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Prof. NikosHatziargyriou Hatziargyriou
National Technical Univercity of Athens

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Research Keywords & Expertise

0 Resilience
0 Power systems analysis and control
0 Microgrids operation and control
0 Smartgrids
0 Power system planning

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Resilience
Power system planning

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Short Biography

Nikos Hatziargyriou is professor in Power Systems at the National Technical University of Athens. He has over 10 year industrial experience as Chairman and CEO of the Hellenic Distribution Network Operator (HEDNO) and as executive Vice-Chair and Deputy CEO of the Public Power Corporation (PPC), responsible for the Transmission and Distribution Divisions. He is honorary member of CIGRE and past Chair of CIGRE SC C6 “Distribution Systems and Distributed Generation”. He is Life Fellow Member of IEEE, past Chair of the Power System Dynamic Performance Committee (PSDPC) and currently Editor in Chief of the IEEE Trans on Power Systems. He has participated in more than 60 RD&D projects funded by the EU Commission, electric utilities and manufacturers for fundamental research and practical applications. He is included in the 2016, 2017 and 2019 Thomson Reuters lists of the top 1% most cited researchers and he is Globe Energy Prize laureate 2020.

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Journal article
Published: 22 August 2021 in Applied Sciences
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Transmission system operators (TSOs) often set requirements to distribution system operators (DSOs) regarding the exchange of reactive power on the interface between the two parts of the system they operate, typically High Voltage and Medium Voltage. The presence of increasing amounts of Distributed Energy Resources (DERs) at the distribution networks complicates the problem, but provides control opportunities in order to keep the exchange within the prescribed limits. Typical DER control methods, such as constant cosϕ or Q/V functions, cannot adequately address these limits, while power electronics interfaced DERs provide to DSOs reactive power control capabilities for complying more effectively with TSO requirements. This paper proposes an optimisation method to provide power set-points to DERs in order to control the hourly reactive power exchanges with the transmission network. The method is tested via simulations using real data from the distribution substation at the Sundom Smart Grid, in Finland, using the operating guidelines imposed by the Finnish TSO. Results show the advantages of the proposed method compared to traditional methods for reactive power compensation from DERs. The application of more advanced Model Predictive Control techniques is further explored.

ACS Style

Panagiotis Pediaditis; Katja Sirviö; Charalampos Ziras; Kimmo Kauhaniemi; Hannu Laaksonen; Nikos Hatziargyriou. Compliance of Distribution System Reactive Flows with Transmission System Requirements. Applied Sciences 2021, 11, 7719 .

AMA Style

Panagiotis Pediaditis, Katja Sirviö, Charalampos Ziras, Kimmo Kauhaniemi, Hannu Laaksonen, Nikos Hatziargyriou. Compliance of Distribution System Reactive Flows with Transmission System Requirements. Applied Sciences. 2021; 11 (16):7719.

Chicago/Turabian Style

Panagiotis Pediaditis; Katja Sirviö; Charalampos Ziras; Kimmo Kauhaniemi; Hannu Laaksonen; Nikos Hatziargyriou. 2021. "Compliance of Distribution System Reactive Flows with Transmission System Requirements." Applied Sciences 11, no. 16: 7719.

Journal article
Published: 21 July 2021 in IEEE Systems Journal
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An aggregation of distributed energy resources (DERs) can bring economic and technical benefits for the DER owners and system operator. However, the operation of DERs encounters various uncertainties, which can seriously impact the benefits of DER aggregation. This article presents a new operation optimization approach for an aggregator of DERs considering the unavailability of DERs (as discrete uncertainty sources) as well as forecast uncertainties of electricity prices, solar powers, and wind powers (as continuous uncertainty sources). The proposed approach for DER aggregator (DERA) operation optimization comprises stochastic multiobjective information-gap decision theory (IGDT) to model these discrete and continuous uncertain variables. Moreover, a hybrid endogenous/exogenous scenario generation method is incorporated into the proposed approach to enhance the efficiency of the stochastic programming part by producing decision-dependent scenario trees. The proposed approach is formulated as a nested bilevel optimization model. The proposed approach is compared with other DERA operation optimization models using an out-of-sample analysis method. The comparative results illustrate the superiority of the proposed stochastic multiobjective IGDT approach over various deterministic, stochastic, and IGDT methods. In addition, the high tractability of the proposed solution method is illustrated, while its linearization error for the stochastic multiobjective IGDT problem is well below 1%.

ACS Style

Mohsen Yazdaninejad; Nima Amjady; Nikos D. Hatziargyriou. Nested Bilevel Optimization for DERA Operation Strategy: A Stochastic Multiobjective IGDT Model With Hybrid Endogenous/Exogenous Scenarios. IEEE Systems Journal 2021, PP, 1 -12.

AMA Style

Mohsen Yazdaninejad, Nima Amjady, Nikos D. Hatziargyriou. Nested Bilevel Optimization for DERA Operation Strategy: A Stochastic Multiobjective IGDT Model With Hybrid Endogenous/Exogenous Scenarios. IEEE Systems Journal. 2021; PP (99):1-12.

Chicago/Turabian Style

Mohsen Yazdaninejad; Nima Amjady; Nikos D. Hatziargyriou. 2021. "Nested Bilevel Optimization for DERA Operation Strategy: A Stochastic Multiobjective IGDT Model With Hybrid Endogenous/Exogenous Scenarios." IEEE Systems Journal PP, no. 99: 1-12.

Journal article
Published: 25 May 2021 in IEEE Access
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Distribution network is an essential part of electric power system, which however has higher power losses than transmission system. Distribution losses directly affect the operational cost of the system. Therefore, power loss reduction in distribution network is very important for distribution system users and connected customers. One of the commonly used ways for reducing losses is distribution system reconfiguration (DSR). In this process, configuration of distribution network changes by opening and closing sectional and tie switches in order to achieve the lowest level of power losses, while the network has to maintain its radial configuration and nodal voltage limits, and supply all connected loads. The DSR aiming loss reduction is a complex mixed-integer optimization problem with a quadratic term of power losses in the objective function and a set of linear and non-linear constraints. Accordingly, distribution network researchers have dedicated their efforts to developing efficient models and methodologies in order to find optimal solutions for loss reduction via DSR. In this paper, an efficient mathematical model for loss minimization in distribution network reconfiguration considering the system voltage profile is presented. The model can be solved by commercially available solvers. In the paper, the proposed model is applied to several test systems and real distribution networks showing its high efficiency and effectiveness for distribution systems reconfiguration.

ACS Style

Meisam Mahdavi; Hassan Haes Alhelou; Nikos D. Hatziargyriou; Amer Al-Hinai. An Efficient Mathematical Model for Distribution System Reconfiguration Using AMPL. IEEE Access 2021, 9, 79961 -79993.

AMA Style

Meisam Mahdavi, Hassan Haes Alhelou, Nikos D. Hatziargyriou, Amer Al-Hinai. An Efficient Mathematical Model for Distribution System Reconfiguration Using AMPL. IEEE Access. 2021; 9 (99):79961-79993.

Chicago/Turabian Style

Meisam Mahdavi; Hassan Haes Alhelou; Nikos D. Hatziargyriou; Amer Al-Hinai. 2021. "An Efficient Mathematical Model for Distribution System Reconfiguration Using AMPL." IEEE Access 9, no. 99: 79961-79993.

Journal article
Published: 14 May 2021 in Energies
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Lately, data-driven algorithms have been proposed to design local controls for Distributed Generators (DGs) that can emulate the optimal behaviour without any need for communication or centralised control. The design is based on historical data, advanced off-line optimization techniques and machine learning methods, and has shown great potential when the operating conditions are similar to the training data. However, safety issues arise when the real-time conditions start to drift away from the training set, leading to the need for online self-adapting algorithms and experimental verification of data-driven controllers. In this paper, we propose an online self-adapting algorithm that adjusts the DG controls to tackle local power quality issues. Furthermore, we provide experimental verification of the data-driven controllers through power Hardware-in-the-Loop experiments using an industrial inverter. The results presented for a low-voltage distribution network show that data-driven schemes can emulate the optimal behaviour and the online modification scheme can mitigate local power quality issues.

ACS Style

Stavros Karagiannopoulos; Athanasios Vasilakis; Panos Kotsampopoulos; Nikos Hatziargyriou; Petros Aristidou; Gabriela Hug. Experimental Verification of Self-Adapting Data-Driven Controllers in Active Distribution Grids. Energies 2021, 14, 2837 .

AMA Style

Stavros Karagiannopoulos, Athanasios Vasilakis, Panos Kotsampopoulos, Nikos Hatziargyriou, Petros Aristidou, Gabriela Hug. Experimental Verification of Self-Adapting Data-Driven Controllers in Active Distribution Grids. Energies. 2021; 14 (10):2837.

Chicago/Turabian Style

Stavros Karagiannopoulos; Athanasios Vasilakis; Panos Kotsampopoulos; Nikos Hatziargyriou; Petros Aristidou; Gabriela Hug. 2021. "Experimental Verification of Self-Adapting Data-Driven Controllers in Active Distribution Grids." Energies 14, no. 10: 2837.

Journal article
Published: 20 April 2021 in Applied Sciences
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During the ongoing evolution of energy systems toward increasingly flexible, resilient, and digitalized distribution systems, many issues need to be developed. In general, a holistic multi-level systemic view is required on the future enabling technologies, control and management methods, operation and planning principles, regulation as well as market and business models. Increasing integration of intermittent renewable generation and electric vehicles, as well as industry electrification during the evolution, requires a huge amount of flexibility services at multiple time scales and from different voltage levels, resources, and sectors. Active use of distribution network-connected flexible energy resources for flexibility services provision through new marketplaces will also be needed. Therefore, increased collaboration between system operators in operation and planning of the future power system will also become essential during the evolution. In addition, use of integrated cyber-secure, resilient, cost-efficient, and advanced communication technologies and solutions will be of key importance. This paper describes a potential three-stage evolution path toward fully flexible, resilient, and digitalized electricity distribution networks. A special focus of this paper is the evolution and development of adaptive control and management methods as well as compatible collaborative market schemes that can enable the improved provision of flexibility services by distribution network-connected flexible energy resources for local (distribution system operator) and system-wide (transmission system operator) needs.

ACS Style

Hannu Laaksonen; Hosna Khajeh; Chethan Parthasarathy; Miadreza Shafie-Khah; Nikos Hatziargyriou. Towards Flexible Distribution Systems: Future Adaptive Management Schemes. Applied Sciences 2021, 11, 3709 .

AMA Style

Hannu Laaksonen, Hosna Khajeh, Chethan Parthasarathy, Miadreza Shafie-Khah, Nikos Hatziargyriou. Towards Flexible Distribution Systems: Future Adaptive Management Schemes. Applied Sciences. 2021; 11 (8):3709.

Chicago/Turabian Style

Hannu Laaksonen; Hosna Khajeh; Chethan Parthasarathy; Miadreza Shafie-Khah; Nikos Hatziargyriou. 2021. "Towards Flexible Distribution Systems: Future Adaptive Management Schemes." Applied Sciences 11, no. 8: 3709.

Journal article
Published: 19 April 2021 in IEEE Power and Energy Magazine
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Microgrids have gained significant interest over the last 20 years and are perceived as key components of future power systems. Microgrids are defined as distribution networks with distributed energy resources (DERs) (e.g., distributed generators, storage devices, and controllable loads) operating in a controlled and coordinated way. Moreover, microgrids should have clear electrical boundaries and the ability to operate connected to the main power network or islanded. The coordinated control of microgrid resources increases energy efficiency, minimizes the overall energy consumption, and reduces the environmental impacts of energy production. At the same time, the ability of microgrids to seamlessly transition to islanded operation when upstream network faults occur increases the reliability and resilience of the customer supply. Furthermore, microgrids have been adopted as prominent and viable solutions for rural electrification in developing countries, isolated areas, or areas with weak power transmission infrastructures.

ACS Style

Dimitris Lagos; Vasileios Papaspiliotopoulos; George Korres; Nikos Hatziargyriou. Microgrid Protection Against Internal Faults: Challenges in Islanded and Interconnected Operation. IEEE Power and Energy Magazine 2021, 19, 20 -35.

AMA Style

Dimitris Lagos, Vasileios Papaspiliotopoulos, George Korres, Nikos Hatziargyriou. Microgrid Protection Against Internal Faults: Challenges in Islanded and Interconnected Operation. IEEE Power and Energy Magazine. 2021; 19 (3):20-35.

Chicago/Turabian Style

Dimitris Lagos; Vasileios Papaspiliotopoulos; George Korres; Nikos Hatziargyriou. 2021. "Microgrid Protection Against Internal Faults: Challenges in Islanded and Interconnected Operation." IEEE Power and Energy Magazine 19, no. 3: 20-35.

Journal article
Published: 29 March 2021 in IEEE Transactions on Power Systems
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Stochastic unit commitment is an efficient method for grid operation in the presence of significant uncertainties. An example is an operation during a predicted hurricane with uncertain line out-ages. However, the solution quality comes at the cost of substantial computational burden, which makes its adoption challenging. This paper evaluates some possible ways that machine learning can be used to reduce this computational burden. First, a set of feasibility studies is conducted. Results suggest that using machine learning as an assistant to the stochastic unit commitment solver is more advantageous than using it as a standalone solver. In particular, the machine learning model is trained to facilitate solving the problem by determining the unnecessary constraints that can be removed from the original problem without affecting the final accuracy. The variables that can be used as input features/predictors or outputs for the machine learning model are determined through feasibility studies. Then, an algorithm to train and utilize a machine learning model is proposed. The method is tested on a 500-bus synthetic South Carolina system. Various test cases show an average reduction in solution time by more than 90% by using the trained machine learning model to assist the stochastic unit commitment solver.

ACS Style

Farshad Mohammadi; Mostafa Sahraei-Ardakani; Dimitris Trakas; Nikos D. Hatziargyriou. Machine Learning Assisted Stochastic Unit Commitment during Hurricanes with Predictable Line Outages. IEEE Transactions on Power Systems 2021, PP, 1 -1.

AMA Style

Farshad Mohammadi, Mostafa Sahraei-Ardakani, Dimitris Trakas, Nikos D. Hatziargyriou. Machine Learning Assisted Stochastic Unit Commitment during Hurricanes with Predictable Line Outages. IEEE Transactions on Power Systems. 2021; PP (99):1-1.

Chicago/Turabian Style

Farshad Mohammadi; Mostafa Sahraei-Ardakani; Dimitris Trakas; Nikos D. Hatziargyriou. 2021. "Machine Learning Assisted Stochastic Unit Commitment during Hurricanes with Predictable Line Outages." IEEE Transactions on Power Systems PP, no. 99: 1-1.

Journal article
Published: 27 March 2021 in Energies
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In this paper, we investigate the economic benefits of an energy community investing in small-scale photovoltaics (PVs) when local energy trading is operated amongst the community members. The motivation stems from the open research question on whether a community-operated local energy market can enhance the investment feasibility of behind-the-meter small-scale PVs installed by energy community members. Firstly, a review of the models, mechanisms and concepts required for framing the relevant concepts is conducted, while a clarification of nuances at important terms is attempted. Next, a tool for the investigation of the economic benefits of operating a local energy market in the context of an energy community is developed. We design the local energy market using state-of-the-art formulations, modified according to the requirements of the case study. The model is applied to an energy community that is currently under formation in a Greek municipality. From the various simulations that were conducted, a series of generalizable conclusions are extracted.

ACS Style

Alexandros-Georgios Chronis; Foivos Palaiogiannis; Iasonas Kouveliotis-Lysikatos; Panos Kotsampopoulos; Nikos Hatziargyriou. Photovoltaics Enabling Sustainable Energy Communities: Technological Drivers and Emerging Markets. Energies 2021, 14, 1862 .

AMA Style

Alexandros-Georgios Chronis, Foivos Palaiogiannis, Iasonas Kouveliotis-Lysikatos, Panos Kotsampopoulos, Nikos Hatziargyriou. Photovoltaics Enabling Sustainable Energy Communities: Technological Drivers and Emerging Markets. Energies. 2021; 14 (7):1862.

Chicago/Turabian Style

Alexandros-Georgios Chronis; Foivos Palaiogiannis; Iasonas Kouveliotis-Lysikatos; Panos Kotsampopoulos; Nikos Hatziargyriou. 2021. "Photovoltaics Enabling Sustainable Energy Communities: Technological Drivers and Emerging Markets." Energies 14, no. 7: 1862.

Journal article
Published: 27 March 2021 in Electric Power Systems Research
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Reliable and fast state discrimination are among the most important requirements in islanding detection methods (IDMs) to avoid islanded operation problems of distributed generation (DG) systems. This paper proposes a novel, IDM based on the dynamic response characteristics of synchronous DGs. The proposed method is based on four features of the dynamic behavior of synchronous DGs, namely, participation matrix; zero mode; oscillation frequency; and damping factor. This allows to distinguish between islanding conditions and grid-connected disturbances, even when demand and generation are closely matched. These features are extracted in practice from local measurements using Hilbert-Huang transform (HHT) technique. Moreover, a new method for online observation of the participation matrix based on online power system measurements is proposed. The impacts of synchronous DG controllers and motor loads are considered in the proposed method. Different scenarios such as load shedding, load restoration, capacitor switching, and short circuit faults have been simulated to assess the performance of the proposed method. Simulations are performed on a typical distribution system with real data for different scenarios to verify the high speed performance, reliability, robustness, and applicability of the proposed islanding detection algorithm. Comparison with alternative islanding detection methods prove the superiority of the proposed approach.

ACS Style

Reza Zamani; Mohammad Esmail Hamedani Golshan; Hassan Haes Alhelou; Nikos Hatziargyriou. A Novel Synchronous DGs Islanding Detection Method based on Online Dynamic Features Extraction. Electric Power Systems Research 2021, 195, 107180 .

AMA Style

Reza Zamani, Mohammad Esmail Hamedani Golshan, Hassan Haes Alhelou, Nikos Hatziargyriou. A Novel Synchronous DGs Islanding Detection Method based on Online Dynamic Features Extraction. Electric Power Systems Research. 2021; 195 ():107180.

Chicago/Turabian Style

Reza Zamani; Mohammad Esmail Hamedani Golshan; Hassan Haes Alhelou; Nikos Hatziargyriou. 2021. "A Novel Synchronous DGs Islanding Detection Method based on Online Dynamic Features Extraction." Electric Power Systems Research 195, no. : 107180.

Journal article
Published: 21 March 2021 in Applied Sciences
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The power system transition to smart grids brings challenges to electricity distribution network development since it involves several stakeholders and actors whose needs must be met to be successful for the electricity network upgrade. The technological challenges arise mainly from the various distributed energy resources (DERs) integration and use and network optimization and security. End-customers play a central role in future network operations. Understanding the network’s evolution through possible network operational scenarios could create a dedicated and reliable roadmap for the various stakeholders’ use. This paper presents a method to develop the evolving operational scenarios and related management schemes, including microgrid control functionalities, and analyzes the evolution of electricity distribution networks considering medium and low voltage grids. The analysis consists of the dynamic descriptions of network operations and the static illustrations of the relationships among classified actors. The method and analysis use an object-oriented and standardized software modeling language, the unified modeling language (UML). Operational descriptions for the four evolution phases of electricity distribution networks are defined and analyzed by Enterprise Architect, a UML tool. This analysis is followed by the active management architecture schemes with the microgrid control functionalities. The graphical models and analysis generated can be used for scenario building in roadmap development, real-time simulations, and management system development. The developed method, presented with high-level use cases (HL-UCs), can be further used to develop and analyze several parallel running control algorithms for DERs providing ancillary services (ASs) in the evolving electricity distribution networks.

ACS Style

Katja Sirviö; Hannu Laaksonen; Kimmo Kauhaniemi; Nikos Hatziargyriou. Evolution of the Electricity Distribution Networks—Active Management Architecture Schemes and Microgrid Control Functionalities. Applied Sciences 2021, 11, 2793 .

AMA Style

Katja Sirviö, Hannu Laaksonen, Kimmo Kauhaniemi, Nikos Hatziargyriou. Evolution of the Electricity Distribution Networks—Active Management Architecture Schemes and Microgrid Control Functionalities. Applied Sciences. 2021; 11 (6):2793.

Chicago/Turabian Style

Katja Sirviö; Hannu Laaksonen; Kimmo Kauhaniemi; Nikos Hatziargyriou. 2021. "Evolution of the Electricity Distribution Networks—Active Management Architecture Schemes and Microgrid Control Functionalities." Applied Sciences 11, no. 6: 2793.

Journal article
Published: 19 March 2021 in IEEE Access
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Distribution network connected distributed energy resources (DER) are able to provide various flexibility services for distribution system operators (DSOs) and transmission system operators (TSOs). These local and system-wide flexibility services offered by DER can support the frequency (f) and voltage (U) management of a future power system with large amounts of weather-dependent renewable generation and electric vehicles. Depending on the magnitude of frequency deviation, other active network management-based frequency control services for TSOs could also be provided by DSOs in coordination with adaptive control of DER. This paper proposes utilisation of demand response based on frequency-dependent HV/MV transformer on-load tap-changer (OLTC) operation in case of larger frequency deviations. The main principle underlying the proposed scheme lies in the voltage dependency of the distribution network connected loads. In this paper, it is also proposed to, simultaneously with frequency-dependent OLTC control, utilise reverse reactive power -voltage (QU) - and adaptive active power -voltage (PU) -droops with distribution network connected DER units during these larger frequency deviations, in order to enable better frequency support service for TSOs from DSO networks. The effectivity and potential of the proposed schemes are shown through PSCAD simulations. In addition, this paper also presents a holistic and collaborative view of potential future frequency control services which are provided by DSO network-connected resources for TSOs at different frequency deviation levels.

ACS Style

Hannu Laaksonen; Chethan Parthasarathy; Hosna Khajeh; Miadreza Shafie-Khah; Nikos Hatziargyriou. Flexibility Services Provision by Frequency-Dependent Control of On-Load Tap-Changer and Distributed Energy Resources. IEEE Access 2021, 9, 45587 -45599.

AMA Style

Hannu Laaksonen, Chethan Parthasarathy, Hosna Khajeh, Miadreza Shafie-Khah, Nikos Hatziargyriou. Flexibility Services Provision by Frequency-Dependent Control of On-Load Tap-Changer and Distributed Energy Resources. IEEE Access. 2021; 9 (99):45587-45599.

Chicago/Turabian Style

Hannu Laaksonen; Chethan Parthasarathy; Hosna Khajeh; Miadreza Shafie-Khah; Nikos Hatziargyriou. 2021. "Flexibility Services Provision by Frequency-Dependent Control of On-Load Tap-Changer and Distributed Energy Resources." IEEE Access 9, no. 99: 45587-45599.

Journal article
Published: 08 March 2021 in IEEE Transactions on Sustainable Energy
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This paper proposes a bi-level optimal integration scheme for buildings space heating loads in the integrated community energy system (ICES). The optimal integration scheme consists of an efficient energy management method and a heating pricing method for the ICES with buildings. At the upper level, the ICES operator optimizes the schedules of energy generation and supply, and the heating prices to buildings to maximize its profit. At the lower level, consumers in buildings optimize the water flow rates in the radiators to minimize their heating costs. The thermal dynamics of the building with controllable indoor radiators is modeled using the Resistor-Capacitor thermal network model. Moreover, the model predictive control (MPC) is integrated with the bi-level optimization to achieve economic and reliable scheduling of the ICES and buildings under uncertainties. The bi-level MPC optimization is reformulated as an MPC based mixed-integer linear program using the Karush-Kuhn-Tucker optimality conditions and several linearization techniques. Numerical studies show that the bi-level MPC method can obtain a balanced scheduling scheme between the energy costs of consumers in buildings and the ICES operator's profits. The MPC method can ensure higher profits of the ICES operator and simultaneously, lower energy costs of consumers in buildings.

ACS Style

Xiaolong Jin; Qiuwei Wu; Hongjie Jia; Nikos D. Hatziargyriou. Optimal Integration of Building Heating Loads in Integrated Heating/Electricity Community Energy Systems: A Bi-Level MPC Approach. IEEE Transactions on Sustainable Energy 2021, 12, 1741 -1754.

AMA Style

Xiaolong Jin, Qiuwei Wu, Hongjie Jia, Nikos D. Hatziargyriou. Optimal Integration of Building Heating Loads in Integrated Heating/Electricity Community Energy Systems: A Bi-Level MPC Approach. IEEE Transactions on Sustainable Energy. 2021; 12 (3):1741-1754.

Chicago/Turabian Style

Xiaolong Jin; Qiuwei Wu; Hongjie Jia; Nikos D. Hatziargyriou. 2021. "Optimal Integration of Building Heating Loads in Integrated Heating/Electricity Community Energy Systems: A Bi-Level MPC Approach." IEEE Transactions on Sustainable Energy 12, no. 3: 1741-1754.

Journal article
Published: 02 March 2021 in IEEE Transactions on Power Systems
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This paper proposes a new decentralized data-driven load res-toration (DDLR) scheme for transmission and distribution (TD) systems with high penetration of wind power. Robust DDLR models are constructed in order to handle uncertainties and ensure the feasibility of decentralized schemes. The Wasserstein metric is used to describe the ambiguity sets of probability distributions in order to build the complete DDLR model and realize computationally tractable formulation. A data-driven model-nested analytical target cascading (DATC) algorithm is developed to obtain the final load restoration result by iteratively solving small-scale mathematical models. The proposed DDLR scheme provides load restoration results with adjustable robustness, and performance efficiency is independent from the amount of data. The DDLR scheme makes full use of the available data while respecting information privacy requirements of independently operated systems, and ensures the feasibility of the decentralized load restoration strategy even in the worst-case condition. The effectiveness of the proposed method is validated using a small-scale TDS and a large-scale system with the IEEE 118-bus TS and thirty IEEE-33 DSs, showing high computational efficiency and superior restoration performance.

ACS Style

Jin Zhao; Qiuwei Wu; Nikos D. Hatziargyriou; Fangxing Fran Li; Fei Teng. Decentralized Data-Driven Load Restoration in Coupled Transmission and Distribution System With Wind Power. IEEE Transactions on Power Systems 2021, 36, 4435 -4444.

AMA Style

Jin Zhao, Qiuwei Wu, Nikos D. Hatziargyriou, Fangxing Fran Li, Fei Teng. Decentralized Data-Driven Load Restoration in Coupled Transmission and Distribution System With Wind Power. IEEE Transactions on Power Systems. 2021; 36 (5):4435-4444.

Chicago/Turabian Style

Jin Zhao; Qiuwei Wu; Nikos D. Hatziargyriou; Fangxing Fran Li; Fei Teng. 2021. "Decentralized Data-Driven Load Restoration in Coupled Transmission and Distribution System With Wind Power." IEEE Transactions on Power Systems 36, no. 5: 4435-4444.

Journal article
Published: 22 February 2021 in IEEE Transactions on Power Systems
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The replacement of directly connected synchronous generators with power electronics interfaced generation has led to a decrease in system's inertia posing a significant challenge on frequency dynamics. In isolated systems with reduced inertia predefined limits for renewable penetration and primary reserves are frequently set for dynamic security purposes. This approach might not ensure dynamic security or can prove conservative in certain conditions. Furthermore, these approaches rarely consider the capabilities of inverter based renewable generation to provide frequency services. In this paper, a data driven approach, based on optimal classification trees is proposed to extract, from a detailed dynamic model of the system, the constraints for a frequency dynamic unit commitment formulation. Hence, both dynamic security and optimal exploitation of renewable and conventional units for power production and frequency support can be achieved. The advantages of the proposed method compared to conventional and state of the art approaches in frequency security are validated through dynamic simulations on a realistic model of Rhodes island and IEEE 118. Uncertainties in load demand and renewable generation are dealt by a robust optimization method. Its economic performance, computational overhead and modelling complexity is compared to a stochastic approach.

ACS Style

Dimitris T. Lagos; Nikos D. Hatziargyriou. Data-Driven Frequency Dynamic Unit Commitment for Island Systems With High RES Penetration. IEEE Transactions on Power Systems 2021, 36, 4699 -4711.

AMA Style

Dimitris T. Lagos, Nikos D. Hatziargyriou. Data-Driven Frequency Dynamic Unit Commitment for Island Systems With High RES Penetration. IEEE Transactions on Power Systems. 2021; 36 (5):4699-4711.

Chicago/Turabian Style

Dimitris T. Lagos; Nikos D. Hatziargyriou. 2021. "Data-Driven Frequency Dynamic Unit Commitment for Island Systems With High RES Penetration." IEEE Transactions on Power Systems 36, no. 5: 4699-4711.

Journal article
Published: 22 February 2021 in IEEE Transactions on Power Systems
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The Editorial Board of the IEEE Transactions on Power Systems would like to recognize the following high quality papers published from 2018 through 2020:

ACS Style

Nikos Hatziargyriou. Best Papers and Outstanding Reviewers. IEEE Transactions on Power Systems 2021, 36, 829 -829.

AMA Style

Nikos Hatziargyriou. Best Papers and Outstanding Reviewers. IEEE Transactions on Power Systems. 2021; 36 (2):829-829.

Chicago/Turabian Style

Nikos Hatziargyriou. 2021. "Best Papers and Outstanding Reviewers." IEEE Transactions on Power Systems 36, no. 2: 829-829.

Journal article
Published: 16 February 2021 in IEEE Transactions on Control of Network Systems
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Decomposing the large distribution grids into the interconnected microgrids (MGs) can potentially contribute to enhance the power system efficiency, sustainability, resiliency, and reliability. However, energy management within the entire network would be more complicated and challenging. This paper develops a novel energy management framework for interconnected MGs based on blockchain technology. Utilizing the blockchain technology can potentially enhance the system security, and also reduce the system risks, mitigate financial fraud, and cut down the operational cost. A priority list is first defined to get into an efficient energy trade-off within the interconnected MGs. Moreover, the incentive contract is proposed to provide a price discount for a party that purchases more power from one sub-MG. A stochastic framework based on the Unscented Transform (UT) technique is also established to manage the uncertainties associated with hourly load demands and output power of renewable energy sources. The proposed model is formulated as a mixed-integer linear programming (MILP) optimization problem and solved through the blockchain-based energy/power management algorith

ACS Style

Morteza Dabbaghjamanesh; Boyu Wang; Abdollah Kavousi-Fard; Nikos Hatziargyriou; Jie Zhang. Blockchain-based Stochastic Energy Management of Interconnected Microgrids Considering Incentive Price. IEEE Transactions on Control of Network Systems 2021, PP, 1 -1.

AMA Style

Morteza Dabbaghjamanesh, Boyu Wang, Abdollah Kavousi-Fard, Nikos Hatziargyriou, Jie Zhang. Blockchain-based Stochastic Energy Management of Interconnected Microgrids Considering Incentive Price. IEEE Transactions on Control of Network Systems. 2021; PP (99):1-1.

Chicago/Turabian Style

Morteza Dabbaghjamanesh; Boyu Wang; Abdollah Kavousi-Fard; Nikos Hatziargyriou; Jie Zhang. 2021. "Blockchain-based Stochastic Energy Management of Interconnected Microgrids Considering Incentive Price." IEEE Transactions on Control of Network Systems PP, no. 99: 1-1.

Chapter
Published: 01 January 2021 in Springer Handbook of Odor
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This chapter presents an overview of power distribution networks. The description of the main components of a distribution network are given and various power flow models for the steady state analysis of distribution networks are formulated. The increasing penetration of distributed energy resources into the distribution level has transformed distribution networks into active ones. The basic functions of an advanced distribution management system for the control and monitoring of a distribution network are presented. Furthermore, methods for the operation of the network under normal and emergency operating conditions and for distribution network planning are presented.

ACS Style

Nikolaos C. Koutsoukis; Pavlos S. Georgilakis; George N. Korres; Nikos D. Hatziargyriou. Distribution Systems. Springer Handbook of Odor 2021, 1093 -1129.

AMA Style

Nikolaos C. Koutsoukis, Pavlos S. Georgilakis, George N. Korres, Nikos D. Hatziargyriou. Distribution Systems. Springer Handbook of Odor. 2021; ():1093-1129.

Chicago/Turabian Style

Nikolaos C. Koutsoukis; Pavlos S. Georgilakis; George N. Korres; Nikos D. Hatziargyriou. 2021. "Distribution Systems." Springer Handbook of Odor , no. : 1093-1129.

Journal article
Published: 08 December 2020 in IEEE Transactions on Power Systems
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Since the publication of the original paper on power system stability definitions in 2004, the dynamic behavior of power systems has gradually changed due to the increasing penetration of converter interfaced generation technologies, loads, and transmission devices. In recognition of this change, a Task Force was established in 2016 to re-examine and extend, where appropriate, the classic definitions and classifications of the basic stability terms to incorporate the effects of fast-response power electronic devices. This paper based on an IEEE PES report summarizes the major results of the work of the Task Force and presents extended definitions and classification of power system stability.

ACS Style

Nikos Hatziargyriou; Jovica Milanovic; Claudia Rahmann; Venkataramana Ajjarapu; Claudio Canizares; Istvan Erlich; David Hill; Ian Hiskens; Innocent Kamwa; Bikash Pal; Pouyan Pourbeik; J. J. Sanchez-Gasca; Aleksandar Stankovic; Thierry Van Cutsem; Vijay Vittal; Costas Vournas. Definition and Classification of Power System Stability – Revisited & Extended. IEEE Transactions on Power Systems 2020, 36, 3271 -3281.

AMA Style

Nikos Hatziargyriou, Jovica Milanovic, Claudia Rahmann, Venkataramana Ajjarapu, Claudio Canizares, Istvan Erlich, David Hill, Ian Hiskens, Innocent Kamwa, Bikash Pal, Pouyan Pourbeik, J. J. Sanchez-Gasca, Aleksandar Stankovic, Thierry Van Cutsem, Vijay Vittal, Costas Vournas. Definition and Classification of Power System Stability – Revisited & Extended. IEEE Transactions on Power Systems. 2020; 36 (4):3271-3281.

Chicago/Turabian Style

Nikos Hatziargyriou; Jovica Milanovic; Claudia Rahmann; Venkataramana Ajjarapu; Claudio Canizares; Istvan Erlich; David Hill; Ian Hiskens; Innocent Kamwa; Bikash Pal; Pouyan Pourbeik; J. J. Sanchez-Gasca; Aleksandar Stankovic; Thierry Van Cutsem; Vijay Vittal; Costas Vournas. 2020. "Definition and Classification of Power System Stability – Revisited & Extended." IEEE Transactions on Power Systems 36, no. 4: 3271-3281.

Journal article
Published: 07 December 2020 in IEEE Transactions on Smart Grid
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This paper proposes a DR program characterized by a novel compensation scheme. The proposed scheme recognizes the different characteristics of curtailment, such as the total length of curtailments within a window of time, or the number of separate curtailment events (i.e. curtailment startup), and compensates the end-user accordingly. The proposed compensation scheme features a piece-wise reward function comprised of two intervals. DR participants receive a onetime reward upfront when they enroll in the DR program and accept a set of predefined curtailment aspects. Curtailment aspects in excess of the agreed quantities are rewarded at a linear rate. This design is tailored to appeal to residential DR participants, and aims to secure sufficient flexibility at minimum cost. The parameters of the smart contract are optimized such that the system’s social welfare is maximized. The optimization problem is modeled as a mixed-integer linear program. Consequently, this paper updates the unit-commitment (UC) formulation with the commitment aspects of DR units. The proposed extension to the UC problem considers the critical aspects of DR participation, such as: the total length of interruptions within a window, the frequency of interruptions within a time-window irrespective of their length, and the net energy deviation from the original load profile. Deployment of the smart DR contract in the unit dispatch problem requires translating DR participants’ characteristics to their equivalent aspects in conventional thermal generators, such as minimum up time, minimum down-time, start-up and shutdown costs. The obtained results demonstrate significant improvement in social welfare, notable reduction of curtailed renewable energy and reduction in extreme ramping events of conventional generators.

ACS Style

Baraa Mohandes; Mohamed Shawky El Moursi; Nikos D. Hatziargyriou; Sameh El Khatib. Incentive Based Demand Response Program for Power System Flexibility Enhancement. IEEE Transactions on Smart Grid 2020, 12, 2212 -2223.

AMA Style

Baraa Mohandes, Mohamed Shawky El Moursi, Nikos D. Hatziargyriou, Sameh El Khatib. Incentive Based Demand Response Program for Power System Flexibility Enhancement. IEEE Transactions on Smart Grid. 2020; 12 (3):2212-2223.

Chicago/Turabian Style

Baraa Mohandes; Mohamed Shawky El Moursi; Nikos D. Hatziargyriou; Sameh El Khatib. 2020. "Incentive Based Demand Response Program for Power System Flexibility Enhancement." IEEE Transactions on Smart Grid 12, no. 3: 2212-2223.

Journal article
Published: 02 December 2020 in IEEE Electrification Magazine
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The noninterconnected island of Kythnos (100 km2 with 1,600 inhabitants) belongs to the complex of the Western Cyclades islands in Greece and is located in the Aegean Sea, 104 km from Athens. The island has a rich history in the adoption of sustainable energy applications, starting from the installation of the first wind farm in Europe [5 ? 20-kW wind turbines (WTs)] by the Public Power Corporation (PPC) in 1982, followed in 1983 by the first hybrid station comprising a 100-kW photovoltaic (PV) system coupled with a 400-kWh battery storage, also by PPC. In 1989, the WTs were replaced by 5 ? 33 kW (Figure 1), and in 1992, the PV inverters were upgraded.

ACS Style

Nikos Hatziargyriou; Aris Dimeas; Nasos Vasilakis; Dimitrios Lagos; Alkistis Kontou. The Kythnos Microgrid: A 20-Year History. IEEE Electrification Magazine 2020, 8, 46 -54.

AMA Style

Nikos Hatziargyriou, Aris Dimeas, Nasos Vasilakis, Dimitrios Lagos, Alkistis Kontou. The Kythnos Microgrid: A 20-Year History. IEEE Electrification Magazine. 2020; 8 (4):46-54.

Chicago/Turabian Style

Nikos Hatziargyriou; Aris Dimeas; Nasos Vasilakis; Dimitrios Lagos; Alkistis Kontou. 2020. "The Kythnos Microgrid: A 20-Year History." IEEE Electrification Magazine 8, no. 4: 46-54.