Showing papers by "Robert J. Thomas published in 2007"

On Computational Issues of Market-Based Optimal Power Flow

Abstract: 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.

Transmission Expansion Planning Using Contingency Criteria

Abstract: This paper proposes a methodology for choosing the best transmission expansion plan considering various types of security (operating reliability) criteria. The proposed method minimizes the total cost that includes the investment cost of transmission as well as the operating cost and standby cost of generators. The purpose of the study is development of new methodology for solving transmission system expansion planning problem subject to contingency criteria which are essentially extensions of the (N-1) contingency criterion. The transmission expansion problem uses an integer programming framework, and the optimal strategy is determined using a branch and bound method that utilizes a network flow approach and the maximum flow-minimum cut set theorem. The characteristics of the proposed method are illustrated by applying it to a five-bus system and a 21-bus system. The results of these case studies demonstrate that the proposed method provides a practical way to find an optimal plan for power system expansion planning.

On the computation and application of multi-period security-constrained optimal power flow for real-time electricity market operations

Abstract: This work concerns the formulation and solution of a multi-period security-constrained optimal power flow problem for real-time electricity market operations. The solution of the proposed problem is intended to be part of the core pricing procedure for electricity trading in open markets where real energy, reactive energy, voltages support, and other system resources and services can all be traded in discrete bids and offers. Traditionally, real-time dispatching operations only involve solving single-period security-constrained optimal power flow problems. This work demonstrates the need for solving multi-period security-constrained optimal power flows. The nonsmoothness of the offer/bid-driven optimal power flow problem is studied. Three techniques, namely, a trust-region based augmented Lagrangian method, a step-controlled primal-dual interior point method, and a modified constrained cost variables method, are developed for reliable and efficient computation of large-scale nonsmooth optimal power flows. Numerical studies show that these techniques are reliable and better than some existing ones. To reduce the computational complexity, two decomposition techniques are proposed and studied. In the first one, the auxiliary problem principle method is extended to handle inequality constraints created from generator ramping limits. In the second one, binding time-coupling and contingency-coupling constraints are estimated, ranked, and filtered before the computation is decomposed and parallelized using standard block matrix computation techniques. According to experimental results, the most promising way of solving large-scale multi-period security-constrained optimal power flow problems in real time is to combine the second decomposition method with the modified constrained cost variables method. The optimal power flow formulation and relevant computation techniques proposed in this work balance the needs for: (1) deterministic convergence, (2) accurate computation of nodal prices, (3) support of both smooth and nonsmooth costings of a variety of resources and services, such as real energy, reactive energy, voltage support, etc., (4) full active and reactive power flow modeling of large-scale systems, and (5) satisfactory worst-case performance that meets the real-time dispatching requirement.

A scalable wireless communication architecture for average consensus

Abstract: This paper introduces a multiple-access coding technique that is tailored to solve average consensus problems efficiently in wireless networks. We propose a novel data driven architecture which grants channel access to nodes based on their local data values. We analyze the performance of the scheme in the presence of quantization errors and noise. We show that our scheme is unbiased with respect to quantized consensus algorithms, it achieves good MSE performance, and it can be configured to provide a speedup in the convergence rate. The amount of speedup achieved is a function of |Qk| which indicates the number of quantization bins used to represent the state variables exchanged during the computation.

Transmission System Expansion Planning Considering Outage Cost

Abstract: This paper proposes a method for choosing the best composite power system expansion plan considering an annual outage cost assessment. The proposed method minimizes the investment budget (economics) for constructing new generating units and transmission lines as well as the annual outage cost subject to deterministic (demand constraint) and probabilistic reliability criterion (LOLER), while considering the uncertainties of system elements. It models the power system expansion problem as an integer programming one. The method solves for the optimal strategy using a probabilistic theory-based branch and bound method that utilizes a network flow approach and the maximum flow-minimum cut set theorem. The proposed method is applied to a 5-bus MRBTS, the test results demonstrate that the proposed method is suitable for solving the composite power system expansion planning problem subject to practical future uncertainties.

On the Communication Architecture for Wide-Area Real-Time Monitoring in Power Networks

Abstract: Reliable and efficient operation of power networks is of paramount importance. In this paper we explore communication architectures that leverage phasor measurement units (PMUs) and fusion centers to enable robust real-time monitoring of power networks over wide areas. We examine scalability issues in data aggregation for a power network in which PMUs are attached to every bus. We argue that in power networks, the data recorded by the PMUs are spatially correlated and therefore the data admit a sparse representation in a given basis. Furthermore, the number of bits required to reconstruct the PMU data to within a given accuracy at a remote location grows sublinearly with the density of the power network. Our results are: i) the PMUs should not transmit their data to the fusion center independently or asynchronously - an intermediate data aggregation step is beneficial, and ii) if we perform data aggregation then we can add more PMUs to the network to achieve finer network monitoring without causing network congestion

Composite Power System Expansion Planning Considering Outage Cost

Abstract: This paper proposes a method for choosing the best composite power system expansion plan considering a outage cost assessment. The proposed method minimizes the investment budget (economics) for constructing new generating units and transmission lines as well as outage cost subject to deterministic (demand constraint) and probabilistic reliability criterion (LOLER), while considering the uncertainties of system elements. It models the power system expansion problem as an integer programming one. The method solves for the optimal strategy using a probabilistic theory-based branch and bound method that utilizes a network flow approach and the maximum flow- minimum cut set theorem. Although the proposed method is applied to a simple sample study, the test results demonstrate that the proposed method is suitable for solving the composite power system expansion planning problem subject to practical future uncertainties.

Transmission System Expansion Plans in View Point of Deterministic, Probabilistic and Security Reliability Criteria

Abstract: This paper proposes three methods for choosing the transmission system expansion plan considering three reliability constraints, which are deterministic reliability criterion, probabilistic reliability criterion and security criterion based on N-alpha contingency in order to give more successful market operation. The proposed method minimizes total investment cost. It models the transmission system expansion problem as an integer programming one. The method solves for the optimal strategy using a branch and bound method that utilizes a network flow approach and the maximum flow-minimum cut set theorem. The 21 bus system case study results demonstrate that the proposed method is practical for solving the power system expansion planning problem subject to practical future uncertainties.

Towards Reliable Computation of Large-Scale Market-Based Optimal Power Flow

Abstract: The deregulated electricity market calls for robust OPF tools that can provide deterministic convergence, accurate computation of a variety of nodal prices, support of continuous costs as well as discrete bids and offers, full active and reactive power flow modeling of large-scale systems, and satisfactory worst-case performance that meets the real-time dispatching requirement. For historical reasons, most prior research on OPF has focused on performance issues, without much treatment of requirements. This paper discusses these new challenges and presents two new algorithms for reliable computation of large-scale market-based OPF: trust-region based augmented Lagrangian method (TRALM) and step-controlled primal-dual interior point method (SCIPM). The former is more theoretically rigid while the latter is more effective in practice. The new algorithms, along with several existing ones, are tested and compared using large-scale power system models

Real and Reactive Power Prices and Market Power

Abstract: The exercise of market power is a major concern in deregulating the electric energy business in the U.S. Exploitation of market power can destroy any market efficiencies and award unwarranted profits based solely on the lack of competition rather than on economic merit. There have been several attempts to quantify market power with much of the work focused separately on either real power or reactive power. This paper addresses a new possibility for a market participant to exploit an opportunity to increase revenue by gaming both real and reactive markets.

Introduction: Electric Power Systems Restructuring :Engineering, Economics and Policy Track

Abstract: This track seeks to explore methods at the frontier of understanding the restructuring of electric power system worldwide. It will focus on engineering, economics and policy issues that are at the forefront of current thinking.

A Diffusion-Model-Based Supply-Side Offer Agent

Abstract: Summary form only given. World-wide energy markets have been on a path toward deregulation for several decades. These markets have proven to be difficult to design and run because of their repetitive nature and the externalities provided by reliable grid operation. In a deregulated market environment, our experiments suggest that market participants will pursue their own profit maximizing objective rather than use an objective that reflects social benefit. Multi-agent simulation is useful for gaining insights into market participant behavior under various rules. In this way market rules can be tested for efficacy and efficiency. In this paper an agent based on a double layer diffusion model developed elsewhere is tested and its effectiveness reported.