TY - JOUR
T1 - Stochastically Optimized, Carbon-Reducing Dispatch of Storage, Generation, and Loads
JF - IEEE Transactions on Power Systems
Y1 - 2015/03//
SP - 1064
EP - 1075
A1 - Alberto J Lamadrid
A1 - Daniel L. Shawhan
A1 - Carlos E. Murillo-Sanchez
A1 - Ray D. Zimmerman
A1 - Zhu, Yujia
A1 - Daniel J. Tylavsky
A1 - Kindle, Andrew G.
A1 - Dar, Zamiyad
KW - CERTS
KW - reliability and markets
KW - RM07-002
AB - We present a new formulation of a hybrid stochastic-robust optimization and use it to calculate a look-ahead, security-constrained optimal power flow. It is designed to reduce carbon dioxide (CO2) emissions by efficiently accommodating renewable energy sources and by realistically evaluating system changes that could reduce emissions. It takes into account ramping costs, CO2 damages, demand functions, reserve needs, contingencies, and the temporally linked probability distributions of stochastic variables such as wind generation. The inter-temporal trade-offs and transversality of energy storage systems are a focus of our formulation. We use it as part of a new method to comprehensively estimate the operational net benefits of system changes. Aside from the optimization formulation, our method has four other innovations. First, it statistically estimates the cost and CO2 impacts of each generator's electricity output and ramping decisions. Second, it produces a comprehensive measure of net operating benefit, and disaggregates that into the effects on consumers, producers, system operators, government, and CO2 damage. Third and fourth, our method includes creating a novel, modified Ward reduction of the grid and a thorough generator dataset from publicly available information sources. We then apply this method to estimating the impacts of wind power, energy storage, and operational policies.
VL - 30
IS - 2
JO - IEEE Trans. Power Syst.
DO - 10.1109/TPWRS.2014.2388214
ER -
TY - JOUR
T1 - Secure Planning and Operations of Systems With Stochastic Sources, Energy Storage, and Active Demand
JF - IEEE Transactions on Smart Grid
Y1 - 2013/12//
SP - 2220
EP - 2229
A1 - Carlos E. Murillo-Sanchez
A1 - Ray D. Zimmerman
A1 - C. Lindsay Anderson
A1 - Robert J. Thomas
KW - ancillary services
KW - CERTS
KW - power system planning
KW - power system reliability
KW - reliability and markets
KW - renewables
KW - RM07-002
AB - 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.
VL - 4
IS - 4
JO - IEEE Trans. Smart Grid
DO - 10.1109/TSG.2013.2281001
ER -
TY - JOUR
T1 - A stochastic, contingency-based security-constrained optimal power flow for the procurement of energy and distributed reserve
JF - Decision Support Systems
Y1 - 2013/12//
A1 - Carlos E. Murillo-Sanchez
A1 - Ray D. Zimmerman
A1 - C. Lindsay Anderson
A1 - Robert J. Thomas
KW - CERTS
KW - reliability and markets
KW - reserve markets
KW - RM07-002
KW - smart grid
AB - It is widely agreed that optimal procurement of reserves, with explicit consideration of system contingencies, can improve reliability and economic efficiency in power systems. With increasing penetration of uncertain generation resources, this optimal allocation is becoming even more crucial. Herein, a problem formulation is developed to solve the day-ahead energy and reserve market allocation and pricing problem that explicitly considers the redispatch set required by the occurrence of contingencies and the corresponding optimal power flow, static and dynamic security constraints. Costs and benefits, including those arising from eventual demand deviation and contingency-originated redispatch and shedding, are weighted by the contingency probabilities, resulting in a scheme that contracts the optimal amount of resources in a stochastic day-ahead procurement setting. Furthermore, the usual assumption that the day-ahead contracted quantities correspond to some base case dispatch is removed, resulting in an optimal procurement as opposed to an optimal dispatch. Inherent in the formulation are mechanisms for rescheduling and pricing dispatch deviations arising from realized demand fluctuations and contingencies. Because the formulation involves a single, one stage, comprehensive mathematical program, the Lagrange multipliers obtained at the solution are consistent with shadow prices and can be used to clear the day-ahead and spot markets of the different commodities involved.
VL - 56
JO - Decision Support Systems
DO - 10.1016/j.dss.2013.04.006
ER -
TY - CONF
T1 - Alternate mechanisms for integrating renewable sources of energy into electricity markets
T2 - 2012 IEEE Power & Energy Society General Meeting. New Energy Horizons - Opportunities and Challenges2012 IEEE Power and Energy Society General Meeting
Y1 - 2012/07//
SP - 1
EP - 8
A1 - Alberto J Lamadrid
A1 - Timothy D. Mount
A1 - Ray D. Zimmerman
A1 - Carlos E. Murillo-Sanchez
A1 - C. Lindsay Anderson
KW - electricity markets
KW - load modeling
KW - reliability and markets
KW - renewables integration
KW - RM12-004
AB - 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.
JF - 2012 IEEE Power & Energy Society General Meeting. New Energy Horizons - Opportunities and Challenges2012 IEEE Power and Energy Society General Meeting
PB - IEEE
CY - San Diego, CA
SN - 978-1-4673-2727-5
DO - 10.1109/PESGM.2012.6345107
ER -
TY - JOUR
T1 - MATPOWER: Steady-State Operations, Planning, and Analysis Tools for Power Systems Research and Education
JF - IEEE Transactions on Power Systems
Y1 - 2011/02//
SP - 12
EP - 19
A1 - Ray D. Zimmerman
A1 - Carlos E. Murillo-Sanchez
A1 - Robert J. Thomas
KW - CERTS
KW - load flow
KW - optimal power flow (OPF)
KW - power system economics
KW - reliability and markets
KW - RM07-002
AB - 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.
VL - 26
IS - 1
JO - IEEE Trans. Power Syst.
DO - 10.1109/TPWRS.2010.2051168
ER -
TY - CONF
T1 - An advanced security constrained OPF that produces correct market-based pricing
T2 - 2008 IEEE Power and Energy Society General Meeting
Y1 - 2008/07//
SP - 1
EP - 6
A1 - Robert J. Thomas
A1 - Carlos E. Murillo-Sanchez
A1 - Ray D. Zimmerman
KW - electricity markets
KW - optimal power flow (OPF)
KW - reliability and markets
KW - RM07-002
AB - 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.
JF - 2008 IEEE Power and Energy Society General Meeting
PB - IEEE
CY - Pittsburgh, PA, USA
SN - 978-1-4244-1905-0
DO - 10.1109/PES.2008.4596331
ER -
TY - RPRT
T1 - A "SuperOPF" Framework
Y1 - 2008/12//
SP - 59
A1 - Alberto J Lamadrid
A1 - Surin Maneevitjit
A1 - Timothy D. Mount
A1 - Carlos E. Murillo-Sanchez
A1 - Robert J. Thomas
A1 - Ray D. Zimmerman
KW - Market mechanisms
KW - reliability and markets
KW - reliability management
KW - RM05-003
KW - SuperOPF
AB - The objective of the SuperOPF project is to develop a framework that will provide proper allocation and valuation of resources through true co-optimization across multiple scenarios. Instead of solving a sequence of simpler and approximate sub-problems, the SuperOPF approach combines as much as possible into a single mathematical programming framework, with a full AC network and simultaneous co-optimization across multiple scenarios with stochastic costs.This effort involves development of the problem formulations, implementation of research grade software codes, and testing of the methods and algorithms on a range of case studies to demonstrate their added value over currently available tools.
ER -
TY - RPRT
T1 - Time-space Methods for Determining Locational Reserves: A Framework for Location Based Pricing and Scheduling for Reserve Markets Annual Report
Y1 - 2001/11//
SP - 20
A1 - James S. Thorp
A1 - Carlos E. Murillo-Sanchez
A1 - Robert J. Thomas
KW - locational marginal pricing
KW - reserve markets
AB - This project is exploring several options for the solution of the reserve scheduling problem that are also compatible with the idea of a deregulated reserve market structure. One of the major questions is whether it is possible to devise a cost-minimizing scheduling algorithm for the spatially distributed reserve problem that reveals the location-based shadow prices for the reserve requirements. The constraints imposed by grid security considerations should be taken into account in the procedure. If this major question is answered in the affirmative, a framework for a reserve power market based on the computed shadow prices should be derived automatically from it.
ER -