Amro M. Farid

Robust control of quantum information

Errors in the control of quantum systems may be classified as unitary, decoherent, and incoherent. Unitary errors are systematic, and result in a density matrix that differs from the desired one by a unitary operation. Decoherent errors correspond to general completely positive superoperators, and can only be corrected using methods such as quantum error correction. Incoherent errors can also be described, on average, by completely positive superoperators, but can nevertheless be corrected by the application of a locally unitary operation that “refocuses” them. They are due to reproducible spatial or temporal variations in the system’s Hamiltonian, so that information on the variations is encoded in the system’s spatiotemporal state and can be used to correct them. In this paper liquid-state nuclear magnetic resonance is used to demonstrate that such refocusing effects can be built directly into the control fields, where the incoherence arises from spatial inhomogeneities in the quantizing static magnetic...

Production degrees of freedom as manufacturing system reconfiguration potential measures

In recent years, many design approaches have been developed for automated manufacturing systems in the fields of reconfigurable manufacturing systems (RMSs), holonic manufacturing systems (HMSs), and multi-agent systems (MASs). One of the principle reasons for these developments has been to enhance the reconfigurability of a manufacturing system, allowing it to adapt readily to changes over time. However, to date, reconfigurability assessment has been limited. Hence, the efficacy of these design approaches remains inconclusive. This paper is the first of two in this issue to address reconfigurability measurement. Specifically, it seeks to address ‘reconfiguration potential’ by analogy. Mechanical degrees of freedom have been used in the field of mechanics as a means of determining the independent directions of motion of a mechanical system. By analogy, manufacturing degrees of freedom can be used to determine independent ways of production. Furthermore, manufacturing degrees of freedom can be classified into their production and product varieties. This paper specifically focuses on the former to measure the product-independent aspects of manufacturing system ‘reconfiguration potential’. This approach will be added to complementary work on the measurement of ‘reconfiguration ease’ so as to form an integrated reconfigurability measurement process described elsewhere [1—5].

A Reference System Architecture for the Energy–Water Nexus

The energy-water nexus has been studied predominantly through discussions of policy options supported by data surveys and technology considerations. As the degree of coupling between the energy and water systems is affected by the design and operation of various engineered system components, our understanding of the nexus and ability to tackle its associated challenges would be enhanced by a system-of-systems engineering model. Such a model, however, requires, first, the development of an appropriate system architecture that clearly identifies the relevant flows of matter and energy and the defining system parameters. This paper presents a reference system architecture for this purpose developed and presented with the Systems Modeling Language (SysML). Once instantiated, this architecture can serve three purposes. First, the presented graphical models can serve qualitative discussions on where and how the supply and demand of water and energy are interdependent. Second, within the operations timescale, the SysML models can support the development of automated information technology and control solutions that integrate energy and water management. Finally, at a planning timescale, the models can inform quantitative decisions on how to best grow and reconfigure the water, wastewater, and energy infrastructure.

Facilitating ease of system reconfiguration through measures of manufacturing modularity

In recent years, many design approaches have been developed for automated manufacturing systems in the fields of reconfigurable manufacturing systems (RMSs), holonic manufacturing systems (HMSs), and multiagent systems (MASs). One of the principle reasons for these developments has been to enhance the reconfigurability of a manufacturing system, allowing it to adapt readily to changes over time. However, to date reconfigurability assessment has been limited. Hence the efficacy of these design approaches remains inconclusive. This paper is the second of two in this issue to address reconfigurability measurement. Specifically, ‘reconfiguration ease’ has often been qualitatively argued to depend on the systems modularity. For this purpose, this paper develops modularity measures in a three-step approach. Firstly, the nature of typical manufacturing system interfaces is discussed. Next, the qualitative understanding underlying existing modularity measures is distilled. Finally, these understandings are synthesized for a manufacturing system context. This approach forms the second of two pillars that together lay the foundation for an integrated reconfigurability measurement process described elsewhere.

An Enterprise Control Assessment Method for Variable Energy Resource-Induced Power System Imbalances—Part II: 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.

Static Resilience of Large Flexible Engineering Systems: Axiomatic Design Model and Measures

Our modern life has grown to depend on many and nearly ubiquitous large complex engineering systems. Many disciplines now seemingly ask the same question: “In the face of assumed disruption, to what degree will these systems continue to perform and when will they be able to bounce back to normal operation.” This paper seeks to partially fulfill this need with static resilience measures for large flexible engineering systems based upon an axiomatic design model. This development is founded upon graph theory and axiomatic design for large flexible engineering systems (LFESs). Central to the development is the concept of structural degrees of freedom as the available combinations of system processes and resources, which could be individually measured to describe system capabilities or sequentially measured to give a sense of the skeleton of a systems behavior. This approach facilitates the enumeration of service paths through an LFES, along which valuable artifacts flow. Therefore, this work compares the value and quantity of service paths before and after a disruption as measures of static resilience or survivability. To complete the contribution, a full illustrative example from the production system domain is given.

An Axiomatic Design of a Multiagent Reconfigurable Mechatronic System Architecture

In recent years, the fields of reconfigurable manufacturing systems, holonic manufacturing systems, and multiagent 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, their ultimate industrial adoption remains limited. Among the barriers to adoption has been the relative absence of formal and quantitative multiagent system design methodologies based on reconfigurability measurement. Hence, it is not clear that the degree to which these designs have achieved their intended level of reconfigurability, which systems are indeed quantitatively more reconfigurable, and how these designs may overcome their design limitations to achieve greater reconfigurability in subsequent design iterations. To our knowledge, this paper is the first multiagent system reference architecture for reconfigurable manufacturing systems driven by a quantitative and formal design approach. It is rooted in an established engineering design methodology called axiomatic design for large flexible engineering systems and draws upon design principles distilled from prior works on reconfigurability measurement. The resulting architecture is written in terms of the mathematical description used in reconfigurability measurement, which straightforwardly allows instantiation for system-specific application.

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.

A meta-system architecture for the energy-water nexus

The energy-water nexus has been studied predominantly through discussions of policy options supported by data surveys and technology considerations. At a technological level, there have been attempts to optimize coupling points between the electricity and water systems to reduce the water-intensity of technologies in the former and the energy-intensity of technologies in the latter. To our knowledge, there has been little discussion of the energy-water nexus from an engineering systems perspective. As the energy-water nexus presents a large scale, multidisciplinary problem with various technological and non-technological dimensions, efforts for coordinated control, operation & planning of the energy and water systems would benefit from the modeling platforms developed in systems engineering. This paper presents a meta-architecture of the energy-water nexus in the electricity supply, engineered water supply and wastewater management systems developed using the Systems Modeling Language (SysML). This meta-architecture serves to elucidate the nexus for qualitative discussions. Once instantiated such an architecture can serve as a conceptual framework upon which quantitative planning and control approaches can be based.

An enhanced method for the determination of load following reserves

Power generation reserves play a central role for maintaining the balance of generation and consumption. Reserves, scheduled in advance, compensate for forecast error, variability and transmission losses. However, as reserves are a costly commodity, their amount should be carefully assessed to prevent unnecessary expense. Currently, the quantity of required reserves are determined based upon a posteriori methods that use operators experience and established assumptions. This paper instead presents a method founded upon non-dimensional numbers and digitial signal processing to determine the quantity of load following reserves a priori.