Joint Frequency Regulation and Economic Dispatch Using Limited Communication

We study the performance of a decentralized integral control scheme for joint power grid frequency regulation and economic dispatch. We show that by properly designing the controller gains, after a power flow perturbation, the control achieves near-optimal economic dispatch while recovering the nominal frequency, without requiring any communication. We quantify the gap between the controllable power generation cost under the decentralized control scheme and the optimal cost, based on the DC power flow model. Moreover, we study the tradeoff between the cost and the convergence time, by adjusting parameters of the control scheme. Communication between generators reduces the convergence time. We identify key communication links whose failures have more significant impacts on the performance of a distributed power grid control scheme that requires information exchange between neighbors

Analyzing Linear Communication Networks using the Ribosome Flow Model

The Ribosome Flow Model (RFM) describes the unidirectional movement of interacting particles along a one-dimensional chain of sites. As a site becomes fuller, the effective entry rate into this site decreases. The RFM has been used to model and analyze mRNA translation, a biological process in which ribosomes (the particles) move along the mRNA molecule (the chain), and decode the genetic information into proteins. Here we propose the RFM as an analytical framework for modeling and analyzing linear communication networks. In this context, the moving particles are data-packets, the chain of sites is a one dimensional set of ordered buffers, and the decreasing entry rate to a fuller buffer represents a kind of decentralized backpressure flow control. For an RFM with homogeneous link capacities, we provide closed-form expressions for important network metrics including the throughput and end-to-end delay. We use these results to analyze the hop length and the transmission probability (in a contention access mode) that minimize the end-to-end delay in a multihop linear network, and provide closed-form expressions for the optimal parameter values

Assessment of novel distributed control techniques to address network constraints with demand side management

The development of sustainable generation, a reliable electricity supply and affordable tariffs are the primary requirements to address the uncertainties in different future energy scenarios. Due to the predicted increase in Distributed Generation (DG) and load profile changes in future scenarios, there are significant operational and planning challenges facing netwrok operators. These changes in the power system distribution network require a new Active Network Management (ANM) control system to manage distribution constraint issues such as thermal rating, voltage, and fault levels. The future smart grid focuses on harnessing the control potential from demand side via bidirectional power flow, transparent information communication, and contractual customer participation. Demand Side Management (DSM) is considered as one of the effective solutions to defer network capacity reinforcement, increase energy efficiency, facilitate renewable access, and implement low carbon energy strategy. From the Distribution Network Operator's (DNO) perspective, the control opportunity from Demand Response (DR) and Decentralized Energy Resource (DER) contributes on capacity investment reduction, energy efficiency, and enable low carbon technologies. This thesis develops a new decentralized control system for dealing effectively with the constraint issues in the Medium Voltage (MV) distribution network. In the decentralized control system, two novel control approaches are proposed to autonomously relieve the network thermal constraint via DNO's direct control of the real power in network components during the operation period. The first approach, Demand Response for Power Flow Management (DR-PFM), implements the DSM peak clipping control of Active Demand (AD), whilst the second approach, Hybrid Control for Power Flow Management (HC-PFM), implements the hybrid control of both AD and DER. The novelty of these two new control algorithms consists in the application of a Constraint Satisfaction Problem (CSP) based programming model on decision making of the real power curtailment to relieve the network thermal overload. In the Constraint Programming (CP) model, three constraints are identified: a preference constraint, and a network constraint. The control approaches effectively solve the above constraint problem in the CSP model within 5 seconds' time response. The control performance is influenced by the pre-determined variable, domain and constraint settings. These novel control approaches take advantages on flexible control, fast response and demand participation enabling in the future smart grid.The development of sustainable generation, a reliable electricity supply and affordable tariffs are the primary requirements to address the uncertainties in different future energy scenarios. Due to the predicted increase in Distributed Generation (DG) and load profile changes in future scenarios, there are significant operational and planning challenges facing netwrok operators. These changes in the power system distribution network require a new Active Network Management (ANM) control system to manage distribution constraint issues such as thermal rating, voltage, and fault levels. The future smart grid focuses on harnessing the control potential from demand side via bidirectional power flow, transparent information communication, and contractual customer participation. Demand Side Management (DSM) is considered as one of the effective solutions to defer network capacity reinforcement, increase energy efficiency, facilitate renewable access, and implement low carbon energy strategy. From the Distribution Network Operator's (DNO) perspective, the control opportunity from Demand Response (DR) and Decentralized Energy Resource (DER) contributes on capacity investment reduction, energy efficiency, and enable low carbon technologies. This thesis develops a new decentralized control system for dealing effectively with the constraint issues in the Medium Voltage (MV) distribution network. In the decentralized control system, two novel control approaches are proposed to autonomously relieve the network thermal constraint via DNO's direct control of the real power in network components during the operation period. The first approach, Demand Response for Power Flow Management (DR-PFM), implements the DSM peak clipping control of Active Demand (AD), whilst the second approach, Hybrid Control for Power Flow Management (HC-PFM), implements the hybrid control of both AD and DER. The novelty of these two new control algorithms consists in the application of a Constraint Satisfaction Problem (CSP) based programming model on decision making of the real power curtailment to relieve the network thermal overload. In the Constraint Programming (CP) model, three constraints are identified: a preference constraint, and a network constraint. The control approaches effectively solve the above constraint problem in the CSP model within 5 seconds' time response. The control performance is influenced by the pre-determined variable, domain and constraint settings. These novel control approaches take advantages on flexible control, fast response and demand participation enabling in the future smart grid

Mostly-static decentralized information flow control

Thesis (Ph.D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1999.Includes bibliographical references (p. 169-174) and index.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.The growing use of mobile code in downloaded programs such as applets and servlets has increased interest in robust mechanisms for ensuring privacy and secrecy. Common security mechanisms such as sand boxing and access control are either too restrictive or too weak -- they prevent applications from sharing data usefully, or allow private information to leak. For example, security mechanisms in Java prevent many useful applications while still permitting Trojan horse applets to leak private information. This thesis describes the decentralized label model, a new model of information flow control that protects private data while allowing applications to share data. Unlike previous approaches to privacy protection based on information flow, this label model is decentralized: it allows cooperative computation by mutually distrusting principals, without mediation by highly trusted agents. Cooperative computation is possible because individual principals can declassify their own data without infringing on other principals' privacy. The decentralized label model permits programs using it to be checked statically, which is important for the precise detection of information leaks. This thesis also presents the new language J flow, an extension to the Java programming language that incorporates the decentralized label model and permits static checking of information flows within programs. Variable declarations in J flow programs are annotated with labels that allow the static checker to check programs for information leaks efficiently, in a manner similar to type checking. Often, these labels can be inferred automatically, so annotating programs is not onerous. Dynamic checks also may be used safely when static checks are insufficiently powerful. A compiler has been implemented for the J flow language. Because most checking is performed statically at compile time, the compiler generates code with few additional dynamic tests, improving performance.by Andrew C. Myers.Ph.D

Decentralized control design approaches for formation control of unmanned aerial vehicles

The leader follower type formation of Unmanned Aerial Vehicles usually demands decentralized yet co-operative control among the vehicles. The decentralized control approach is superior to centralized control in view of lesser involvement of delay, minimal information sharing requirement, reduced computational effort for controller design etc. The dynamic model of leader follower formation with an information structure constraint, in which each vehicle except the leader have the information of all the states of vehicle in front of it. The formation is treated as an interconnected system with overlapping control gains in the sense an UAV share information only with its neighbouring ones.In this thesis, two approaches are used: (i) Inclusion principle (ii) Graph theory based approach for designing control gains. In the inclusion principle approach, control gain is designed separately for each disjoint subsystem in the expanded space. The static state feedback control law and linear matrix inequalities tool boxes are used for designing the controllers for each subsystem. Finally decentralized controllers are contracted back so as to be applied to the original system. In the graph theory approach, an overlapping information flow structure is constructed that determines the outputs of the system available in constructing any input signal of the system. The Graph theory is used to transform the overlapping interconnected system to decentralized one. The static state feedback type controller is used and a DK iterative algorithm is used to find out control gain. Then, a comparison between these two decentralized approaches is reported in the thesis so as to obtain the relative merits and demerits. There is delay in information flow form leader to follower in the formation so frequency domain stability analysis is done for time delay system. Frequency sweeping test is conducted for getting maximum tolerable communication delay between any two UAVs