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2021-06-24
Maneebang, Kotchakorn, Methapatara, Kanokpol, Kudtongngam, Jasada.  2020.  A Demand Side Management Solution: Fully Automated Demand Response using OpenADR2.0b Coordinating with BEMS Pilot Project. 2020 International Conference on Smart Grids and Energy Systems (SGES). :30–35.
Per the National Energy Policy, Demand Side Management (DSM) is one of the energy conservations that performs a function to manage electric power of demand-side resources. One of the DSM solutions is a demand response program, which is a part of Thailand Smart Grid Action Plan 2017 - 2021. Demand response program such as peak demand reduction plays a role in both the management of the electricity crisis and enhance energy security. This paper presents a pilot project for a fully automated demand response program at MEA Rat Burana District Office. The system is composed of a Building Energy Management System (BEMS) with Demand Response Client gateway and 5 energy controllers at the air conditioner by using the OpenADR2.0b protocol. Also, this concept leads to automatic or semi-automatic demand response program in the future. The result shows the total energy consumption reduction for air conditioners by 53.5%. The future works to be carried out are to implement into other MEA District Office such as Khlong Toei, Yan Nawa and Bang Khun Thian and to test with a Load Aggregator Management System (LAMS).
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.
2019-11-19
Nasiruzzaman, A. B. M., Akter, M. N., Mahmud, M. A., Pota, H. R..  2018.  Network Theory Based Power Grid Criticality Assessment. 2018 IEEE International Conference on Power Electronics, Drives and Energy Systems (PEDES). :1-5.

A process of critical transmission lines identification in presented here. The criticality is based on network flow, which is essential for power grid connectivity monitoring as well as vulnerability assessment. The proposed method can be utilized as a supplement of traditional situational awareness tool in the energy management system of the power grid control center. At first, a flow network is obtained from topological as well as functional features of the power grid. Then from the duality property of a linear programming problem, the maximum flow problem is converted to a minimum cut problem. Critical transmission lines are identified as a solution of the dual problem. An overall set of transmission lines are identified from the solution of the network flow problem. Simulation of standard IEEE test cases validates the application of the method in finding critical transmission lines of the power grid.

2017-05-19
Paridari, Kaveh, El-Din Mady, Alie, La Porta, Silvio, Chabukswar, Rohan, Blanco, Jacobo, Teixeira, André, Sandberg, Henrik, Boubekeur, Menouer.  2016.  Cyber-physical-security Framework for Building Energy Management System. Proceedings of the 7th International Conference on Cyber-Physical Systems. :18:1–18:9.

Energy management systems (EMS) are used to control energy usage in buildings and campuses, by employing technologies such as supervisory control and data acquisition (SCADA) and building management systems (BMS), in order to provide reliable energy supply and maximise user comfort while minimising energy usage. Historically, EMS systems were installed when potential security threats were only physical. Nowadays, EMS systems are connected to the building network and as a result directly to the outside world. This extends the attack surface to potential sophisticated cyber-attacks, which adversely impact EMS operation, resulting in service interruption and downstream financial implications. Currently, the security systems that detect attacks operate independently to those which deploy resiliency policies and use very basic methods. We propose a novel EMS cyber-physical-security framework that executes a resilient policy whenever an attack is detected using security analytics. In this framework, both the resilient policy and the security analytics are driven by EMS data, where the physical correlations between the data-points are identified to detect outliers and then the control loop is closed using an estimated value in place of the outlier. The framework has been tested using a reduced order model of a real EMS site.