• Energy Research

The evolution of distribution systems (DS) towards the smart-grid concept posses new challenges, triggered by the integration of distributed generation (DG) and the installation of new devices. These challenges raise the need to reconsider the traditional network operation during the planning stage, enabling the DS to be flexible to operate under different network configuration scenarios. In this paper we propose a DS planning methodology for the connection of support feeders in radial networks, explicitly considering reconfiguration options with open-and closed-loop operation. To this end, we propose an efficiency evaluation, based on Data Envelopment Analysis, to assess candidate feeders in terms of expansion costs, energy losses, and lines' chargeability, under a range of demand scenarios that include GD penetration. Additionally, we have developed a method to identify the main feeder in a radial system, obtaining a simplified version of the DS, better suited for analysis. Simulation results on a real urban DS show the effectiveness of the method to identify the best nodes in a main feeder to connect support feeders, further indicating how to divide the network into operation areas for an improved network performance.

The modernization of the power system introduces technologies that may improve the system's efficiency by enhancing the capabilities of users. Despite their potential benefits, such technologies can have a negative impact. This subject has widely analyzed, mostly considering for-profit electric utilities. However, the literature has a gap regarding the impact of new technologies on non-profit utilities. In this work, we quantify the price of anarchy of non-profit utilities, that is, the cost caused by lack of coordination of users. We find that users, in the worst case, can consume up to twice the optimal demand, obtaining a small fraction of the optimal surplus. For this reason, we leverage the theory of mechanism design to design an incentive scheme that reduces the inefficiencies of the system, which preserves the privacy of users. We illustrate with simulations the efficiency loss of the system and show two instances of incentive mechanism that satisfy either budget balance and budget deficit. 17 pages, 3 figures, accepted in the International Journal of Electrical Power and Energy Systems

Demand response systems assume an electricity retail-market with strategic electricity consuming agents. The goal in these systems is to design load shaping mechanisms to achieve efficiency of resources and customer satisfaction. Recent research efforts have studied the impact of integrity attacks in simplified versions of the demand response problem, where neither the load consuming agents nor the adversary are strategic.In this paper, we study the impact of integrity attacks considering strategic players (a social planner or a consumer) and a strategic attacker. We identify two types of attackers: (1) a malicious attacker who wants to damage the equipment in the power grid by producing sudden overloads, and (2) a selfish attacker that wants to defraud the system by compromising and then manipulating control (load shaping) signals. We then explore the resiliency of two different demand response systems to these fraudsters and malicious attackers. Our results provide guidelines for system operators deciding which type of demand-response system they want to implement, how to secure them, and directions for detecting these attacks.

Parabolic-trough solar collector fields are large-scale systems, so the application of centralized optimizationbased control methods to these systems is often not suitable for real-time control. As such, this paper formulates a novel coalitional control approach as an appropriate alternative to the centralized scheme. The key idea is to split the overall solar collector field into smaller subsystems, each of them governed by a local controller. Then, controllers are clustered into coalitions to solve a local optimization-based problem related to the corresponding subset of subsystems, so that an approximate solution of the original centralized problem can be obtained in a decentralized fashion. However, the operational constraints of the solar collector field couple the optimization problems of the multiple coalitions, thus limiting the ability to solve them in a fully decentralized manner. To overcome this issue, a novel population-dynamics-assisted resource allocation strategy is proposed as a mechanism to decouple the local optimization problems of the multiple coalitions. The proposed coalitional methodology allows to solve the multiple local subproblems in parallel, hence reducing the overall computational burden, while guaranteeing the satisfaction of the operational constraints and without significantly compromising the overall performance. The effectiveness of proposed approach is shown through numerical simulations of a 10- and 100-loop version of the ACUREX solar collector field of Plataforma Solar de Almería, Spain. Peer Reviewed

Abstract There exists an increasing interest in networked systems due to the wide number of applications in distributed and decentralized control of large scale systems, such as smart grids. We address the problem of distributed frequency synchronization of several isolated microgrids, each one described by a linear-time continuous system, composed by different types of generators, whose outputs are measured and sent through a communication infrastructure. We assume that each microgrid possesses renewable resources with storage capabilities that helps to improve stability of the network when small damping ratio is considered. Thus, using the smart grid communication infrastructure and the data flow through the network, we propose a cooperative control strategy based on the consensus algorithm that simultaneously manages the turbine governor input and the amount of energy that the storage devices have to absorb/inject from/into the grid. Nevertheless, physical constraints need to be included, which can be modeled using saturation non-linearities, and conditions to assure synchronization even with saturation are obtained based on multi-agent systems. Additionally, we consider that sensor measurements are sampled and we extend the results of frequency synchronization with saturation to the case of control discretization and sampling-period independence is demonstrated using passivity concepts.

Abstract This work proposes a distributed strategy to solve a joint active and reactive power dispatch in isolated microgrids. The information shared among neighboring local controllers allows the algorithm to achieve the optimal dispatch in a secondary layer, which is the reference for primary controllers in each generator. The method based on population dynamics facilitates the implementation in systems with high penetration of distributed generation and a basic communication network. The hierarchical strategy is evaluated in a co-simulation platform to emulate real conditions in a study case of a microgrid with a management control scheme programmed with the distributed optimization technique. Results show that the proposed technique provides an optimal dispatch in distinct scenarios with the expected reduction of losses, improvement in voltage profiles, and minimization of the generation costs.

Abstract Distributed energy resources (DERs) coordination problems and load shedding in power systems can be modeled as a distributed resource allocation problem with physical constraints. The dynamic resource allocation problem can be approached using nonlinear methods based on population dynamics. This paper presents an optimization model to minimize the load curtailments needed to restore the equilibrium of the operating point when the system is in a fault condition (e.g., loss of generation). A mathematical model of the proposed strategy for the dispatch generation and an optimal load shedding algorithm are shown. The developed methodology minimizes the load cuts depending on the load relevance of each node of the system, and carrying out the power distribution of the generators under the new demand power condition using the replicator dynamics or the local replicator equation. This model can be used for the operation planning of electrical power systems with DERs. In order to illustrate our methodology, some simulations are performed using the IEEE 34 node test feeder in OpenDSS.

Planning of protection systems has been a significant task in order to achieve an efficient behavior of distribution systems. Feeders that offer high robustness and reliability are essential to ensure continuous energy delivering to all customer loads. Since distributed generation (DG) has increased its penetration in distribution systems, it has become necessary to place protective devices (such as reclosers) in order to allow DG islanded operation, which decreases the energy not supplied. This paper addresses efficient placement of normally closed reclosers (NCRs). A multi-objective optimization is defined to reduce SAIDI, SAIFI, and system costs. This approach yields optimal planning of NCRs by applying the non-dominated sorting differential evolution algorithm (NSDE). The NSDE is implemented in Matlab, while the power system is modeled in DigSILENT in order to employ a co-simulation environment. Simulations are developed on a real test feeder for two cases: i) without DG; and ii) with 6 MW penetration of distributed sources.

We illustrate the potential of applying population games in two key related problems in microgrids management: 1) economic dispatch of active and reactive power; and 2) demand response. For the dynamic economic dispatch problem, we present a hierarchical microgrid energy management algorithm able to dispatch active and reactive power dynamically. In the second case, we use an opinion dynamics model, including the market in which the network agents interact. Opinion dynamics considers individuals who shape their beliefs based on information they receive from a subset of the society and offers tools to analyze the outcome of collective decision processes, which apparently can be considered arbitrary. We propose an opinion dynamics model including some desired characteristics, such as prominent agents and environmental incentives.