- Lausanne, Switzerland
- Maryam Bahramipanah is a PhD in Energy, Power System Engineering from Ecole Polytechnique Federal de Lausanne (EPFL), Lausanne, Switzerland.edit
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This paper proposes a real-time decentralized control algorithm in multi-area active distribution network relying only on dispersed battery energy storage systems (BESSs). In particular, we propose a zonal control strategy targeting... more
This paper proposes a real-time decentralized control algorithm in multi-area active distribution network relying only on dispersed battery energy storage systems (BESSs). In particular, we propose a zonal control strategy targeting voltage support and line congestion management. The proposed zonal control relies on an accurate dynamic model of BESSs capable to account for their dc active power limits. The communication among different areas is defined using the concept of multi-agents. The effectiveness of the proposed zonal control is assessed and compared to the equivalent centralized control problem using a test case composed by the IEEE 13 nodes distribution test feeders suitably adapted to include stochastic generation and BESSs.
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This paper proposes an intelligent line congestion prognosis scheme based on wide-area measurements, which accurately identifies an impending congestion and the problem causing the congestion. Due to the increasing penetration of... more
This paper proposes an intelligent line congestion prognosis scheme based on wide-area measurements, which accurately identifies an impending congestion and the problem causing the congestion. Due to the increasing penetration of renewable energy resources and uncertainty of load/generation patterns in the Active Distribution Networks (ADNs), power line congestion is one of the issues that could happen during peak load conditions or high-power injection by renewable energy resources. Congestion would have devastating effects on both the economical and technical operation of the grid. Hence, it is crucial to accurately predict congestions to alleviate the problem in-time and command proper control actions; such as, power redispatch, incorporating ancillary services and energy storage systems, and load curtailment. We use neural network methods in this work due to their outstanding performance in predicting the nonlinear behavior of the power system. Bayesian Regularization, along with Levenberg-Marquardt algorithm, is used to train the proposed neural networks to predict an impending congestion and its cause. The proposed method is validated using the IEEE 13-bus test system. Utilizing the proposed method, extreme control actions (i.e., protection actions and load curtailment) can be avoided. This method will improve the distribution grid resiliency and ensure the continuous supply of power to the loads.
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In this work, a novel agent-based day-ahead power management scheme is proposed for multiple-microgrid distribution systems with the intent of reducing operational costs and improving system resilience. The proposed power sharing... more
In this work, a novel agent-based day-ahead power management scheme is proposed for multiple-microgrid distribution systems with the intent of reducing operational costs and improving system resilience. The proposed power sharing algorithm executes within each microgrid (MG) locally, and the neighboring MGs cooperate via a multi-agent system cooperation scheme, established to model the communication among the agents. The power management for each agent is modeled as a multi-objective optimization problem (MOP) including two objectives: maximizing load coverage and minimizing the operating costs. The proposed MOP is solved using the Nondominated Sorting Genetic Algorithm (NSGA-II), where a set of Pareto optimal solutions is obtained for each agent through the NSGA-II. The final solution is obtained using an Analytical Hierarchical Process. The effectiveness of the proposed scheme is evaluated using a benchmark 4-MG distribution system. It is shown that the proposed power management s...
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Appropriate planning and optimization strategies for day-ahead power management play important roles in efficient operation of Microgrids (MGs). Due to the uncertainties in electricity demand and renewable generations, and the... more
Appropriate planning and optimization strategies for day-ahead power management play important roles in efficient operation of Microgrids (MGs). Due to the uncertainties in electricity demand and renewable generations, and the multi-objective (MO) nature of MG power management, conventional optimization techniques have not been as effective in giving satisfactory results. This paper aims at solving the day-ahead power management problem as a MO optimization problem, with a focus on increasing the system's resiliency using an agent-based Dynamic Programming (DP) approach named Value Iteration (VI) and a model-free Q-learning (QL) algorithm. The two objectives of the MO problem are: maximizing load serviceability and minimizing operational cost. Both the approaches are data-driven, and the behavior of the agent of each component of a MG is formulated as a finite-horizon Markov Decision Process (MDP). VI guarantees an optimal solution to the MO problem given the MDP model, and QL has the ability to work under uncertainty and incomplete information. The effectiveness of the two algorithms have been evaluated using a benchmark MG test system.
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This paper provides a comprehensive review of distribution system state estimation in terms of basic definition, different methods, and their application. In the last few years, the operation of distribution networks has been influenced... more
This paper provides a comprehensive review of distribution system state estimation in terms of basic definition, different methods, and their application. In the last few years, the operation of distribution networks has been influenced by the installation of distributed generations. In order to control and manage an active distribution network’s performance, distribution system state estimation methods are introduced. A transmission system state estimation cannot be used directly in distribution networks since transmission and distribution networks are different due to topology configuration, the number of buses, line parameters, and the number of measurement instruments. So, the proper state estimation algorithms should be proposed according to the main distribution network features. Accuracy, computational efficiency, and practical implications should be considered in the designing of distribution state estimation techniques since technical issues and wrong decisions could emerge...
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Proper planning and optimal resource allocation of distribution systems during an electrical fault or an extreme-event can enhance their resiliency and ensure their stable operation with maximum customer survivability. This paper presents... more
Proper planning and optimal resource allocation of distribution systems during an electrical fault or an extreme-event can enhance their resiliency and ensure their stable operation with maximum customer survivability. This paper presents a graph-theory-based approach for subdividing Active Distribution Networks (ADNs) into different clusters considered as Micro-Grids (MGs), with a focus on improving their resiliency. A case study on a modified IEEE 34-bus distribution system, including wind and solar photovoltaic (PV) distributed generation (DG), shows that with the proposed graph-theory based clustering and MG formation algorithm, the system's resiliency is improved, and when necessary, using demand response, the system operational constraints are maintained at the desired level.
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Due to the increased penetration of Distributed Generations (DGs) in distribution networks, the system control and operation may become quite different from the case of traditional network. Most DGs can only provide intermittent power to... more
Due to the increased penetration of Distributed Generations (DGs) in distribution networks, the system control and operation may become quite different from the case of traditional network. Most DGs can only provide intermittent power to the Active Distribution Networks (ADNs) due to the intermittent nature of the resources. Moreover, ADN utilities usually do not own DGs, and have difficulty in controlling directly DGs output powers. The main problem related to the considerable connection of DGs is usually associated to the node voltage quality and line congestion mitigation. Within the above context, the motivating factors for this thesis are supported by the issues related to optimal operation and control of ADNs integrating stochastic and non-stochastic DGs. One of the most promising near-term solution is offered by using distributed Energy Storage Systems (ESSs) which can perform their full role to guarantee a more flexible network. Indeed, the availability of ESSs allows, in pr...
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COVID-19 pandemic imposes a dramatic reduction in traffic volume, mobility, and energy consumption worldwide and across the United States. This pandemic provides us with a unique opportunity to investigate its sudden intervention on the... more
COVID-19 pandemic imposes a dramatic reduction in traffic volume, mobility, and energy consumption worldwide and across the United States. This pandemic provides us with a unique opportunity to investigate its sudden intervention on the habitual mobility of people and the traffic volume trends in respond to the number of COVID-19 cases, non-pharmaceutical interventions measures, public response and medical precautions. Looking into the two states of California and Montana, the severe changes in mobility and traffic volume happened during the “Stay at Home-Stay Safe” period during March and April 2020. The traffic volume trend started to recover in May in Montana and in late April in California. This paper also presents a data-driven case study electric vehicle charging in Los Angeles county, CA. The number of sessions and energy consumption for electric vehicles declined by 76% and 78% in 2020. The Electric vehicle mobility started to recover gradually in December 2020. Therefore, the respond of electric vehicle drivers to COVID-19 was different than the respond of the internal combustion engine car drivers
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Extreme events such as hurricane, earthquake, flooding, and cyber-attacks can result in power system blackout. Due to the high cost of power outage, appropriate planning, scheduling and preventive strategies should be considered to... more
Extreme events such as hurricane, earthquake, flooding, and cyber-attacks can result in power system blackout. Due to the high cost of power outage, appropriate planning, scheduling and preventive strategies should be considered to improve the resiliency of the power system. The optimal resource allocation in an area with high risk of extreme events occurrence is quite challenging. In this paper, a novel method is presented to improve the grid resiliency, from electrical point of view, in case of an extreme event with an emphasis on grid preparation. A multi-objective planning & control strategy is proposed at the pre-event stage. The proposed approach includes microgrid islanding, generation regulation, and load curtailment. Energy Storage Systems are considered as alternative resources in case of occurrence of extreme events. The effectiveness of the proposed method is assessed and compared to the equivalent conventional control scheme using a test case composed by the IEEE 13-bus distribution test feeders suitably adapted to include stochastic generation and energy storage systems. It is shown that our proposed strategy is able to cover the critical loads in all the 24-hour simulation study.
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In the modern power grid, with the growing penetration of renewable and distributed energy systems, the use of parallel inverters has significantly increased. It is essential to achieve stable parallel operation and reasonable power... more
In the modern power grid, with the growing penetration of renewable and distributed energy systems, the use of parallel inverters has significantly increased. It is essential to achieve stable parallel operation and reasonable power sharing between these parallel inverters. Droop controllers are commonly used to control the power sharing between parallel inverters in an inverter-based microgrid. In this paper, a small signal model of droop controllers with secondary loop control and an internal model-based voltage and current controller is proposed to improve the stability, resiliency, and power sharing of inverter-based distributed generation systems. The distributed generation system’s nonlinear dynamic equations are derived by incorporating the appropriate and accurate models of the network, load, phase locked loop and filters. The obtained model is then trimmed and linearized around its operating point to find the distributed generation system’s state space representation. Moreo...
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This paper proposes a real-time decentralized control algorithm in multi-area active distribution network relying only on dispersed battery energy storage systems (BESSs). In particular, we propose a zonal control strategy targeting... more
This paper proposes a real-time decentralized control algorithm in multi-area active distribution network relying only on dispersed battery energy storage systems (BESSs). In particular, we propose a zonal control strategy targeting voltage support and line congestion management. The proposed zonal control relies on an accurate dynamic model of BESSs capable to account for their dc active power limits. The communication among different areas is defined using the concept of multi-agents. The effectiveness of the proposed zonal control is assessed and compared to the equivalent centralized control problem using a test case composed by the IEEE 13 nodes distribution test feeders suitably adapted to include stochastic generation and BESSs.
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This paper presents controller design of PEM fuel cell distributed generation. The configuration of the PEMFC DG system and the dynamic models for the PEMFC power plant and its power electronic interfacing are shown. Controlling the power... more
This paper presents controller design of PEM fuel cell distributed generation. The configuration of the PEMFC DG system and the dynamic models for the PEMFC power plant and its power electronic interfacing are shown. Controlling the power flow from the fuel cell power plant to the synchronous generator, controller design methods for the power conditioning units are presented. The results
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1 : PROCEEDINGS OF THE 1ST INTERNATIONAL NUCLEAR AND ENEWABLE ENERGY CONFERENCE (INREC 2010) 2010; -(1ST INTERNATIONAL NUCLEAR AND RENEWABLE ENERGY CONFERENCE (INREC 2010)):0-0. A SURVEY ON THE EFFECT OF DIFFERENT ...
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ABSTRACT In this paper, an effective doubly fed induction generators' grid side converter control strategy is proposed. This scheme helps in limiting the fault currents as well as in voltage unbalance compensation. In the... more
ABSTRACT In this paper, an effective doubly fed induction generators' grid side converter control strategy is proposed. This scheme helps in limiting the fault currents as well as in voltage unbalance compensation. In the considered topology three single-phase converters is used instead of one three-phase converters. Voltage is injected in series with the transmission line to limit the fault currents as well as to balance the voltages. The advantages of the proposed controller method with previous one are in inverter size reduction, controllability and feasibility. This scheme allows wind turbines to remain synchronized to the grid during faults or during voltage sags and swings. The effectiveness of the proposed control strategy is confirmed with simulation results in MATLAB/SIMULINK environment.
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With an ever-increasing importance of wind power generation in power systems, the necessity of choosing the appropriate type of technology for the wind turbine generators becomes more significant. In the current paper, fixed and variable... more
With an ever-increasing importance of wind power generation in power systems, the necessity of choosing the appropriate type of technology for the wind turbine generators becomes more significant. In the current paper, fixed and variable speed wind turbines and the application of energy storage system (ESS) to smoothen the wind farm output power are studied. A detailed analysis of the