R. Baldick | The University of Texas at Austin (original) (raw)
Papers by R. Baldick
Conference Record of the Thirty-Sixth Asilomar Conference on Signals, Systems and Computers, 2002.
Renewable Energy and Power Quality Journal, 2012
IEEE Transactions on Power Delivery, 2009
Journal of Regulatory Economics, 1993
Proceedings 2001 IEEE International Conference on Computer Design: VLSI in Computers and Processors. ICCD 2001
IEEE Transactions on Power Systems, 2011
IEEE Transactions on Power Systems, 2007
Proceedings of the ASP-DAC '99 Asia and South Pacific Design Automation Conference 1999 (Cat. No.99EX198), 1999
In this paper we investigate the multiplexing of heterogeneous applications and the pricing of tr... more In this paper we investigate the multiplexing of heterogeneous applications and the pricing of transmission services on an ATM network. Pricing is of interest for network management to promote efficient utilization of resources. A framework is presented in which users select from a menu of services, are peak-rate policed, and are charged according to their usage and connection time. We illustrate the considerable improvement in network utilization possible compared to a traditional
2019 American Control Conference (ACC), Jul 1, 2019
Meter measurements in the power grid are susceptible to manipulation by adversaries, that can lea... more Meter measurements in the power grid are susceptible to manipulation by adversaries, that can lead to errors in state estimation. This paper presents a general framework to study attacks on state estimation by adversaries capable of injecting bad-data into measurements and further, of jamming their reception. Through these two techniques, a novel `detectable jamming' attack is designed that changes the state estimation despite failing bad-data detection checks. Compared to commonly studied `hidden' data attacks, these attacks have lower costs and a wider feasible operating region. It is shown that the entire domain of jamming costs can be divided into two regions, with distinct graph-cut based formulations for the design of the optimal attack. The most significant insight arising from this result is that the adversarial capability to jam measurements changes the optimal 'detectable jamming' attack design only if the jamming cost is less than half the cost of bad-data...
IEEE Transactions on Power Systems
This paper introduces a two-stage stochastic program for transmission planning. The model has two... more This paper introduces a two-stage stochastic program for transmission planning. The model has two dependent random variables, namely, total electric load and available wind power. Given univariate marginal distributions for these two random variables and their correlation coefficient, the joint distribution is modeled using a Gaussian copula. The optimal power flow (OPF) problem is solved based on the linearized direct current (DC) power flow. The Electric Reliability Council of Texas (ERCOT) network model and its load and wind data are used for a test case. A 95% confidence interval is formed on the optimality gap of candidate solutions obtained using a sample average approximation with 200 and 300 samples from the joint distribution of load and wind.
2012 IEEE Power and Energy Society General Meeting, 2012
ABSTRACT
2013 IEEE Power & Energy Society General Meeting, 2013
ABSTRACT
In recent years, high penetration of variable generating sources, such as wind power, has challen... more In recent years, high penetration of variable generating sources, such as wind power, has challenged independent system operators (ISO) in keeping a cheap and reliable power system operation. Any deviation between expected and real wind production must be absorbed by the power system resources (reserves), which must be available and ready to be deployed in real time. To guarantee this resource availability, the system resources must be committed in advance, usually the day-ahead, by solving the so-called unit commitment (UC) problem. If the quantity of committed resources is extremely low, there will be devastating and costly consequences in the system, such as significant load shedding. On the other hand, if this quantity is extremely high, the system operation will be excessively expensive, mainly because facilities will not be fully exploited.This thesis proposes computationally efficient models for optimal day-ahead planning in (thermal) power systems to adequately face the stochastic nature of wind production in the real-time system operation. The models can support ISOs to face the new challenges in short-term planning as uncertainty increases dramatically due to the integration of variable generating resources. This thesis then tackles the UC problem in the following aspects: Power system representation: This thesis identifies drawbacks of the traditional energy-block scheduling approach, which make it unable to adequately prepare the power system to face deterministic and perfectly known events. To overcome those drawbacks, we propose the ramp-based scheduling approach that more accurately describes the system operation, thus better exploiting the system flexibility.UC computational performance: Developing more accurate models would be pointless if these models considerably increase the computational burden of the UC problem, which is already a complex integer and non-convex problem. We then devise simultaneously tight and compact formulations under the mixed-integer programming (MIP) approach. This simultaneous characteristic reinforces the convergence speed by reducing the search space (tightness) and simultaneously increasing the searching speed (compactness) with which solvers explore that reduced space.Uncertainty management in UC: By putting together the improvements in the previous two aspects, this thesis contributes to a better management of wind uncertainty in UC, even though these two aspects are in conflict and improving one often means harming the other. If compared with a traditional energy-block UC model under the stochastic (deterministic) paradigm, a stochastic (deterministic) ramp-based UC model: 1) leads to more economic operation, due to a better and more detailed system representation, while 2) being solved significantly faster, because the core of the model is built upon simultaneously tight and compact MIP formulations.To further improve the uncertainty management in the proposed ramp-based UC, we extend the formulation to a network-constrained UC with robust reserve modelling. Based on robust optimization insights, the UC solution guarantees feasibility for any realization of the uncertain wind production, within the considered uncertainty ranges. This final model remains as a pure linear MIP problem whose size does not depend on the uncertainty representation, thus avoiding the inherent computational complications of the stochastic and robust UCs commonly found in the literature.
IEEE Transactions on Power Systems, 2001
J. Aguado and V. Quintana comment on the paper by R. Ebrahimian and R. Baldick (see ibid., vol.15... more J. Aguado and V. Quintana comment on the paper by R. Ebrahimian and R. Baldick (see ibid., vol.15, no.4, p.1240-6, 2000), and ask for comments on five points relating to their own work in this area of power network state estimation. The original authors reply to the comments
IEEE Transactions on Power Systems, 1997
IEEE Transactions on Power Systems, 2005
We consider transmission owners that bid capacity, under appropriate Regional Transmission Organi... more We consider transmission owners that bid capacity, under appropriate Regional Transmission Organization (RTO) market rules, at a positive price into forward and spot (dispatch) auctions to derive congestion revenues. This can encompass daily, monthly, or multimonthly auctions, allowing for commitment of transmission to reflect market needs in different time periods, e.g., seasons. We provide two and three node examples and
Conference Record of the Thirty-Sixth Asilomar Conference on Signals, Systems and Computers, 2002.
Renewable Energy and Power Quality Journal, 2012
IEEE Transactions on Power Delivery, 2009
Journal of Regulatory Economics, 1993
Proceedings 2001 IEEE International Conference on Computer Design: VLSI in Computers and Processors. ICCD 2001
IEEE Transactions on Power Systems, 2011
IEEE Transactions on Power Systems, 2007
Proceedings of the ASP-DAC '99 Asia and South Pacific Design Automation Conference 1999 (Cat. No.99EX198), 1999
In this paper we investigate the multiplexing of heterogeneous applications and the pricing of tr... more In this paper we investigate the multiplexing of heterogeneous applications and the pricing of transmission services on an ATM network. Pricing is of interest for network management to promote efficient utilization of resources. A framework is presented in which users select from a menu of services, are peak-rate policed, and are charged according to their usage and connection time. We illustrate the considerable improvement in network utilization possible compared to a traditional
2019 American Control Conference (ACC), Jul 1, 2019
Meter measurements in the power grid are susceptible to manipulation by adversaries, that can lea... more Meter measurements in the power grid are susceptible to manipulation by adversaries, that can lead to errors in state estimation. This paper presents a general framework to study attacks on state estimation by adversaries capable of injecting bad-data into measurements and further, of jamming their reception. Through these two techniques, a novel `detectable jamming' attack is designed that changes the state estimation despite failing bad-data detection checks. Compared to commonly studied `hidden' data attacks, these attacks have lower costs and a wider feasible operating region. It is shown that the entire domain of jamming costs can be divided into two regions, with distinct graph-cut based formulations for the design of the optimal attack. The most significant insight arising from this result is that the adversarial capability to jam measurements changes the optimal 'detectable jamming' attack design only if the jamming cost is less than half the cost of bad-data...
IEEE Transactions on Power Systems
This paper introduces a two-stage stochastic program for transmission planning. The model has two... more This paper introduces a two-stage stochastic program for transmission planning. The model has two dependent random variables, namely, total electric load and available wind power. Given univariate marginal distributions for these two random variables and their correlation coefficient, the joint distribution is modeled using a Gaussian copula. The optimal power flow (OPF) problem is solved based on the linearized direct current (DC) power flow. The Electric Reliability Council of Texas (ERCOT) network model and its load and wind data are used for a test case. A 95% confidence interval is formed on the optimality gap of candidate solutions obtained using a sample average approximation with 200 and 300 samples from the joint distribution of load and wind.
2012 IEEE Power and Energy Society General Meeting, 2012
ABSTRACT
2013 IEEE Power & Energy Society General Meeting, 2013
ABSTRACT
In recent years, high penetration of variable generating sources, such as wind power, has challen... more In recent years, high penetration of variable generating sources, such as wind power, has challenged independent system operators (ISO) in keeping a cheap and reliable power system operation. Any deviation between expected and real wind production must be absorbed by the power system resources (reserves), which must be available and ready to be deployed in real time. To guarantee this resource availability, the system resources must be committed in advance, usually the day-ahead, by solving the so-called unit commitment (UC) problem. If the quantity of committed resources is extremely low, there will be devastating and costly consequences in the system, such as significant load shedding. On the other hand, if this quantity is extremely high, the system operation will be excessively expensive, mainly because facilities will not be fully exploited.This thesis proposes computationally efficient models for optimal day-ahead planning in (thermal) power systems to adequately face the stochastic nature of wind production in the real-time system operation. The models can support ISOs to face the new challenges in short-term planning as uncertainty increases dramatically due to the integration of variable generating resources. This thesis then tackles the UC problem in the following aspects: Power system representation: This thesis identifies drawbacks of the traditional energy-block scheduling approach, which make it unable to adequately prepare the power system to face deterministic and perfectly known events. To overcome those drawbacks, we propose the ramp-based scheduling approach that more accurately describes the system operation, thus better exploiting the system flexibility.UC computational performance: Developing more accurate models would be pointless if these models considerably increase the computational burden of the UC problem, which is already a complex integer and non-convex problem. We then devise simultaneously tight and compact formulations under the mixed-integer programming (MIP) approach. This simultaneous characteristic reinforces the convergence speed by reducing the search space (tightness) and simultaneously increasing the searching speed (compactness) with which solvers explore that reduced space.Uncertainty management in UC: By putting together the improvements in the previous two aspects, this thesis contributes to a better management of wind uncertainty in UC, even though these two aspects are in conflict and improving one often means harming the other. If compared with a traditional energy-block UC model under the stochastic (deterministic) paradigm, a stochastic (deterministic) ramp-based UC model: 1) leads to more economic operation, due to a better and more detailed system representation, while 2) being solved significantly faster, because the core of the model is built upon simultaneously tight and compact MIP formulations.To further improve the uncertainty management in the proposed ramp-based UC, we extend the formulation to a network-constrained UC with robust reserve modelling. Based on robust optimization insights, the UC solution guarantees feasibility for any realization of the uncertain wind production, within the considered uncertainty ranges. This final model remains as a pure linear MIP problem whose size does not depend on the uncertainty representation, thus avoiding the inherent computational complications of the stochastic and robust UCs commonly found in the literature.
IEEE Transactions on Power Systems, 2001
J. Aguado and V. Quintana comment on the paper by R. Ebrahimian and R. Baldick (see ibid., vol.15... more J. Aguado and V. Quintana comment on the paper by R. Ebrahimian and R. Baldick (see ibid., vol.15, no.4, p.1240-6, 2000), and ask for comments on five points relating to their own work in this area of power network state estimation. The original authors reply to the comments
IEEE Transactions on Power Systems, 1997
IEEE Transactions on Power Systems, 2005
We consider transmission owners that bid capacity, under appropriate Regional Transmission Organi... more We consider transmission owners that bid capacity, under appropriate Regional Transmission Organization (RTO) market rules, at a positive price into forward and spot (dispatch) auctions to derive congestion revenues. This can encompass daily, monthly, or multimonthly auctions, allowing for commitment of transmission to reflect market needs in different time periods, e.g., seasons. We provide two and three node examples and