A Data Envelopment Analysis (DEA)-Based Model for Power Interruption Cost Estimation for Industrial Companies

In this paper, a new model based on Data Envelopment Analysis (DEA) and Inverse Data Envelopment Analysis (IDEA) is presented for estimating the effect of electricity on the output of industrial companies. To this end, the effect of electricity deviation, which serves as one input that can influence a manufacturing company's final product, is evaluated. Intuitively, it is known that a direct relationship exists between electricity consumption and the output of the manufacturing company. However, finding a function that accurately represents this relationship is not easy. To check the applicability of the proposed method, it is tested on data from eight major vehicle manufacturing companies. In this model, labor hours, electrical energy consumption, and the value of raw materials are used as inputs, and the sales value is used as the proxy for the output of the company. These input and output data are used to find the efficiency of each company. Then, by changing the electricity consumption level, the output changes are derived. To calculate the outage cost, the deviation of the output is divided by the deviation of the electricity consumption, and the outage cost is estimated.Comment: IEEE ISGT 201

Reliability Assessment of Smart Grid Considering Cyber-Power Interdependencies

Smart grid initiatives are becoming more and more achievable through the use of information infrastructures that feature peer-to-peer communication, monitoring, protection and automated control. The analysis of smart grid operation requires considering the reliability of the cyber network as it is neither invulnerable nor failure free. The objective of this dissertation is to categorize interdependencies between cyber and power networks and propose mathematical evaluation models to calculate the reliability of the power network when considering failures of the cyber network. This study categorizes interdependencies between cyber and power networks into direct and indirect. In this research direct interdependencies among cyber-power networks is studied and the concept of state mapping is proposed to map the failures in the cyber network to the failures of the power network. The impact of indirect interdependencies on the reliability of power system is different and more complicated than that of direct interdependencies. In this dissertation, various aspects of smart monitoring, as an application of indirect interdependency, are discussed and a mathematical model to assess its impact on power grid reliability is proposed. Based on a multiple-state Markov chain model, the failure and repair rates of power components with and without monitoring provisions are determined and compared. In addition, to model indirect interdependencies between cyber and power networks, the concept and formulations of state updating are proposed to update the probability of states due to failures in the cyber network. Furthermore, in order to evaluate the impact of both direct and indirect cyberpower interdependencies on the reliability indices, two optimization models are introduced to maximize the data connection in the cyber network and minimize the load shedding in the power network

Power system reliability enhancement considering smart monitoring

With improvements in smart sensing and digital instrumentation technologies, small, low-cost sensors have been installed in power networks, thus providing new opportunities for smart monitoring. Smart monitoring consists of analog/digital sensors, measurement units, control devices, and protective relays inside a digital communication network working together to gather local information about the power grid, to be recorded in the servers and to demonstrate human machine interfaces (HMI). To keep a power system operating reliably, it is necessary to continuously monitor and indicate crucial points of the power network. This paper introduces various aspects of power system monitoring and indication and proposes a mathematic model to numerically assess the positive effects of smart monitoring on the power system\u27s reliability. Based on the Markov model, the formulation used to calculate the updated failure and repair rates of the power equipment is extracted

Stochastic active and reactive power dispatch in electricity markets with wind power volatility

This paper proposes a stochastic multiobjective optimization algorithm for simultaneous active and reactive power dispatch in electricity markets with wind power volatility. Considering only economic issues during market clearing will achieve minimum system payment but may not yield an efficient and secure system operating point. Therefore, maximizing expected voltage security margin and minimizing transmission congestion probability are incorporated into the proposed multiobjective function. To demonstrate the effectiveness of the proposed algorithm, five average deviation indices and a spider diagram are introduced to evaluate the proposed algorithm. © 2012 IEEE

Distributed transmission expansion planning in multi-area electric power systems

This paper presents a distributed transmission expansion planning (TEP) approach for multi-area power systems. A local TEP is formulated for each area with respect to local characteristics of that area as well as power flow in existing and candidate tie-lines that interconnect the area with its neighbors. Based on the auxiliary problem principle, a distributed decision-making algorithm is presented to coordinates the local TEP problems and find an overall solution for the entire power system. Limited information, only related to the tie-lines and not local lines, is exchanged between transmission areas, so that information privacy of the planners is respected. Numerical results on the Garver Test system show the effectiveness of the proposed distributed TEP algorithm

Optimal operation of distribution grids: A system of systems framework

There are many entities in the modern power systems that collaborate together to operate the system in a secure and reliable manner. Each of the entities is managed and operated autonomously and intends to increase its own benefit. This paper presents a system of systems (SOS) framework for optimal operation of distribution grids. The distribution grids are modeled as the SOS utilized by distribution companies (DISCOs) collaborating with different loads and microgrids. In this framework, the DISCO and microgrids are regarded as the individual systems which are independently managed and operated aiming at maximizing their own profit. Considering the correlation among the independent systems, the ORIGIN and CLIENT data are introduced and the relationship table is constructed to represent the correlated variables between the entities. The relationship table indicates the sequences of the optimization problems for the entities. The proposed framework is applied to a typical distribution grid and results are discussed. © 2013 IEEE

Decentralized Implementation of Unit Commitment with Analytical Target Cascading: A Parallel Approach

This paper presents a decentralized solution algorithm for network-constrained unit commitment (NCUC) in multiregional power systems. The proposed algorithm is based on our previous work in which a local NCUC was formulated for each control entity (i.e., region) and an analytical target cascading (ATC) based distributed but partially parallelized algorithm requiring a central coordinator was presented. The primary objective of this paper is to present a decentralized approach that relaxes the need for any form of central coordinator in ATC and allows fully parallelized solutions of the local NCUCs. To achieve this objective, we formulate a bilevel optimization problem for each control entity. While the upper level solves the NCUC problem of the control entity, the lower level seeks to coordinate the control entity with its neighboring regions. The lower level is a convex optimization, which can be further replaced in the upper level problem by the Karush-Kuhn-Tucker conditions. The control entities communicate directly with each other and synchronously solve their local NCUCs. Having no need for any form of central coordinator, the proposed algorithm is potentially less vulnerable to cyber-attacks and communication failures than the distributed methods utilizing a coordinator

Impacts of information and communication failures on optimal power system operation

This paper focuses on recognizing the ways in which information and communication network failures cause a loss of control over a power system\u27s operation. Using numerical evidence, it also assesses the specific impacts of such failures on the optimal operation of a power system. Optimal power flow (OPF) is the most prominent method for implementing optimal operation. In OPF, it is assumed that all power appliances are accessible through the communication and information network, and all power devices are set as the output of OPF; nevertheless, the loss of control and operation of the power system\u27s apparatuses may seriously impact the real-time operation of the bulk power system. The control and operation of the power system is dedicated to a modern communication network, in that intelligent electronic devices (IEDs) are connected to apparatuses of the power network. Data communication among IEDs enables both automatic and remote manual control of the power system. Although such a network offers new advantages and possibilities not previously achievable, it intrinsically has its own source of failures, such as the failure of physical components, loss of integrity, software failures and data communication faults. © 2013 IEEE

Timeframe capacity factor reliability model for isolated microgrids with renewable energy resources

In recent decades, the integration of renewable energy resources in the power system has grown rapidly around the globe. Using renewable energy resources in microgrids is appropriate, especially where access to public power energy is impossible or costly. This paper presents a novel method for assessing the reliability of microgrids, taking into account the probabilistic behavior of solar and wind power. In this model, the study period is divided into different Timeframes (TFs), and for each TF, the timeframe capacity factor (TFCF) is considered for each renewable energy resource. To assess the microgrid\u27s reliability, the Loss of Load Expectation (LOLP) and Expected Energy Not Supplied (EENS) are calculated. Compared to existing probabilistic models, the prerequisites data and running time for reliability assessment is significantly reduced when using the proposed method. These two virtues suit the model well for optimization-based planning problems. © 2012 IEEE