Visible to the public Biblio

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2020-12-21
Cheng, Z., Chow, M.-Y..  2020.  An Augmented Bayesian Reputation Metric for Trustworthiness Evaluation in Consensus-based Distributed Microgrid Energy Management Systems with Energy Storage. 2020 2nd IEEE International Conference on Industrial Electronics for Sustainable Energy Systems (IESES). 1:215–220.
Consensus-based distributed microgrid energy management system is one of the most used distributed control strategies in the microgrid area. To improve its cybersecurity, the system needs to evaluate the trustworthiness of the participating agents in addition to the conventional cryptography efforts. This paper proposes a novel augmented reputation metric to evaluate the agents' trustworthiness in a distributed fashion. The proposed metric adopts a novel augmentation method to substantially improve the trust evaluation and attack detection performance under three typical difficult-to-detect attack patterns. The proposed metric is implemented and validated on a real-time HIL microgrid testbed.
2020-11-20
Semwal, S., Badoni, M., Saxena, N..  2019.  Smart Meters for Domestic Consumers: Innovative Methods for Identifying Appliances using NIALM. 2019 Women Institute of Technology Conference on Electrical and Computer Engineering (WITCON ECE). :81—90.
A country drives by their people and the electricity energy, the availability of the electricity power reflects the strength of that country. All most everything depends on the electricity energy, So it is become very important that we use the available energy very efficiently, and here the energy management come in the picture and Non Intrusive appliance Load monitoring (NIALM) is the part of energy management, in which the energy consumption by the particular load is monitored without any intrusion of wire/circuit. In literature, NIALM has been discussed as a monitoring process for conservation of energy using single point sensing (SPS) for extraction of aggregate signal of the appliances' features, ignoring the second function of demand response (DR) assuming that it would be manual or sensor-based. This assumption is not implementable in developing countries like India, because of requirement of extra cost of sensors, and privacy concerns. Surprisingly, despite decades of research on NIALM, none of the suggested procedures has resulted in commercial application. This paper highlights the causes behind non- commercialization, and proposes a viable and easy solution worthy of commercial exploitation both for monitoring and DR management for outage reduction in respect of Indian domestic consumers. Using a approach of multi point sensing (MPS), combined with Independent Component Analysis (ICA), experiments has been done in laboratory environment and CPWD specification has been followed.
2020-09-18
Chakrabarty, Shantanu, Sikdar, Biplab.  2019.  A Methodology for Detecting Stealthy Transformer Tap Command Injection Attacks in Smart Grids. 2019 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm). :1—6.
On-Load Tap Changing transformers are a widely used voltage regulation device. In the context of modern or smart grids, the control signals, i.e., the tap change commands are sent through SCADA channels. It is well known that the power system SCADA networks are prone to attacks involving injection of false data or commands. While false data injection is well explored in existing literature, attacks involving malicious control signals/commands are relatively unexplored. In this paper, an algorithm is developed to detect a stealthily introduced malicious tap change command through a compromised SCADA channel. This algorithm is based on the observation that a stealthily introduced false data or command masks the true estimation of only a few state variables. This leaves the rest of the state variables to show signs of a change in system state brought about by the attack. Using this observation, an index is formulated based on the ratios of injection or branch currents to voltages of the terminal nodes of the tap changers. This index shows a significant increase when there is a false tap command injection, resulting in easy classification from normal scenarios where there is no attack. The algorithm is computationally light, easy to implement and reliable when tested extensively on several tap changers placed in an IEEE 118-bus system.
2020-09-14
Widergren, Steve, Melton, Ron, Khandekar, Aditya, Nordman, Bruce, Knight, Mark.  2019.  The Plug-and-Play Electricity Era: Interoperability to Integrate Anything, Anywhere, Anytime. IEEE Power and Energy Magazine. 17:47–58.
The inforrmation age continues to transform the mechanics of integrating electric power devices and systems, from coordinated operations based purely on the physics of electric power engineering to an increasing blend of power with information and communication technology. Integrating electric system components is not just about attaching wires. It requires the connection of computer-based automation systems to associated sensing and communication equipment. The architectural impacts are significant. Well-considered and commonly held concepts, principles, and organizational structures continue to emerge to address the complexity of the integrated operational challenges that drive our society to expect more flexibility in configuring the electric power system, while simultaneously achieving greater efficiency, reliability, and resilience. Architectural concepts, such as modularity and composability, contribute to the creation of structures that enable the connection of power system equipment characterized by clearly defined interfaces consisting of physical and cyberlinks. The result of successful electric power system component connection is interoperation: the discipline that drives integration to be simple and reliable.
2020-03-02
Zhao, Min, Li, Shunxin, Xiao, Dong, Zhao, Guoliang, Li, Bo, Liu, Li, Chen, Xiangyu, Yang, Min.  2019.  Consumption Ability Estimation of Distribution System Interconnected with Microgrids. 2019 IEEE International Conference on Energy Internet (ICEI). :345–350.
With fast development of distributed generation, storages and control techniques, a growing number of microgrids are interconnected with distribution networks. Microgrid capacity that a local distribution system can afford, is important to distribution network planning and microgrids well-organized integration. Therefore, this paper focuses on estimating consumption ability of distribution system interconnected with microgrids. The method to judge rationality of microgrids access plan is put forward, and an index system covering operation security, power quality and energy management is proposed. Consumption ability estimation procedure based on rationality evaluation and interactions is built up then, and requirements on multi-scenario simulation are presented. Case study on a practical distribution system design with multi-microgrids guarantees the validity and reasonableness of the proposed method and process. The results also indicate construction and reinforcement directions for the distribution network.
2020-02-10
Naseem, Faraz, Babun, Leonardo, Kaygusuz, Cengiz, Moquin, S.J., Farnell, Chris, Mantooth, Alan, Uluagac, A. Selcuk.  2019.  CSPoweR-Watch: A Cyber-Resilient Residential Power Management System. 2019 International Conference on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, Physical and Social Computing (CPSCom) and IEEE Smart Data (SmartData). :768–775.

Modern Energy Management Systems (EMS) are becoming increasingly complex in order to address the urgent issue of global energy consumption. These systems retrieve vital information from various Internet-connected resources in a smart grid to function effectively. However, relying on such resources results in them being susceptible to cyber attacks. Malicious actors can exploit the interconnections between the resources to perform nefarious tasks such as modifying critical firmware, sending bogus sensor data, or stealing sensitive information. To address this issue, we propose a novel framework that integrates PowerWatch, a solution that detects compromised devices in the smart grid with Cyber-secure Power Router (CSPR), a smart energy management system. The goal is to ascertain whether or not such a device has operated maliciously. To achieve this, PowerWatch utilizes a machine learning model that analyzes information from system and library call lists extracted from CSPR in order to detect malicious activity in the EMS. To test the efficacy of our framework, a number of unique attack scenarios were performed on a realistic testbed that comprises functional versions of CSPR and PowerWatch to monitor the electrical environment for suspicious activity. Our performance evaluation investigates the effectiveness of this first-of-its-kind merger and provides insight into the feasibility of developing future cybersecure EMS. The results of our experimental procedures yielded 100% accuracy for each of the attack scenarios. Finally, our implementation demonstrates that the integration of PowerWatch and CSPR is effective and yields minimal overhead to the EMS.

2020-01-20
Waqar, Ali, Hu, Junjie, Mushtaq, Muhammad Rizwan, Hussain, Hadi, Qazi, Hassaan Aziz.  2019.  Energy Management in an Islanded Microgrid: A Consensus Theory Approach. 2019 2nd International Conference on Computing, Mathematics and Engineering Technologies (iCoMET). :1–6.

This article presents a consensus based distributed energy management optimization algorithm for an islanded microgrid. With the rapid development of renewable energy and distributed generation (DG) energy management is becoming more and more distributed. To solve this problem a multi-agent system based distributed solution is designed in this work which uses lambda-iteration method to solve optimization problem. Moreover, the algorithm is fully distributed and transmission losses are also considered in the modeling process which enhanced the practicality of proposed work. Simulations are performed for different cases on 8-bus microgrid to show the effectiveness of algorithm. Moreover, a scalability test is performed at the end to further justify the expandability performance of algorithm for more advanced networks.

2019-06-24
You, Y., Li, Z., Oechtering, T. J..  2018.  Optimal Privacy-Enhancing And Cost-Efficient Energy Management Strategies For Smart Grid Consumers. 2018 IEEE Statistical Signal Processing Workshop (SSP). :826–830.

The design of optimal energy management strategies that trade-off consumers' privacy and expected energy cost by using an energy storage is studied. The Kullback-Leibler divergence rate is used to assess the privacy risk of the unauthorized testing on consumers' behavior. We further show how this design problem can be formulated as a belief state Markov decision process problem so that standard tools of the Markov decision process framework can be utilized, and the optimal solution can be obtained by using Bellman dynamic programming. Finally, we illustrate the privacy-enhancement and cost-saving by numerical examples.

Bessa, Ricardo J., Rua, David, Abreu, Cláudia, Machado, Paulo, Andrade, José R., Pinto, Rui, Gonçalves, Carla, Reis, Marisa.  2018.  Data Economy for Prosumers in a Smart Grid Ecosystem. Proceedings of the Ninth International Conference on Future Energy Systems. :622–630.

Smart grids technologies are enablers of new business models for domestic consumers with local flexibility (generation, loads, storage) and where access to data is a key requirement in the value stream. However, legislation on personal data privacy and protection imposes the need to develop local models for flexibility modeling and forecasting and exchange models instead of personal data. This paper describes the functional architecture of an home energy management system (HEMS) and its optimization functions. A set of data-driven models, embedded in the HEMS, are discussed for improving renewable energy forecasting skill and modeling multi-period flexibility of distributed energy resources.

2019-03-28
He, Z., Pan, S., Lin, D..  2018.  PMDA: Privacy-Preserving Multi-Functional Data Aggregation Without TTP in Smart Grid. 2018 17th IEEE International Conference On Trust, Security And Privacy In Computing And Communications/ 12th IEEE International Conference On Big Data Science And Engineering (TrustCom/BigDataSE). :1107-1114.

In the smart grid, residents' electricity usage needs to be periodically measured and reported for the purpose of better energy management. At the same time, real-time collection of residents' electricity consumption may unfavorably incur privacy leakage, which has motivated the research on privacy-preserving aggregation of electricity readings. Most previous studies either rely on a trusted third party (TTP) or suffer from expensive computation. In this paper, we first reveal the privacy flaws of a very recent scheme pursing privacy preservation without relying on the TTP. By presenting concrete attacks, we show that this scheme has failed to meet the design goals. Then, for better privacy protection, we construct a new scheme called PMDA, which utilizes Shamir's secret sharing to allow smart meters to negotiate aggregation parameters in the absence of a TTP. Using only lightweight cryptography, PMDA efficiently supports multi-functional aggregation of the electricity readings, and simultaneously preserves residents' privacy. Theoretical analysis is provided with regard to PMDA's security and efficiency. Moreover, experimental data obtained from a prototype indicates that our proposal is efficient and feasible for practical deployment.

2019-02-25
Al-Waisi, Zainab, Agyeman, Michael Opoku.  2018.  On the Challenges and Opportunities of Smart Meters in Smart Homes and Smart Grids. Proceedings of the 2Nd International Symposium on Computer Science and Intelligent Control. :16:1-16:6.

Nowadays, electricity companies have started applying smart grid in their systems rather than the conventional electrical grid (manual grid). Smart grid produces an efficient and effective energy management and control, reduces the cost of production, saves energy and it is more reliable compared to the conventional grid. As an advanced energy meter, smart meters can measure the power consumption as well as monitor and control electrical devices. Smart meters have been adopted in many countries since the 2000s as they provide economic, social and environmental benefits for multiple stakeholders. The design of smart meter can be customized depending on the customer and the utility company needs. There are different sensors and devices supported by dedicated communication infrastructure which can be utilized to implement smart meters. This paper presents a study of the challenges associated with smart meters, smart homes and smart grids as an effort to highlight opportunities for emerging research and industrial solutions.

2018-09-05
Zhong, Q., Blaabjerg, F., Cecati, C..  2017.  Power-Electronics-Enabled Autonomous Power Systems. IEEE Transactions on Industrial Electronics. 64:5904–5906.

The eleven papers in this special section focus on power electronics-enabled autonomous systems. Power systems are going through a paradigm change from centralized generation to distributed generation and further onto smart grid. Millions of relatively small distributed energy resources (DER), including wind turbines, solar panels, electric vehicles and energy storage systems, and flexible loads are being integrated into power systems through power electronic converters. This imposes great challenges to the stability, scalability, reliability, security, and resiliency of future power systems. This section joins the forces of the communities of control/systems theory, power electronics, and power systems to address various emerging issues of power-electronics-enabled autonomous power systems, paving the way for large-scale deployment of DERs and flexible loads.

2018-03-05
Shelar, D., Sun, P., Amin, S., Zonouz, S..  2017.  Compromising Security of Economic Dispatch in Power System Operations. 2017 47th Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN). :531–542.

Power grid operations rely on the trustworthy operation of critical control center functionalities, including the so-called Economic Dispatch (ED) problem. The ED problem is a large-scale optimization problem that is periodically solved by the system operator to ensure the balance of supply and load while maintaining reliability constraints. In this paper, we propose a semantics-based attack generation and implementation approach to study the security of the ED problem.1 Firstly, we generate optimal attack vectors to transmission line ratings to induce maximum congestion in the critical lines, resulting in the violation of capacity limits. We formulate a bilevel optimization problem in which the attacker chooses manipulations of line capacity ratings to maximinimize the percentage line capacity violations under linear power flows. We reformulate the bilevel problem as a mixed integer linear program that can be solved efficiently. Secondly, we describe how the optimal attack vectors can be implemented in commercial energy management systems (EMSs). The attack explores the dynamic memory space of the EMS, and replaces the true line capacity ratings stored in data regions with the optimal attack vectors. In contrast to the well-known false data injection attacks to control systems that require compromising distributed sensors, our approach directly implements attacks to the control center server. Our experimental results on benchmark power systems and five widely utilized EMSs show the practical feasibility of our attack generation and implementation approach.

Shelar, D., Sun, P., Amin, S., Zonouz, S..  2017.  Compromising Security of Economic Dispatch in Power System Operations. 2017 47th Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN). :531–542.

Power grid operations rely on the trustworthy operation of critical control center functionalities, including the so-called Economic Dispatch (ED) problem. The ED problem is a large-scale optimization problem that is periodically solved by the system operator to ensure the balance of supply and load while maintaining reliability constraints. In this paper, we propose a semantics-based attack generation and implementation approach to study the security of the ED problem.1 Firstly, we generate optimal attack vectors to transmission line ratings to induce maximum congestion in the critical lines, resulting in the violation of capacity limits. We formulate a bilevel optimization problem in which the attacker chooses manipulations of line capacity ratings to maximinimize the percentage line capacity violations under linear power flows. We reformulate the bilevel problem as a mixed integer linear program that can be solved efficiently. Secondly, we describe how the optimal attack vectors can be implemented in commercial energy management systems (EMSs). The attack explores the dynamic memory space of the EMS, and replaces the true line capacity ratings stored in data regions with the optimal attack vectors. In contrast to the well-known false data injection attacks to control systems that require compromising distributed sensors, our approach directly implements attacks to the control center server. Our experimental results on benchmark power systems and five widely utilized EMSs show the practical feasibility of our attack generation and implementation approach.

Shelar, D., Sun, P., Amin, S., Zonouz, S..  2017.  Compromising Security of Economic Dispatch in Power System Operations. 2017 47th Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN). :531–542.
Power grid operations rely on the trustworthy operation of critical control center functionalities, including the so-called Economic Dispatch (ED) problem. The ED problem is a large-scale optimization problem that is periodically solved by the system operator to ensure the balance of supply and load while maintaining reliability constraints. In this paper, we propose a semantics-based attack generation and implementation approach to study the security of the ED problem.1 Firstly, we generate optimal attack vectors to transmission line ratings to induce maximum congestion in the critical lines, resulting in the violation of capacity limits. We formulate a bilevel optimization problem in which the attacker chooses manipulations of line capacity ratings to maximinimize the percentage line capacity violations under linear power flows. We reformulate the bilevel problem as a mixed integer linear program that can be solved efficiently. Secondly, we describe how the optimal attack vectors can be implemented in commercial energy management systems (EMSs). The attack explores the dynamic memory space of the EMS, and replaces the true line capacity ratings stored in data regions with the optimal attack vectors. In contrast to the well-known false data injection attacks to control systems that require compromising distributed sensors, our approach directly implements attacks to the control center server. Our experimental results on benchmark power systems and five widely utilized EMSs show the practical feasibility of our attack generation and implementation approach.
2018-02-21
Zhao, C., He, J., Cheng, P., Chen, J..  2017.  Privacy-preserving consensus-based energy management in smart grid. 2017 IEEE Power Energy Society General Meeting. :1–5.

This paper investigates the privacy-preserving problem of the distributed consensus-based energy management considering both generation units and responsive demands in smart grid. First, we reveal the private information of consumers including the electricity consumption and the sensitivity of the electricity consumption to the electricity price can be disclosed without any privacy-preserving strategy. Then, we propose a privacy-preserving algorithm to preserve the private information of consumers through designing the secret functions, and adding zero-sum and exponentially decreasing noises. We also prove that the proposed algorithm can preserve the privacy while keeping the optimality of the final state and the convergence performance unchanged. Extensive simulations validate the theoretical results and demonstrate the effectiveness of the proposed algorithm.

2018-02-06
Ashok, A., Sridhar, S., Rice, M., Smith, J..  2017.  Substation Monitoring to Enhance Situational Awareness \#x2014; Challenges and Opportunities. 2017 IEEE Power Energy Society Innovative Smart Grid Technologies Conference (ISGT). :1–5.

Situational awareness during sophisticated cyber attacks on the power grid is critical for the system operator to perform suitable attack response and recovery functions to ensure grid reliability. The overall theme of this paper is to identify existing practical issues and challenges that utilities face while monitoring substations, and to suggest potential approaches to enhance the situational awareness for the grid operators. In this paper, we provide a broad discussion about the various gaps that exist in the utility industry today in monitoring substations, and how those gaps could be addressed by identifying the various data sources and monitoring tools to improve situational awareness. The paper also briefly describes the advantages of contextualizing and correlating substation monitoring alerts using expert systems at the control center to obtain a holistic systems-level view of potentially malicious cyber activity at the substations before they cause impacts to grid operation.

2015-05-05
Shahgoshtasbi, D., Jamshidi, M.M..  2014.  A New Intelligent Neuro #x2013;Fuzzy Paradigm for Energy-Efficient Homes. Systems Journal, IEEE. 8:664-673.

Demand response (DR), which is the action voluntarily taken by a consumer to adjust amount or timing of its energy consumption, has an important role in improving energy efficiency. With DR, we can shift electrical load from peak demand time to other periods based on changes in price signal. At residential level, automated energy management systems (EMS) have been developed to assist users in responding to price changes in dynamic pricing systems. In this paper, a new intelligent EMS (iEMS) in a smart house is presented. It consists of two parts: a fuzzy subsystem and an intelligent lookup table. The fuzzy subsystem is based on its fuzzy rules and inputs that produce the proper output for the intelligent lookup table. The second part, whose core is a new model of an associative neural network, is able to map inputs to desired outputs. The structure of the associative neural network is presented and discussed. The intelligent lookup table takes three types of inputs that come from the fuzzy subsystem, outside sensors, and feedback outputs. Whatever is trained in this lookup table are different scenarios in different conditions. This system is able to find the best energy-efficiency scenario in different situations.