Carlos E. Murillo-Sanchez

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

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 MATPOWERs ability to solve large-scale AC and DC OPF problems.

On Computational Issues of Market-Based Optimal Power Flow

The deregulated electricity market calls for robust optimal power flow (OPF) tools that can provide a) deterministic convergence; b) accurate computation of nodal prices; c) support of both smooth and nonsmooth costing of a variety of resources and services, such as real energy, reactive energy, voltages support, etc.; d) full active and reactive power flow modeling of large-scale systems; and e) satisfactory worst-case performance that meets the real-time dispatching requirement. Most prior research on OPF has focused on performance issues in the context of regulated systems, without giving much emphasis to requirements a)-c). This paper discusses the computational challenges brought up by the deregulation and attempts to address them through the introduction of new OPF formulations and algorithms. Trust-region- based augmented Lagrangian method (TRALM), step-controlled primal-dual interior point method (SCIPM), and constrained cost variable (CCV) OPF formulation are proposed. The new formulations and algorithms, along with several existing ones, are tested and compared using large-scale power system models.

MATPOWER's extensible optimal power flow architecture

This paper describes the optimal power flow (OPF) architecture implemented in MATPOWER, an open-source Mat-lab power system simulation package. It utilizes an extensible architecture that allows the user to easily add new variables, constraints and costs to the standard OPF problem formulation while preserving the structure needed to use pre-compiled solvers. A software object is used to encapsulate the definition of the problem formulation, manage the corresponding named sets of variables, constraints and costs, and handle all of the tedious index maintenance tasks. The software design has the advantage of minimizing the coupling between variables, constraints and costs, making it possible, for example, to add variables to an existing model without having to explicitly modify existing constraints or costs to accommodate them. The example of adding joint co-optimization of reserves to the OPF, based on fixed zonal reserve requirements, is used to illustrate the capabilities of MATPOWERs extensible OPF architecture.

Secure Planning and Operations of Systems With Stochastic Sources, Energy Storage, and Active Demand

This work presents a stochastic optimization framework for operations and planning of an electricity network as managed by an Independent System Operator. The objective is to maximize the total expected net benefits over the planning horizon, incorporating the costs and benefits of electricity consumption, generation, ancillary services, load-shedding, storage and load-shifting. The overall framework could be characterized as a secure, stochastic, combined unit commitment and AC optimal power flow problem, solving for an optimal state-dependent schedule over a pre-specified time horizon. Uncertainty is modeled to expose the scenarios that are critical for maintaining system security, while properly representing the stochastic cost. The optimal amount of locational reserves needed to cover a credible set of contingencies in each time period is determined, as well as load-following reserves required for ramping between time periods. The models for centrally-dispatched storage and time-flexible demands allow for optimal tradeoffs between arbitraging across time, mitigating uncertainty and covering contingencies. This paper details the proposed problem formulation and outlines potential approaches to solving it. An implementation based on a DC power flow model solves systems of modest size and can be used to demonstrate the value of the proposed stochastic framework.

An advanced security constrained OPF that produces correct market-based pricing

Security constrained optimal power flow programs are important tools for ensuring correct dispatch of supply while respecting the many constraints imposed by the delivery system. In addition to getting the dispatch right, locational prices must be calculated with equal precision in order to infuse market participants with the proper incentives for operation and investment. In this paper we discuss a co-optimization framework in which contingencies, ancillary services, and network constraints are correctly accounted for in determining both dispatch and price.

Alternate mechanisms for integrating renewable sources of energy into electricity markets

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.

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

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 Centers Velocity AC3 NT cluster.

Thermal Unit Commitment with a Nonlinear AC Power Flow Network Model

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.

Scheduling of thermal units with a nonlinear load flow network model

Abstract We describe a formulation of the thermal unit commitment problem that includes AC network constraints, which allows taking into account VAr production as a criterion for generator commitment for the first time. The formulation makes it possible to use the Lagrangian Relaxation technique as a solution algorithm even though the network constraints are not linear. Although the solution method is computationally intensive, the problem exhibits a separation structure and a price coordination schedule that suggest several ways of improving the performance. Preliminary test results are reported.

Experimental results for single period auctions

The objective of the paper is to present experimental results for testing the performance of different auction mechanisms related to the introduction of competitive markets for the generation of electricity. The research is based on the concept of smart markets introduced by Vernon Smith (K.A. McCabe et al., 1991) and a simulation model (PowerWeb) of a realistic bulk power system. There are unique physical aspects associated with the supply of electricity (e.g. required instantaneous matching of supply and demand, unintended congestion of parallel transmission routes and maintenance of system stability in response to disturbances). As a result, traditional theories of efficient markets and auction structures developed for other commodities may not be efficient if applied without alteration to markets for electricity. Conversely, current utility rules of operation developed for a centrally planned regime may not be appropriate in a competitive environment. The research does not address the issues of multiperiod operations (unit commitment) and multidimensional markets (ancillary services), and considers only real power in a single time period. The main objective is to test three alternative auction mechanisms when market power is a potential problem. This situation occurs when limits on transmission lines are binding to form a load pocket in which demand is met by a few (in this case two) generators.