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Showing papers by "Chen-Ching Liu published in 2010"


Journal ArticleDOI
01 Jul 2010
TL;DR: A supervisory control and data acquisition security framework with the following four major components is proposed: (1) real-time monitoring; (2) anomaly detection; (3) impact analysis; and (4) mitigation strategies; an attack-tree-based methodology for impact analysis is developed.
Abstract: Disruption of electric power operations can be catastrophic on national security and the economy. Due to the complexity of widely dispersed assets and the interdependences among computer, communication, and power infrastructures, the requirement to meet security and quality compliance on operations is a challenging issue. In recent years, the North American Electric Reliability Corporation (NERC) established a cybersecurity standard that requires utilities' compliance on cybersecurity of control systems. This standard identifies several cyber-related vulnerabilities that exist in control systems and recommends several remedial actions (e.g., best practices). In this paper, a comprehensive survey on cybersecurity of critical infrastructures is reported. A supervisory control and data acquisition security framework with the following four major components is proposed: (1) real-time monitoring; (2) anomaly detection; (3) impact analysis; and (4) mitigation strategies. In addition, an attack-tree-based methodology for impact analysis is developed. The attack-tree formulation based on power system control networks is used to evaluate system-, scenario -, and leaf-level vulnerabilities by identifying the system's adversary objectives. The leaf vulnerability is fundamental to the methodology that involves port auditing or password strength evaluation. The measure of vulnerabilities in the power system control framework is determined based on existing cybersecurity conditions, and then, the vulnerability indices are evaluated.

355 citations


Journal ArticleDOI
TL;DR: The results indicate that the proposed algorithm improves the voltage profile of an island after the system reconfiguration compared with the algorithm that only considers real power balance.
Abstract: In response to disturbances, a self-healing system reconfiguration that splits a power network into self-sufficient islands can stop the propagation of disturbances and avoid cascading events This paper proposes an area partitioning algorithm that minimizes both real and reactive power imbalance between generation and load within islands The proposed algorithm is a smart grid technology that applies a highly efficient multilevel multi-objective graph partitioning technique Thus, it is applicable to very large power grids The proposed algorithm has been simulated on a 200- and a 22,000-bus test systems The results indicate that the proposed algorithm improves the voltage profile of an island after the system reconfiguration compared with the algorithm that only considers real power balance In doing so, the algorithm maintains the computational efficiency

138 citations


Journal ArticleDOI
TL;DR: In this paper, the authors present a flexible and integrative method to assess market designs through agent-based modeling and evaluate the proposed PJM-like market power mitigation rules of the California electricity market.
Abstract: The California energy crisis in 2000-2001 showed what could happen to an electricity market if it did not go through a comprehensive and rigorous testing before its implementation. Due to the complexity of the market structure, strategic interaction between the participants, and the underlying physics, it is difficult to fully evaluate the implications of potential changes to market rules. This paper presents a flexible and integrative method to assess market designs through agent-based modeling. Realistic simulation scenarios are constructed for evaluation of the proposed PJM-like market power mitigation rules of the California electricity market. Simulation results show that in the absence of market power mitigation, generation company (GENCO) agents facilitated by Q-learning are able to exploit the market flaws and make significantly higher profits relative to the competitive benchmark. The incorporation of PJM-like local market power mitigation rules is shown to be effective in suppressing the exercise of market power.

93 citations


Posted Content
01 Jan 2010
TL;DR: In this paper, the authors proposed a new short-term forecasting algorithm for congestion, LMPs, and other power system variables based on the concept of system patterns, which combines of status flags for generating units and transmission lines.
Abstract: Short-term congestion forecasting is highly important for market participants in wholesale power markets that use Locational Marginal Prices (LMPs) to manage congestion. Accurate congestion forecasting facilitates market traders in bidding and trading activities and assists market operators in system planning. This study proposes a new short-term forecasting algorithm for congestion, LMPs, and other power system variables based on the concept of system patterns—combinations of status flags for generating units and transmission lines. The advantage of this algorithm relative to standard statistical forecasting methods is that structural aspects underlying power market operations are exploited to reduce forecast error. The advantage relative to previously proposed structural forecasting methods is that data requirements are substantially reduced. Forecasting results based on a NYISO case study demonstrate the feasibility and accuracy of the proposed algorithm.

55 citations


Posted Content
01 Jan 2010
TL;DR: In this paper, the authors analyzed a financial bilateral contract negotiation process between a generating company and a load-serving entity in a wholesale electric power market with congestion managed by locational marginal pricing.
Abstract: Bilateral contracts are important risk-hedging instruments constituting a major component in the portfolios held by many electric power market participants. However, bilateral contract negotiation is a complicated process because it involves risk management, strategic bargaining, and multi-market participation. This study analyzes a financial bilateral contract negotiation process between a generating company and a load-serving entity in a wholesale electric power market with congestion managed by locational marginal pricing. Nash bargaining theory is used to model a Pareto-efficient settlement point. The model predicts negotiation results under varied conditions and identifies circumstances in which the two parties might fail to reach an agreement. Both analysis and simulation are used to gain insight regarding how relative risk aversion and biased price estimates influence negotiated outcomes. These results should provide useful guidance to market participants in their bilateral contract negotiation processes.

51 citations


Proceedings ArticleDOI
18 Nov 2010
TL;DR: This work aims at identifying, assessing and comparing several possible HVDC network topologies, with appropriate control and protection schemes, able to collect wind energy on large areas, transmit it at the best points to the AC grid and provide the necessary ancillary services for optimising the DC / AC interconnection in normal and disturbed conditions.
Abstract: In the scope of a recently launched European Research Project, a team of experts from public laboratories and TSO is in charge of defining the concepts and methodological approaches to design and analyse the technical and economic feasibility of future HVDC grids. This work aims at identifying, assessing and comparing several possible HVDC network topologies, with appropriate control and protection schemes, able to collect wind energy on large areas, transmit it at the best points to the AC grid and provide the necessary ancillary services for optimising the DC / AC interconnection in normal and disturbed conditions. The methodology adopted for the study and presented in this paper will focus on three main items: 1. identify and assess the economic drivers for the development of off-shore HVDC networks 2. identify the requirements for an optimal operation of the AC / DC interconnected power systems under normal and emergency conditions 3. conceptualise the coordinated control / command and protection plans for HVDC networks This paper gives a comprehensive view of the issues and tasks to be addressed during the run of the project.

46 citations


Proceedings ArticleDOI
25 Jul 2010
TL;DR: A global piecewise linear-affine mapping can be used to predict system patterns corresponding to forecasted load patterns, hence also dispatch levels, LMPs, and line flows.
Abstract: Short-term prediction of system variables with respect to load levels is highly important for market operations and demand response programs in wholesale power markets with congestion managed by locational marginal prices (LMPs). Previous studies have conducted local sensitivity analyses for LMPs at specific system operating points. This study undertakes a more global analysis of system variable sensitivities when LMPs are derived from DC optimal power flow solutions for day-ahead energy markets. The possible system states are first partitioned into subsets (“system patterns”) based on relatively slow-changing attributes. It is next established analytically that there is a fixed linear-affine mapping between bus load patterns and corresponding system variables, conditional on a particular system pattern. It is then explained how this global piecewise linear-affine mapping can be used to predict system patterns corresponding to forecasted load patterns, hence also dispatch levels, LMPs, and line flows. A 5-bus case study is used to illustrate the accuracy of the proposed prediction method.

9 citations


Book ChapterDOI
01 Jan 2010
TL;DR: In this article, the authors classify forecasting techniques based on their objective, concept, time horizon, input-output specification, and level of accuracy, and demonstrate a hybrid forecasting system, which combines fuzzy inference system and least-squares estimation.
Abstract: The purpose of electricity price forecasting is to estimate future electricity prices, particularly locational marginal prices (LMP), with consideration to both security and capacity constraints in a grid environment. Electricity price forecasting is vital to both market participants and market operators in wholesale electricity markets. Electricity price forecasts are used to assist the decision making of market participants on bidding submissions, asset allocations, bilateral trades, transmission and distribution planning, and generation construction locations. Electricity price forecasts are also used by market operators to uncover possible market power. The inaccuracy of electricity price forecasting is due to problems associated with volatility of prices, interpretability of explanatory variables, and underlying impacts of power grid security. This study classifies forecasting techniques common in the literature based on their objective, concept, time horizon, input–output specification, and level of accuracy. Thus the state-of-the-art of electricity price forecasting is described in this study. This survey facilitates the validation, comparison, and improvements of specific or combined methods of price forecasting in competitive electricity markets. Moreover, this study demonstrates a hybrid forecasting system, which combines fuzzy inference system and least-squares estimation. The proposed mechanism is applied to the day-ahead electricity price forecasting of an actual security-constrained, wholesale electricity market. This hybrid forecasting system provides both accuracy and transparency to electricity price forecasts. The forecasting information is also interpretable with respect to the fuzzy representations of selected inputs.

8 citations


Journal ArticleDOI
TL;DR: In this article, the authors propose a market-driven solution for importing inexpensive power when this energy is available, but the recovery is based on transmission service charges and the value of incremental financial transmission rights (FTRs) created by the project.
Abstract: Merchant transmission projects (MTPs) are primarily market solutions for importing inexpensive power when this energy is available. As a market driven solution, full recovery of the investment is not guaranteed. In general, the recovery is based on transmission service charges and the value of incremental financial transmission rights (FTRs) created by the project. Since FTRs are valuable only when the system is constrained, the FTR's value diminishes as the constraint is eliminated by the MTP. Hence, the MTP will be commercially viable only if its transmission capacity is fully subscribed. Otherwise, the MTP will likely not be built.

6 citations


Proceedings ArticleDOI
25 Jul 2010
TL;DR: In this paper, a two-step market-based transmission rate design for recovering an MTP investment is presented, where the first step is to develop a firm transmission service rate for using the MTP via an open subscription bid process, and the second step identifies the range of transmission rates for developing possible rate discounts to encourage non-firm transmission usages.
Abstract: Merchant transmission projects (MTPs) are primarily market solutions for importing inexpensive power when this energy is available. As a market driven solution, full recovery of the investment is not guaranteed. In general, the recovery is based on transmission service charges and the value of incremental financial transmission rights (FTRs) created by the project. Since FTRs are valuable only when the system is constrained, the FTR's value diminishes as the constraint is eliminated by the MTP. Hence, the MTP will be commercially viable only if its transmission capacity is fully subscribed. Otherwise, the MTP will likely not be built. This paper presents a two-step market-based transmission rate design for recovering an MTP investment. The first step is to develop a firm transmission service rate for using the MTP via an open subscription bid process. If the MTP capacity is not fully subscribed, the authors propose that the remaining investment be recovered via nonfirm transmission services if and when cheap energy is available. Considering the random availability of economic energy, this second step identifies the range of transmission rates for developing possible rate discounts to encourage non-firm transmission usages to optimize the MTP investment recovery.

4 citations


01 Jan 2010
TL;DR: In this paper, the authors present a flexible and integrative method to assess market designs through agent-based modeling, and evaluate the pro-posed PJM-like market power mitigation rules of the California electricity market.
Abstract: The California energy crisis in 2000-2001 showed what could happen to an electricity market if it did not go through a comprehensive and rigorous testing before its implementation. Due to the complexity of the market structure, strategic interaction between the participants, and the underlying physics, it is difficult to fully evaluate the implications of potential changes to market rules. This paper presents a flexible and integrative method to assess market designs through agent-based modeling. Realistic simulation scenarios are constructed for evaluation of the pro- posed PJM-like market power mitigation rules of the California electricity market. Simulation results show that in the absence of market power mitigation, generation company (GENCO) agents facilitated by Q-learning are able to exploit the market flaws and make significantly higher profits relative to the competitive benchmark. The incorporation of PJM-like local market power mitigation rules is shown to be effective in suppressing the exercise of market power.