Alejandro D. Domínguez-García

Real-time scheduling of deferrable electric loads

We consider a collection of distributed energy resources [DERs] such as electric vehicles and thermostatically controlled loads. These resources are flexible: they require delivery of a certain total energy over a specified service interval. This flexibility can facilitate the integration of renewable generation by absorbing variability, and reducing the reserve capacity and reserve energy requirements. We first model the energy needs of these resources as tasks, parameterized by arrival time, departure time, energy requirement, and maximum allowable servicing power. We consider the problem of servicing these resources by allocating available power using real-time scheduling policies. The available generation consists of a mix of renewable energy [from utility-scale wind-farms or distributed rooftop photovoltaics], and load-following reserves. Reserve capacity is purchased in advance, but reserve energy use must be scheduled in real-time to meet the energy requirements of the resources. We show that there does not exist a causal optimal scheduling policy that respects servicing power constraints. We then present three heuristic causal scheduling policies: Earliest Deadline First [EDF], Least Laxity First [LLF], and Receding Horizon Control [RHC]. We show that EDF is optimal in the absence of power constraints. We explore, via simulation studies, the performance of these three scheduling policies in the metrics of required reserve energy and reserve capacity.

A Two-Stage Distributed Architecture for Voltage Control in Power Distribution Systems

In this paper, we propose an architecture for voltage regulation in distribution networks that relies on controlling reactive power injections provided by distributed energy resources (DERs). A local controller on each bus of the network monitors the bus voltage and, whenever there is a voltage violation, it uses locally available information to estimate the amount of reactive power that needs to be injected into the bus in order to correct the violation. If the DERs connected to the bus can collectively provide the reactive power estimated by the local controller, they are instructed to do so. Otherwise, the local controller initiates a request for additional reactive power support from other controllers at neighboring buses through a distributed algorithm that relies on a local exchange of information among neighboring controllers. We show that the proposed architecture helps prevent voltage violations and shapes the voltage profile in radial distribution networks, even in the presence of considerable penetration of variable generation and loads. We present several case studies involving 8-, 13-, and 123-bus distribution systems to illustrate the operation of the architecture.

Decentralized optimal dispatch of distributed energy resources

In this paper, we address the problem of optimally dispatching a set of distributed energy resources (DERs) without relying on a centralized decision maker. We consider a scenario where each DER can provide a certain resource (e.g., active or reactive power) at some cost (namely, quadratic in the amount of resource), with the additional constraint that the amount of resource that each DER provides is upper and lower bounded by its capacity limits. We propose a low-complexity iterative algorithm for DER optimal dispatch that relies, at each iteration, on simple computations using local information acquired through exchange of information with neighboring DERs. We show convergence of the proposed algorithm to the (unique) optimal solution of the DER dispatch problem. We also describe a wireless testbed we developed for testing the performance of the algorithms.

An Optimal and Distributed Method for Voltage Regulation in Power Distribution Systems

This paper addresses the problem of voltage regulation in power distribution networks with deep-penetration of distributed energy resources, e.g., renewable-based generation, and storage-capable loads such as plug-in hybrid electric vehicles. We cast the problem as an optimization program, where the objective is to minimize the losses in the network subject to constraints on bus voltage magnitudes, limits on active and reactive power injections, transmission line thermal limits and losses. We provide sufficient conditions under which the optimization problem can be solved via its convex relaxation. Using data from existing networks, we show that these sufficient conditions are expected to be satisfied by most networks. We also provide an efficient distributed algorithm to solve the problem. The algorithm adheres to a communication topology described by a graph that is the same as the graph that describes the electrical network topology. We illustrate the operation of the algorithm, including its robustness against communication link failures, through several case studies involving 5-, 34-, and 123-bus power distribution systems.

Coordination and Control of Distributed Energy Resources for Provision of Ancillary Services

This paper discusses the utilization of distributed energy resources on the distribution side of the power grid to provide a number of ancillary services. While the individual capability of these resources to provide grid support might be very small, their presence in large numbers in many distribution networks implies that, under proper control, they can collectively become an asset for providing ancillary services. An example is the power electronics interface of a photovoltaic array mounted in a residential building roof. While its primary function is to control active power flow, when properly controlled, it can also be used to provide reactive power. This paper develops and analyzes distributed control strategies to enable the utilization of these distributed resources for provision of grid support services. We provide a careful analysis of the applicability capabilities and limitations of each of these strategies. Several simulation examples are provided to illustrate the proposed approaches.

A Unified Approach to Reliability Assessment of Multiphase DC–DC Converters in Photovoltaic Energy Conversion Systems

A systematic framework for reliability assessment and fault-tolerant design of multiphase dc-dc converters deployed in photovoltaic applications is presented. System-level steady-state models allow a detailed specification of component failure rates, and in turn establish the effects of ambient conditions and converter design on reliability. Markov reliability models are derived to estimate the mean time to system failure. Case studies applied to two- and three-phase, 250-W converters demonstrate that topological redundancy does not necessarily translate to improved reliability for all choices of switching frequency and capacitance. Capacitor voltage rating is found to be the dominant factor that affects system reliability.

Distributed algorithms for control of demand response and distributed energy resources

This paper proposes distributed algorithms for control and coordination of loads and distributed energy resources (DERs) in distribution networks. These algorithms are relevant for load curtailment control in demand response programs, and also for coordination of DERs for provision of ancillary services. Both the distributed load-curtailment and DER coordination problems can be cast as distributed resource allocation problems with constraints on resource capacity. We focus on linear iterative algorithms in which each resource j maintains a set of values that is updated to be a weighted linear combination of the resources own previous set of values and the previous sets of values of its neighboring resources. This set of values can be used by each node to determine its own contribution to load curtailment or to resource request.

A Distributed Approach to Maximum Power Point Tracking for Photovoltaic Submodule Differential Power Processing

This paper presents the theory and implementation of a distributed algorithm for controlling differential power processing converters in photovoltaic (PV) applications. This distributed algorithm achieves true maximum power point tracking of series-connected PV submodules by relying only on local voltage measurements and neighbor-to-neighbor communication between the differential power converters. Compared to previous solutions, the proposed algorithm achieves reduced number of perturbations at each step and potentially faster tracking without adding extra hardware; all these features make this algorithm well-suited for long submodule strings. The formulation of the algorithm, discussion of its properties, as well as three case studies are presented. The performance of the distributed tracking algorithm has been verified via experiments, which yielded quantifiable improvements over other techniques that have been implemented in practice. Both simulations and hardware experiments have confirmed the effectiveness of the proposed distributed algorithm.

Markov Reliability Modeling for Induction Motor Drives Under Field-Oriented Control

This paper presents a Markov reliability model of induction motor drives operating under field-oriented control. The model includes faults in the power electronics, machine, speed encoder, and current sensors. The procedure can be extended for more detail, to other machines and to other drive topologies. To develop the model, faults are first identified, and then, a simulation model of the setup is developed and experimentally verified. Faults are injected into the model in sequential levels and the system performance is assessed after each fault. Fault coverage-the probability that the system survives given a fault has occurred-is studied. A complete Markov reliability model is developed to assess the mean time to failure of the system and other reliability factors. This analysis is shown to be simple and useful for assessing the reliability of motor drives and is expected to help in designing fault-tolerance mechanisms for specific drives, where reliability can be evaluated after every design.

Estimation of Photovoltaic System Reliability and Performance Metrics

A framework to integrate reliability and performance analysis of grid-tied photovoltaic (PV) systems is formulated using Markov reward models (MRM). The framework allows the computation of performance metrics such as capacity and energy yield, and reliability metrics such as availability. The paper also provides an analytical method to compute the sensitivity of performance metrics to MRM-parameter variations. The approach to sensitivity analysis is demonstrated to be particularly useful to formulate optimal operational policies, e.g., repair strategies, as the impact of variations in model parameters on system performance can be rapidly evaluated. Case studies demonstrate several applications of the proposed framework, including analysis of residential and large utility-level installations, and emerging distributed inverter architectures.