Within the broad topical designation of “smart grid,” research in demand response, or demand-side management, focuses on investigating possibilities for electrically powered devices to adapt their power consumption patterns to better match the availability of intermittent renewable energy sources, especially wind. Devices such as battery chargers, heating and cooling systems, and computers can be controlled to change the time, duration, and magnitude of their power consumption while still meeting workload constraints such as deadlines and rate of throughput. This thesis presents a system by which a computer server, or multiple servers in a data center, can estimate the power imbalance on the electrical grid and use that information to dynamically change the power consumption as a service to the grid. Implementation on a testbed demonstrates the system with a hypothetical but realistic usage case scenario of an online video streaming service in which there are workloads with deadlines (high-priority) and workloads without deadlines (low-priority). The testbed is implemented with real servers, estimates the power imbalance from the grid frequency with real-time measurements of the live outlet, and uses a distributed, real-time algorithm to dynamically adjust the power consumption of the servers based on the frequency estimate and the throughput of video transcoder workloads. Analysis of the system explains and justifies multiple design choices, compares the significance of the system in relation to similar publications in the literature, and explores the potential impact of the system.

The main objective of this thesis was to develop appropriate system protection schemes against two important causes of failure in power systems, namely, long-term voltage instability and cascade tripping of overloaded transmission lines, mainly due to overloading. To this purpose a distributed undervoltage load shedding scheme against voltage instability, and a centralized protection meant to alleviate line overload are proposed. The former, through the chosen system protection scheme characteristics, has the ability to adjust its actions to the disturbance location and severity. This behavior is achieved without resorting to a dedicated communication network. The distributed controllers do not exchange information, but are rather informed of their respective actions through voltage measurements. Neither do the controllers require a model of the system. This and the absence of communication makes the protection scheme simple and reliable. The other protection scheme, inspired of model predictive control, is aimed at bringing the currents in the overloaded lines below their limits in the time interval left by protections, while accounting for constraints on control changes. Its closed-loop nature allows to compensate for model uncertainties and measurement noise. In order to tune the proposed system protection schemes parameters and validate their performance it was preferred to detect plausible cascading event scenarios. To this purpose, an algorithm meant to identify such complex sequences has been developed. It encompasses hidden failures and the resulting system response. The tests performed on small systems as well as on a real-life one confirm not only that proposed protection schemes appropriately deal with the problems for which they were designed, but also that they cooperate satisfactorily for combined voltage and thermal problems that are beyond their individual capabilities.

In the context of the envisioned electric power delivery system of the future, the smart grid, this dissertation focuses on control and management strategies for integration of distributed energy resources in the power system. This work conceptualizes a hierarchical framework for the control of microgrids---the building blocks of the smart grid---and develops the notion of potential functions for the secondary control for devising intermediate set points to ensure feasibility of operation of the system. A scalar potential function is defined for each controllable unit of the microgrid such that its minimization corresponds to achieving the control goal. The set points are dynamically updated using communication within the microgrid. This strategy is generalized to (i) include both local and system-wide constraints and (ii) allow a distributed implementation. This dissertation also proposes and evaluates a simple yet elaborate distributed strategy to mitigate the transients of controllable devices of the microgrid using local measurements. This strategy is based on response monitoring and is augmented to the existing controller of a power system device. This strategy can be implemented based on either set point automatic adjustment (SPAA) or set point automatic adjustment with correction enabled (SPAACE) methods. SPAA takes advantage of an approximate model of the system to calculate intermediate set points such that the response to each one is acceptable. SPAACE treats the device as a generic system and monitors its response and modulates its set point to achieve the desired trajectory. SPAACE bases its decisions on the trend of variations of the response and accounts for inaccuracies and unmodeled dynamics. Case studies using the PSCAD/EMTDC software environment and MATLAB programming environment are presented to demonstrate the application and effectiveness of the proposed strategies in different scenarios.

In the context of the envisioned electric power delivery system of the future, the smart grid, this dissertation focuses on control and management strategies for integration of distributed energy resources in the power system. This work conceptualizes a hierarchical framework for the control of microgrids---the building blocks of the smart grid---and develops the notion of potential functions for the secondary control for devising intermediate set points to ensure feasibility of operation of the system. A scalar potential function is defined for each controllable unit of the microgrid such that its minimization corresponds to achieving the control goal. The set points are dynamically updated using communication within the microgrid. This strategy is generalized to (i) include both local and system-wide constraints and (ii) allow a distributed implementation. This dissertation also proposes and evaluates a simple yet elaborate distributed strategy to mitigate the transients of controllable devices of the microgrid using local measurements. This strategy is based on response monitoring and is augmented to the existing controller of a power system device. This strategy can be implemented based on either set point automatic adjustment (SPAA) or set point automatic adjustment with correction enabled (SPAACE) methods. SPAA takes advantage of an approximate model of the system to calculate intermediate set points such that the response to each one is acceptable. SPAACE treats the device as a generic system and monitors its response and modulates its set point to achieve the desired trajectory. SPAACE bases its decisions on the trend of variations of the response and accounts for inaccuracies and unmodeled dynamics. Case studies using the PSCAD/EMTDC software environment and MATLAB programming environment are presented to demonstrate the application and effectiveness of the proposed strategies in different scenarios.

Driven by economic, technical and environmental factors, the energy sector is currently undergoing a profound paradigm shift towards a smarter grid setup. Increased intake of Distributed and Renewable Generation (DG) units is one of the Smart Grid (SG) pillars that will lead to numerous advantages among which lower electricity losses, increased reliability and reduced greenhouse gas emissions are the most salient. The increase of DG units’ penetration will cause changes to the characteristics of distribution networks from being passive with unidirectional power flow towards Active Distribution Networks (ADNs) with multi-direction power flow. However, such changes in the current distribution systems structure and design will halt the seamless DG integration due to various technical issues that may arise. Voltage and reactive power control is one of the most significant issues that limit increasing DG penetration into distribution systems. On the other hand, the term microgrid has been created to be the building block of ADNs. A microgrid should be able to operate in two modes of operation, grid-connected or islanded. The successful implementation of the microgrid concept demands a proper definition of the regulations governing its integration in distribution systems. In order to define such regulations, an accurate evaluation of the benefits that microgrids will bring to customers and utilities is needed. Therefore, there is a need for careful consideration of microgrids in the assessment, operation, planning and design aspects of ADNs. Moreover, SG offers new digital technologies to be combined with the existing utility grids to substantially improve the overall efficiency and reliability of the network. Advanced network monitoring, two ways communication acts and intelligent control methods represent the main features of SG. Thus it is required to properly apply these features to facilitate a seamless integration of DG units in ADNs considering microgrids. Motivated by voltage and reactive power control issues in ADNs, the concept of microgrids, and SG technologies, three consequent stages are presented in this thesis. In the first stage, the issues of voltage and reactive power control in traditional distribution systems are addressed and assessed in order to shed the light on the potential conflicts that are expected with high DG penetration. A simple, yet efficient and generic three phase power flow algorithm is developed to facilitate the assessment. The results show that utility voltage and reactive power control devices can no longer use conventional control techniques and there is a necessity for the evolution of voltage and reactive power control from traditional to smart control schemes. Furthermore, a probabilistic approach for assessing the impacts of voltage and reactive power constraints on the probability of successful operation of islanded microgrids and its impacts on the anticipated improvement in the system and customer reliability indices is developed. The assessment approach takes into account: 1) the stochastic nature of DG units and loads variability, 2) the special philosophy of operation for islanded microgrids, 3) the different configurations of microgrids in ADNs, and 4) the microgrids dynamic stability. The results show that voltage and reactive power aspects cannot be excluded from the assessment of islanded microgrids successful operation. The assessment studies described in the first stage should be followed by new voltage and reactive power planning approaches that take into account the characteristics of ADNs and the successful operation of islanded microgrids. Feeders shunt capacitors are the main reactive power sources in distribution networks that are typically planned to be located or reallocated in order to provide voltage support and reduce the energy losses. Thus, in the second stage, the problem of capacitor planning in distribution network has been reformulated to consider microgrids in islanded mode. The genetic algorithm technique (GA) is utilized to solve the new formulation. The simulation results show that the new formulation for the problem of capacitor planning will facilitate a successful implementation of ADNs considering islanded microgrids. In the third stage, the SG technologies are applied to construct a two ways communication-based distributed control that has the capability to provide proper voltage and reactive power control in ADNs. The proposed control scheme is defined according to the concept of multiagent technology, where each voltage and reactive power control device or DG unit is considered as a control agent. An intelligent Belief-Desire-Intention (BDI) model is proposed for the interior structure of each control agent. The Foundation for Intelligent Physical Agents (FIPA) performatives are used as communication acts between the control agents. First, the distributed control scheme is applied for voltage regulation in distribution feeders at which load tap changer (LTC) or step voltage regulators are installed at the begging of the feeder. In this case, the proposed control aims to modify the local estimation of the line drop compensation circuit via communication. Second, the control scheme is modified to take into consideration the case of multiple feeders having a substation LTC and unbalanced load diversity. To verify the effectiveness and robustness of the proposed control structure, a multiagent simulation model is proposed. The simulation results show that distributed control structure has the capability to mitigate the interference between DG units and utility voltage and reactive power control devices.

In this paper, optimal control problems for semilinear parabolic equations with distributed and boundary controls are considered. Pointwise constraints on the control and on the state are given. Main emphasis is laid on the discussion of second order sufficient optimality conditions. Sufficiency for local optimality is verified under different assumptions imposed on the dimension of the domain and on the smoothness of the given data.

We consider a class of control problems governed by a linear parabolic initial-boundary value problem with linear-quadratic objective and pointwise constraints on the control. The control system contains different types of perturbations. They appear in the linear part of the objective functional, in the right hand side of the equation, in its boundary condition, and in the initial value. Making use of parabolic regularity in the whole scale of $L^p$ the known Lipschitz stability in the $L^2$-norm is improved to the supremum-norm.

<p>This dissertation presents a novel distributed optimal control (DOC) problem formulation that is applicable to multiscale dynamical systems comprised of numerous interacting systems, or agents, that together give rise to coherent macroscopic behaviors, or coarse dynamics, that can be modeled by partial differential equations (PDEs) on larger spatial and time scales. The DOC methodology seeks to obtain optimal agent state and control trajectories by representing the system's performance as an integral cost function of the macroscopic state, which is optimized subject to the agents' dynamics. The macroscopic state is identified as a time-varying probability density function to which the states of the individual agents can be mapped via a restriction operator. Optimality conditions for the DOC problem are derived analytically, and the optimal trajectories of the macroscopic state and control are computed using direct and indirect optimization algorithms. Feedback microscopic control laws are then derived from the optimal macroscopic description using a potential function approach.</p><p>The DOC approach is demonstrated numerically through benchmark multi-agent trajectory optimization problems, where large systems of agents were given the objectives of traveling to goal state distributions, avoiding obstacles, maintaining formations, and minimizing energy consumption through control. Comparisons are provided between the direct and indirect optimization techniques, as well as existing methods from the literature, and a computational complexity analysis is presented. The methodology is also applied to a track coverage optimization problem for the control of distributed networks of mobile omnidirectional sensors, where the sensors move to maximize the probability of track detection of a known distribution of mobile targets traversing a region of interest (ROI). Through extensive simulations, DOC is shown to outperform several existing sensor deployment and control strategies. Furthermore, the computation required by the DOC algorithm is proven to be far reduced compared to that of classical, direct optimal control algorithms.</p> / Dissertation

Driven by economic, technical and environmental factors, the energy sector is currently undergoing a profound paradigm shift towards a smarter grid setup. Increased intake of Distributed and Renewable Generation (DG) units is one of the Smart Grid (SG) pillars that will lead to numerous advantages among which lower electricity losses, increased reliability and reduced greenhouse gas emissions are the most salient. The increase of DG units’ penetration will cause changes to the characteristics of distribution networks from being passive with unidirectional power flow towards Active Distribution Networks (ADNs) with multi-direction power flow. However, such changes in the current distribution systems structure and design will halt the seamless DG integration due to various technical issues that may arise. Voltage and reactive power control is one of the most significant issues that limit increasing DG penetration into distribution systems. On the other hand, the term microgrid has been created to be the building block of ADNs. A microgrid should be able to operate in two modes of operation, grid-connected or islanded. The successful implementation of the microgrid concept demands a proper definition of the regulations governing its integration in distribution systems. In order to define such regulations, an accurate evaluation of the benefits that microgrids will bring to customers and utilities is needed. Therefore, there is a need for careful consideration of microgrids in the assessment, operation, planning and design aspects of ADNs. Moreover, SG offers new digital technologies to be combined with the existing utility grids to substantially improve the overall efficiency and reliability of the network. Advanced network monitoring, two ways communication acts and intelligent control methods represent the main features of SG. Thus it is required to properly apply these features to facilitate a seamless integration of DG units in ADNs considering microgrids. Motivated by voltage and reactive power control issues in ADNs, the concept of microgrids, and SG technologies, three consequent stages are presented in this thesis. In the first stage, the issues of voltage and reactive power control in traditional distribution systems are addressed and assessed in order to shed the light on the potential conflicts that are expected with high DG penetration. A simple, yet efficient and generic three phase power flow algorithm is developed to facilitate the assessment. The results show that utility voltage and reactive power control devices can no longer use conventional control techniques and there is a necessity for the evolution of voltage and reactive power control from traditional to smart control schemes. Furthermore, a probabilistic approach for assessing the impacts of voltage and reactive power constraints on the probability of successful operation of islanded microgrids and its impacts on the anticipated improvement in the system and customer reliability indices is developed. The assessment approach takes into account: 1) the stochastic nature of DG units and loads variability, 2) the special philosophy of operation for islanded microgrids, 3) the different configurations of microgrids in ADNs, and 4) the microgrids dynamic stability. The results show that voltage and reactive power aspects cannot be excluded from the assessment of islanded microgrids successful operation. The assessment studies described in the first stage should be followed by new voltage and reactive power planning approaches that take into account the characteristics of ADNs and the successful operation of islanded microgrids. Feeders shunt capacitors are the main reactive power sources in distribution networks that are typically planned to be located or reallocated in order to provide voltage support and reduce the energy losses. Thus, in the second stage, the problem of capacitor planning in distribution network has been reformulated to consider microgrids in islanded mode. The genetic algorithm technique (GA) is utilized to solve the new formulation. The simulation results show that the new formulation for the problem of capacitor planning will facilitate a successful implementation of ADNs considering islanded microgrids. In the third stage, the SG technologies are applied to construct a two ways communication-based distributed control that has the capability to provide proper voltage and reactive power control in ADNs. The proposed control scheme is defined according to the concept of multiagent technology, where each voltage and reactive power control device or DG unit is considered as a control agent. An intelligent Belief-Desire-Intention (BDI) model is proposed for the interior structure of each control agent. The Foundation for Intelligent Physical Agents (FIPA) performatives are used as communication acts between the control agents. First, the distributed control scheme is applied for voltage regulation in distribution feeders at which load tap changer (LTC) or step voltage regulators are installed at the begging of the feeder. In this case, the proposed control aims to modify the local estimation of the line drop compensation circuit via communication. Second, the control scheme is modified to take into consideration the case of multiple feeders having a substation LTC and unbalanced load diversity. To verify the effectiveness and robustness of the proposed control structure, a multiagent simulation model is proposed. The simulation results show that distributed control structure has the capability to mitigate the interference between DG units and utility voltage and reactive power control devices.

[Truncated abstract] This thesis analyses the problem of Intelligent Control for large industrial plants and suggests a hierarchical, distributed, object-oriented architecture for Intelligent Control. The architecture is called MLIAC (Multi Level Intelligent Adaptive Control) Architecture. The MLIAC architecture is inspired by biological control systems (which are flexible, and are capable of adapting to unstructured environments with ease) and the success of the distributed architecture SCADA (Supervisory Control and Data Acquisition) Systems. The MLIAC Architecture structures the decision and control mechanism for the real-time properties namely safety, liveliness, and timeliness . . . In addition, three case studies have been reported. The case studies cover the control of a Flexible Manufacturing System and the Mine Products Quality Control. The results show that MLIAC Knowledge Representation model meets the requirements of the Roth-Hayes benchmark regarding Knowledge Representation. The decisions taken are logically tractable. The software architecture is effective and easily implemented. The actual performance has been found to depend upon a number of factors discussed in this thesis. For the specification and design of Potline MLIAC software, a CASE package ("Software Through Pictures") has been used. The Potline MLIAC software has been developed using C⁄C++, SQL, 4 GL and RDBMS based on a Client-Server model. For computer simulation the Potline MLIAC software has been integrated with the MATLAB⁄SIMULINK package.