Showing papers by "Robert J. Thomas published in 2011"

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

Abstract: 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.

Malicious Data Attacks on the Smart Grid

Abstract: Malicious attacks against power systems are investigated, in which an adversary controls a set of meters and is able to alter the measurements from those meters. Two regimes of attacks are considered. The strong attack regime is where the adversary attacks a sufficient number of meters so that the network state becomes unobservable by the control center. For attacks in this regime, the smallest set of attacked meters capable of causing network unobservability is characterized using a graph theoretic approach. By casting the problem as one of minimizing a supermodular graph functional, the problem of identifying the smallest set of vulnerable meters is shown to have polynomial complexity. For the weak attack regime where the adversary controls only a small number of meters, the problem is examined from a decision theoretic perspective for both the control center and the adversary. For the control center, a generalized likelihood ratio detector is proposed that incorporates historical data. For the adversary, the trade-off between maximizing estimation error at the control center and minimizing detection probability of the launched attack is examined. An optimal attack based on minimum energy leakage is proposed.

Malicious data attack on real-time electricity market

Abstract: Malicious data attacks to the real-time electricity market are studied. In particular, an adversary launches an attack by manipulating data from a set of meters with the goal of influencing revenues of a real-time market. The adversary must deal with the tradeoff between avoiding being detected by the control center and making maximum profit from the real time market. Optimal attacking strategy is obtained through an optimization of a quasi-concave objective function. It is shown that the probability of detection of optimal attack will always be less than 0.5. Attack performance is evaluated using simulations on the IEEE 14-bus system.

A Privacy-Aware Architecture for Demand Response Systems

Abstract: We explore the privacy issues implicated by the development of demand response systems. We begin by highlighting the invasive nature of fine-granularity power consumption data, showing that the data collected by Advanced Metering Infrastructure (AMI) reveals detailed information about behavior within the home. We then show how privacy-aware design principles lead to novel system architectures that realize the benefits of demand response without requiring that AMI data be centrally collected. The resulting systems avoid both harm to subscribers and the potential need to scrap AMI-based demand response efforts in the face of public outcry. We also show that Trusted Platform Modules can be used to develop privacy-sensitive metering infrastructure.

Information infrastructure for cellular load management in green power delivery systems

Abstract: In this paper, we outline a specific communication framework to support a novel demand management program on the edge of the power distribution network. We suggest a model where the arrival process of the smart appliances is made visible to control centers, forming a cellular Microgrid infrastructure, through Home Energy Management Systems (HEMS). These appliances then wait to receive an authorization message before starting to function. The cell control center uses this information to choose an optimal departure process that serves the waiting appliances while minimizing its operational costs. The described information exchange strategy gives the cell the ability to better match the load to the available green energy supply and its day ahead energy bid. We show that this model will allow to increase the integration of intermittent resources in the power grid, with modest communication rate requirements.1

Direct load management of electric vehicles

Abstract: Electrical Vehicles are gaining increasing attention, due to the opportunities and challenges they present for the energy market. On the one hand, they will allow to drastically reduce the need for oil; on the other hand they may require a significant shift in the day to day management of the electricity generation. This paper is concerned with finding appropriate models for residential load in light of a widespread penetration of electric vehicles. The analysis is aimed at finding a SmartGrid solution that would enable us to optimize the generation dispatch in real time and allow to plug cars in any SmartGrid enabled plug. The key idea is to discriminate between regular load and the load due to the EVs, gathering in real time aggregate information about the sensed EV arrivals and their associated charging times in a demand matrix, that can be readily used to optimize the dispatch, while updating without real time constraints the billing record for the EV.

Scheduling of Energy Storage Systems with Geographically Distributed Renewables

Abstract: Renewable energy sources (RES) are very likely to continue the upward capacity trend witnessed in the past years. The reasons for adoption are varied and respond to both market pressures, influence of government intervention and a raised awareness of the consequences on the environment of the current generation fleet. The change from dispatch able generation to an environment in which Independent System Operators (ISO's), Regional Transmission Operators (RTO's) and consumers, among others, accommodate the demand to the available generation, requires fundamental changes in the way the system is managed. Also, to better harness the energy from renewable sources, both new methods and technologies need to be adopted, counteracting for the sometimes unpredictable behavior of these sources. This study proposes a method with multi-period optimization to help prescribe the optimal placement and usage of RES and Energy Storage Systems (ESS) with full information of the system. Four cases are analyzed in their dispatches, as well as the benefits to the participants in the wholesale market, for a reduced 30-bus network. While the data requirements are high, and the use of a reduced system limits the applications herein proposed, the policy implications from the results obtained provide useful insights into an ongoing debate regarding on how to direct investment in the electrical system.

Integrating Wind Power: Can Controllable Load Substitute for Transmission Upgrades?

Abstract: The Cornell SuperOPF is used to illustrate how the system costs can be determined for a reliable network (the amount of conventional generating capacity needed to maintain System Adequacy is determined endogenously). Eight cases are studied to illustrate the effects of geographical distribution, ramping costs and load response to customers payment in the wholesale market, and the amount of potential wind generation that is dispatched. The proposed regulatory changes for electricity markets are 1) to establish a new market for ramping services, 2) to aggregate the loads of customers on a distribution network so that they can be represented as a single wholesale customer on the bulk-power transmission network and 3) to make use of controllable load to mitigate the variability of wind generation as an alternative to upgrading the capacity of the transmission network. The cost of ramping reduces the amount of potential wind generation that is dispatched because of the inherent variability of wind speeds. The analysis evaluates whether the ability to dispatch some load that is not time-sensitive, such as charging the batteries in electric vehicles over night above the minimum usage requirement, can be an effective way to use more of the potential wind generation without upgrading the transfer capacity of a transmission network. The expectation is that more wind generation can be dispatched at times when load is relatively low and congestion on the network is not a major limitation.

The hidden system costs of wind generation in a deregulated electricity market

Abstract: Earlier research has shown that adding wind capacity to a network can lower the total annual operating cost of meeting a given pattern of loads by displacing conventional generation. At the same time, the variability of wind generation and the need for higher levels of reserve generating capacity to maintain reliability standards impose additional costs on the system that should not be ignored. The important implication for regulators is that the capacity payments [“missing money”] for eachMW of peak system load is now much higher. Hence, the economic benefits to a network of using storage, controllable load and other mechanisms to reduce the peak system load will be higher with high penetrations of wind generation. These potential benefits are illustrated in a case study using a test network and a security constrained OPF with endogenous reserves (SuperOPF). The capabilities of the SuperOPF provide a consistent economic framework for evaluating Operating Reliability in real-time markets and System Adequacy for planning purposes. The scenarios considered make it possible to determine 1) the amount of conventional generating capacity needed to meet the peak system load and maintain System Adequacy, and the amount of wind dispatched, 2) total payments by customers in the Wholesale Market, and the amount of missing money paid to generators to maintain their Financial Adequacy, 3) changes in the congestion rents for transmission that are collected by the system operator, and finally, 4) the total annual system costs paid by customers directly in the Wholesale Market and, indirectly, as missing money. The results show that the benefits (i.e. the reduction in the total annual system costs) from making an investment in wind capacity and/of upgrading a tie line are very sensitive to 1) how much of the inherent variability of wind generation is mitigated, and 2) how the missing money paid to conventional generators is determined (e.g. comparing a regulated market with a deregulated market).

Integration of Stochastic Power Generation, Geographical Averaging and Load Response

Abstract: The objective of this paper is to analyze how the variability of wind affects optimal dispatches and reserves in a daily optimization cycle. The Cornell SuperOPF1 is used to illustrate how the system costs can be determined for a reliable network (the amount of conventional generating capacity needed to maintain System Adequacy is determined endogenously). Eight cases are studied to illustrate the effects of geographical distribution, ramping costs and load response to customers payment in the wholesale market, and the amount of potential wind generation that is dispatched. The results in this paper use a typical daily pattern of load and capture the cost of ramping by including additions to the operating costs of the generating units associated with the hour-to-hour changes in their optimal dispatch. The proposed regulatory changes for electricity markets are 1) to establish a new market for ramping services, 2) to aggregate the loads of customers on a distribution network so that they can be represented as a single wholesale customer on the bulk-power transmission network and 3) to make use of controllable load and geographical distribution of wind to mitigate the variability of wind generation as an alternative to upgrading the capacity of the transmission network.