Advanced Energy Technologies
Moslem Geravandi; Hassan Moradi CheshmehBeigi
Abstract
The ability of power systems against severe events shows their increased resilience, which in turn reduces the operation costs and recovery time of the system. This study presents a new resilient stochastic unit commitment model using the frequency change rate as a new index of system resilience. Furthermore, ...
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The ability of power systems against severe events shows their increased resilience, which in turn reduces the operation costs and recovery time of the system. This study presents a new resilient stochastic unit commitment model using the frequency change rate as a new index of system resilience. Furthermore, uncertainties of wind and solar power plants and demanded load are considered simultaneously. In the proposed method that considers the occurrence of a destructive incident in important production units in the worst-case scenarios and by using the generation capacity, adaptive frequency load shedding, and interrupting contracts, an effective strategy was provided to solve the unit commitment problem of thermal units to prevent instability in system frequency and to minimize unwanted load shedding. The proposed model was tested and evaluated on the IEEE 39-bus system with a wind power plant and a solar power plant. Moreover, the results obtained from simulation were reported. The effectiveness of this innovative approach in increasing the resilience of the power system against different degrees of uncertainty was confirmed based on the results.
Advanced Energy Technologies
Purna Prakash Kasaraneni; Pavan Kumar Yellapragada Venkata
Abstract
Smart homes are considered to be the subset of smart grids that have gained widespread popularity and significance in the present energy sector. These homes are usually equipped with different kinds of sensors that communicate between appliances and the metering infrastructure to monitor and trace the ...
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Smart homes are considered to be the subset of smart grids that have gained widespread popularity and significance in the present energy sector. These homes are usually equipped with different kinds of sensors that communicate between appliances and the metering infrastructure to monitor and trace the energy consumption details. The smart meters trace the energy consumption data continuously or in a period of intervals as required. Sometimes, these traces will be missed due to errors in communication channels, an unexpected breakdown of networks, malfunctioning of smart meters, etc. This missingness greatly impacts smart home operations such as load estimation and management, energy pricing, optimizing assets, planning, decision making, etc. Moreover, to implement a suitable precautionary measure to eliminate missing of data traces, it is required to understand the past behavior of the data anomalies. Hence, it is essential to comprehend the behavior of missing data in the smart home energy consumption dataset. In this regard, this paper proposes an analytical approach to detect and quantify the missing data instants in all days for all appliances. Using this quantification, the behavior of missing data anomalies is analyzed during the day. For the analysis, a practical smart home energy consumption dataset ‘Tracebase’ is considered. Initially, the existence and the count of missing instants are computed. From this, the appliance ‘MicrowaveOven’ is considered for further analysis as it comprises the highest count of missing instants (84740) in a day when compared to all other appliances. Finally, the proposed analysis reveals that the large number of missing instants is occurring during the daylight period of a day.
Advanced Energy Technologies
Vahid Nazari; Mohammad Hossein Mousavi; Hassan Moradi CheshmehBeigi
Abstract
Over the past decades, power engineers have begun to connect power grids to other networks such as microgrids associated with renewable units using long transmission lines to provide higher reliability and greater efficiency in production and distribution besides saving resources. However, many dynamic ...
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Over the past decades, power engineers have begun to connect power grids to other networks such as microgrids associated with renewable units using long transmission lines to provide higher reliability and greater efficiency in production and distribution besides saving resources. However, many dynamic problems such as low frequency oscillations were observed as a result of these connections. Low frequency oscillation is a normal phenomenon in most power systems that causes perturbations and, thus, the grid stability and damping process are of paramount importance. In this paper, to attenuate these oscillations, a novel method for designing Power System Stabilizer (PSS) is presented via Linear Parameter-Varying (LPV) approach for a Single Machine Infinite Bus system (SMIB). Because the system under study is subject to frequent load and production changes, designing the stabilizer based on the nominal model may not yield the desired performance. To guarantee the flexibility of the stabilizer with respect to the aforementioned issues, the power system polytopic representation is used. In order to apply the new method, the nonlinear equations of the system at each operating point, located in a polytope, are parametrically linearized by scheduling variables. Scheduling variables can be measured online in any operating point. By using this model and following the H∞ synthesis, feedback theories, and Linear Matrix Inequalities (LMIs), LPV controllers at all operating points are obtained. Finally, the simulation results verify the effectiveness of the proposed controller over classic and robust controllers with regard to uncertainties and changes in system conditions.
