the emerging roles of curtailment, energy storage, and demand response as integral parts of normal balancing performance. Keywords: Renewable energy integration, Operating reserves, Unit commitment, Economic dispatch, ISO New England, Enterprise control

Recently, the academic and industrial literature has arrived at a consensus in which the electric grid evolves to a more intelligent, responsive, dynamic, flexible, and adaptive system. This evolution is caused by several drivers including: decarbonization, electrified transportation, deregulation, growing electricity demand, and active consumer participation. Many of these changes will occur at the periphery of the grid, in the radial distribution system, and its potentially billions of demand-side resources. Such spatially distributed energy resources naturally require equally distributed control and electricity market design approaches to enable an increasingly active “smart grid.”In that regard, this paper serves to highlight lessons recently learned from the literature and point to seven open long-term challenges facing the future design of electricity markets. They are: 1) simultaneously manage the technical and economic performance of the electricity grid; 2) span multiple operations time scales; 3) enable active demand side resources; 4) activate the power grid periphery; 5) promote synergies with interdependent infrastructures; 6) respect organizational jurisdictions; and 7) promote resilient self-healing operation. For each challenge, some recent contributions are highlighted and promising directions for future work are identified.

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.

Abstract 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.

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.