Carlos E. Murillo-Sánchez

Bio: Carlos E. Murillo-Sánchez is an academic researcher from National University of Colombia. The author has contributed to research in topics: Electric power system & Power system simulation. The author has an hindex of 14, co-authored 25 publications receiving 5751 citations. Previous affiliations of Carlos E. Murillo-Sánchez include National University of Colombia at Manizales & Cornell University.

Alternate mechanisms for integrating renewable sources of energy into electricity markets

Abstract: The objective of this paper is to contrast the effect of demand side versus supply side policies aimed at operating a secured system, while maintaining the sustainability of the system by analyzing: 1) the role that load following costs can have in counteracting the impact of unpredictable Renewable Energy Sources (RES) on system operation and 2) The optimal management of Deferrable (or controllable) demand, given the inter-temporal constraints they face, to be coupled with RES. This will extend the concept of controllable loads to include thermal storage, and in particular, the use of ice batteries to replace standard forms of air-conditioning (AC). The analysis is done by simulation in Matpower ([1]) for a Multi-period, stochastic, security constrained AC optimal power flow. This is a continuation of work in stochastic AC-OPF modeling ([2]). A set of constraints reflecting specific ramping costs for all generation is included. The expected amount of Load Not Served (LNS) is also endogenously solved. Wind is modeled as the RES, with a characterization similar to historical data from New York and New England. The network model is a reduction of the Northeastern Power Coordinating Council (NPCC, [3]), modified to focus on New York and New England. Since the adoption of renewables leads to higher cost of capacity for conventional generation, new investments need to be made to be able to manage the load in more economical ways. A load-following ramping reserve product is proposed as an example of a mechanism for participants to signal their technical characteristics and constraints. Investments in storage and controllable load management can also improve the system efficiency. Our results illustrate the importance of market designs that provide participants with the correct economic incentives and signaling mechanisms.

Thermal Unit Commitment with a Nonlinear AC Power Flow Network Model

Abstract: This chapter presents a formulation of the thermal unit commitment problem that includes nonlinear power flow constraints, thus allowing a more accurate representation of the network than is possible with DC flow models. This also permits potential VAr production to be used as a criterion for commitment of otherwise expensive generators in strategic locations. We use a Lagrangian relaxation framework with duplicated variables for each active and reactive source, permitting the exploitation of the separable structure of the dual cost. Results for medium-sized systems in a parallel processing environment are available.

Parallel processing implementation of the unit commitment problem with full AC power flow constraints

Abstract: The authors describe a parallel implementation of the Lagrangian Relaxation Algorithm with variable duplication for the thermal unit commitment problem. The formulation was previously reported by the authors and allows inclusion of the full nonlinear AC network power flow model, which permits addressing voltage limits, as well as more realistic branch flow limits than is possible with a linear DC flow model. Thus, potential VAr production can be used as another criterion for commitment of otherwise expensive generators in strategic locations. The algorithm is highly parallelizable, and the authors have taken advantage of this in a version currently being developed for the Cornell Theory Center's Velocity AC3 NT cluster.

Kirchhoff vs. competitive electricity markets: a few examples

Abstract: Electric power is often regarded as a homogeneous commodity due to the ubiquity of the transmission grid. This paper, however, presents a collection of cases in which the physical laws governing network flows can have anomalous and unexpected market implications. For example, reactive power requirements can affect optimal unit commitment and impact real power prices in otherwise competitive markets. Network topology and constraint interactions can result in other unwelcome market phenomena, such as large price differentials within a congestion zone, nodal prices well above the highest offer and "cascading market power".

MATPOWER: Steady-State Operations, Planning, and Analysis Tools for Power Systems Research and Education

Abstract: MATPOWER is an open-source Matlab-based power system simulation package that provides a high-level set of power flow, optimal power flow (OPF), and other tools targeted toward researchers, educators, and students. The OPF architecture is designed to be extensible, making it easy to add user-defined variables, costs, and constraints to the standard OPF problem. This paper presents the details of the network modeling and problem formulations used by MATPOWER, including its extensible OPF architecture. This structure is used internally to implement several extensions to the standard OPF problem, including piece-wise linear cost functions, dispatchable loads, generator capability curves, and branch angle difference limits. Simulation results are presented for a number of test cases comparing the performance of several available OPF solvers and demonstrating MATPOWER's ability to solve large-scale AC and DC OPF problems.

Attack Detection and Identification in Cyber-Physical Systems

Abstract: Cyber-physical systems are ubiquitous in power systems, transportation networks, industrial control processes, and critical infrastructures. These systems need to operate reliably in the face of unforeseen failures and external malicious attacks. In this paper: (i) we propose a mathematical framework for cyber-physical systems, attacks, and monitors; (ii) we characterize fundamental monitoring limitations from system-theoretic and graph-theoretic perspectives; and (ii) we design centralized and distributed attack detection and identification monitors. Finally, we validate our findings through compelling examples.

Zero Duality Gap in Optimal Power Flow Problem

Abstract: The optimal power flow (OPF) problem is nonconvex and generally hard to solve. In this paper, we propose a semidefinite programming (SDP) optimization, which is the dual of an equivalent form of the OPF problem. A global optimum solution to the OPF problem can be retrieved from a solution of this convex dual problem whenever the duality gap is zero. A necessary and sufficient condition is provided in this paper to guarantee the existence of no duality gap for the OPF problem. This condition is satisfied by the standard IEEE benchmark systems with 14, 30, 57, 118, and 300 buses as well as several randomly generated systems. Since this condition is hard to study, a sufficient zero-duality-gap condition is also derived. This sufficient condition holds for IEEE systems after small resistance (10-5 per unit) is added to every transformer that originally assumes zero resistance. We investigate this sufficient condition and justify that it holds widely in practice. The main underlying reason for the successful convexification of the OPF problem can be traced back to the modeling of transformers and transmission lines as well as the non-negativity of physical quantities such as resistance and inductance.

Attack Detection and Identification in Cyber-Physical Systems -- Part I: Models and Fundamental Limitations

Abstract: Cyber-physical systems integrate computation, communication, and physical capabilities to interact with the physical world and humans. Besides failures of components, cyber-physical systems are prone to malignant attacks, and specific analysis tools as well as monitoring mechanisms need to be developed to enforce system security and reliability. This paper proposes a unified framework to analyze the resilience of cyber-physical systems against attacks cast by an omniscient adversary. We model cyber-physical systems as linear descriptor systems, and attacks as exogenous unknown inputs. Despite its simplicity, our model captures various real-world cyber-physical systems, and it includes and generalizes many prototypical attacks, including stealth, (dynamic) false-data injection and replay attacks. First, we characterize fundamental limitations of static, dynamic, and active monitors for attack detection and identification. Second, we provide constructive algebraic conditions to cast undetectable and unidentifiable attacks. Third, by using the system interconnection structure, we describe graph-theoretic conditions for the existence of undetectable and unidentifiable attacks. Finally, we validate our findings through some illustrative examples with different cyber-physical systems, such as a municipal water supply network and two electrical power grids.

Branch Flow Model: Relaxations and Convexification—Part II

Abstract: We propose a branch flow model for the analysis and optimization of mesh as well as radial networks. The model leads to a new approach to solving optimal power flow (OPF) that consists of two relaxation steps. The first step eliminates the voltage and current angles and the second step approximates the resulting problem by a conic program that can be solved efficiently. For radial networks, we prove that both relaxation steps are always exact, provided there are no upper bounds on loads. For mesh networks, the conic relaxation is always exact but the angle relaxation may not be exact, and we provide a simple way to determine if a relaxed solution is globally optimal. We propose convexification of mesh networks using phase shifters so that OPF for the convexified network can always be solved efficiently for an optimal solution. We prove that convexification requires phase shifters only outside a spanning tree of the network and their placement depends only on network topology, not on power flows, generation, loads, or operating constraints. Part I introduces our branch flow model, explains the two relaxation steps, and proves the conditions for exact relaxation. Part II describes convexification of mesh networks, and presents simulation results.