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Short-term load forecasting (STLF) is fundamental for the proper operation of power systems, as it finds its use in various basic processes. Therefore, advanced calculation techniques are needed to obtain accurate results of the consumption prediction, taking into account the numerous exogenous factors that influence the results’ precision. The purpose of this study is to integrate, additionally to the conventional factors (weather, holidays, etc.), the current aspects regarding the global COVID-19 pandemic in solving the STLF problem, using a convolutional neural network (CNN)-based model. To evaluate and validate the impact of the new variables considered in the model, the simulations are conducted using publicly available data from the Romanian power system. A comparison study is further carried out to assess the performance of the proposed model, using the multiple linear regression method and load forecasting results provided by the Romanian Transmission System Operator (TSO). In this regard, the Mean Squared Error (MSE), the Mean Absolute Error (MAE), the Mean Absolute Percentage Error (MAPE), and the Root Mean Square Error (RMSE) are used as evaluation indexes. The proposed methodology shows great potential, as the results reveal better error values compared to the TSO results, despite the limited historical data.
Andrei Tudose; Irina Picioroaga; Dorian Sidea; Constantin Bulac; Valentin Boicea. Short-Term Load Forecasting Using Convolutional Neural Networks in COVID-19 Context: The Romanian Case Study. Energies 2021, 14, 4046 .
AMA StyleAndrei Tudose, Irina Picioroaga, Dorian Sidea, Constantin Bulac, Valentin Boicea. Short-Term Load Forecasting Using Convolutional Neural Networks in COVID-19 Context: The Romanian Case Study. Energies. 2021; 14 (13):4046.
Chicago/Turabian StyleAndrei Tudose; Irina Picioroaga; Dorian Sidea; Constantin Bulac; Valentin Boicea. 2021. "Short-Term Load Forecasting Using Convolutional Neural Networks in COVID-19 Context: The Romanian Case Study." Energies 14, no. 13: 4046.
The optimal reactive power dispatch (ORPD) problem represents a fundamental concern in the efficient and reliable operation of power systems, based on the proper coordination of numerous devices. Therefore, the ORPD calculation is an elaborate nonlinear optimization problem that requires highly performing computational algorithms to identify the optimal solution. In this paper, the potential of metaheuristic methods is explored for solving complex optimization problems specific to power systems. In this regard, an improved salp swarm algorithm is proposed to solve the ORPD problem for the IEEE-14 and IEEE-30 bus systems, by approaching the reactive power planning as both a single- and a multi- objective problem and aiming at minimizing the real power losses and the bus voltage deviations. Multiple comparison studies are conducted based on the obtained results to assess the proposed approach performance with respect to other state-of-the-art techniques. In all cases, the results demonstrate the potential of the developed method and reflect its effectiveness in solving challenging problems.
Andrei Tudose; Irina Picioroaga; Dorian Sidea; Constantin Bulac. Solving Single- and Multi-Objective Optimal Reactive Power Dispatch Problems Using an Improved Salp Swarm Algorithm. Energies 2021, 14, 1222 .
AMA StyleAndrei Tudose, Irina Picioroaga, Dorian Sidea, Constantin Bulac. Solving Single- and Multi-Objective Optimal Reactive Power Dispatch Problems Using an Improved Salp Swarm Algorithm. Energies. 2021; 14 (5):1222.
Chicago/Turabian StyleAndrei Tudose; Irina Picioroaga; Dorian Sidea; Constantin Bulac. 2021. "Solving Single- and Multi-Objective Optimal Reactive Power Dispatch Problems Using an Improved Salp Swarm Algorithm." Energies 14, no. 5: 1222.
In the electric distribution systems, the “Smart Grid” concept is implemented to encourage energy savings and integration of the innovative technologies, helping the distribution network operators (DNOs) in choosing the investment plans which lead to the optimal operation of the networks and increasing the energy efficiency. In this context, a new phase load balancing algorithm was proposed to be implemented in the low voltage distribution networks with hybrid structures of the consumption points (switchable and non-switchable consumers). It can work in both operation modes (real-time and off-line), uploading information from different databases of the DNO which contain: The consumers’ characteristics, the real loads of the consumers integrated into the smart metering system (SMS), and the typical load profiles for the consumers non-integrated in the SMS. The algorithm was tested in a real network, having a hybrid structure of the consumption points, on a by 24-h interval. The obtained results were analyzed and compared with other algorithms from the heuristic (minimum count of loads adjustment algorithm) and the metaheuristic (particle swarm optimization and genetic algorithms) categories. The best performances were provided by the proposed algorithm, such that the unbalance coefficient had the smallest value (1.0017). The phase load balancing led to the following technical effects: decrease of the average current in the neutral conductor and the energy losses with 94%, respectively 61.75%, and increase of the minimum value of the phase voltage at the farthest pillar with 7.14%, compared to the unbalanced case.
Gheorghe Grigoraș; Bogdan-Constantin Neagu; Mihai Gavrilaș; Ion Triștiu; Constantin Bulac. Optimal Phase Load Balancing in Low Voltage Distribution Networks Using a Smart Meter Data-Based Algorithm. Mathematics 2020, 8, 549 .
AMA StyleGheorghe Grigoraș, Bogdan-Constantin Neagu, Mihai Gavrilaș, Ion Triștiu, Constantin Bulac. Optimal Phase Load Balancing in Low Voltage Distribution Networks Using a Smart Meter Data-Based Algorithm. Mathematics. 2020; 8 (4):549.
Chicago/Turabian StyleGheorghe Grigoraș; Bogdan-Constantin Neagu; Mihai Gavrilaș; Ion Triștiu; Constantin Bulac. 2020. "Optimal Phase Load Balancing in Low Voltage Distribution Networks Using a Smart Meter Data-Based Algorithm." Mathematics 8, no. 4: 549.
In the electric distribution systems, the “Smart Grid” concept is implemented to encourage energy savings and integration of the innovative technologies, helping the Distribution Network Operators (DNOs) in choosing the investment plans which to lead the optimal operation of the networks and increasing the energy efficiency. In this context, a new phase load balancing algorithm was proposed to be implemented in the low voltage distribution networks with hybrid structures of the consumption points (switchable and non-switchable consumers). It can work in both operation modes (on-line and off-line), uploading information from different databases of the DNO which contain: the consumers’ characteristics, the real loads of the consumers integrated into the Smart Metering System (SMS), and the typical load profiles for the consumers non-integrated in the SMS. The algorithm was tested in a real network, having a hybrid structure of the consumption points, on a time interval by 24 hours. The obtained results were analyzed and compared with other algorithms from the heuristic (Minimum Count of Loads Adjustment algorithm) and the metaheuristic (Particle Swarm Optimization and Genetic Algorithms) categories. The best performances were provided by the proposed algorithm, such that the unbalance coefficient resulted in the smallest value (1.0017). The phase load balancing led to the following technical effects: decreasing the average current in the neutral conductor with 94% and for the energy losses with 61.75 %, and increasing the minimum value of the phase voltage at the farthest pillar with the 7.14 %, compared to the unbalanced case.
Gheorghe Grigoras; Bogdan-Constantin Neagu; Mihai Gavrilas; Ion Tristiu; Constantin Bulac. Optimal Phase Load Balancing in Low Voltage Distribution Networks Using a Smart Meter Data-Based Algorithm. 2020, 1 .
AMA StyleGheorghe Grigoras, Bogdan-Constantin Neagu, Mihai Gavrilas, Ion Tristiu, Constantin Bulac. Optimal Phase Load Balancing in Low Voltage Distribution Networks Using a Smart Meter Data-Based Algorithm. . 2020; ():1.
Chicago/Turabian StyleGheorghe Grigoras; Bogdan-Constantin Neagu; Mihai Gavrilas; Ion Tristiu; Constantin Bulac. 2020. "Optimal Phase Load Balancing in Low Voltage Distribution Networks Using a Smart Meter Data-Based Algorithm." , no. : 1.
Microgrids are about to change the architecture and the operation principles of the future power systems towards smartness and resiliency. Power electronics technologies are key enablers for novel solutions. In this paper we analyze the benefits of a “microgrid by design” architecture (MDA), using a solid-state transformer (SST) as a low-voltage grid-former and inverter-based generation only. In this context, the microgrid stability is maintained with the help of “electrostatic energy inertia” that can be provided by the capacitor connected to the DC busbar behind the SST inverter topology. This happens in a natural way, alike the mechanical inertia in power systems with synchronous machines, however without depending on frequency and without the need of a rotational inertia. This type of microgrid always operates (both fully connected to the main grid or in islanding mode) with all the necessary mechanisms needed to maintain the microgrid stable—no matter of the perturbations in the upstream of the point of common coupling (PCC). In the case of microgrids with inverter-based generation only (including the energy storage systems), there is no mechanical inertia and different stability mechanisms need to be applied compared to the stability principle of the classical power systems. Our proposed mechanism differentiates from the recently proposed stability assessments of microgrids based on virtual synchronous generators from the control theory perspective. This paper is a continuation of our previous work where the MDA was first introduced. The use-cases and scenarios are based on realistic and yet reasonable complexities, by coupling the disturbance magnitude with the voltage stability limit in power grids. The paper finds meaningful disturbances to test the electrostatic energy inertia at the boundaries of grid stability, as guidance to understand the range of voltage variation for extreme conditions. The results show that in microgrids with inverter-based generation only and passive loads (RLC type) the operation is no longer frequency dependent. The energy of the DC busbar capacitor as electrostatic energy inertia of the MDA has a role similar to that of the rotational machines in classical grids in terms of maintaining dynamic stability, however impacting two different types of stability.
Mihai Sanduleac; Lucian Toma; Mircea Eremia; Irina Ciornei; Constantin Bulac; Ion Triștiu; Andreea Iantoc; João F. Martins; Vitor F. Pires. On the Electrostatic Inertia in Microgrids with Inverter-Based Generation Only—An Analysis on Dynamic Stability. Energies 2019, 12, 3274 .
AMA StyleMihai Sanduleac, Lucian Toma, Mircea Eremia, Irina Ciornei, Constantin Bulac, Ion Triștiu, Andreea Iantoc, João F. Martins, Vitor F. Pires. On the Electrostatic Inertia in Microgrids with Inverter-Based Generation Only—An Analysis on Dynamic Stability. Energies. 2019; 12 (17):3274.
Chicago/Turabian StyleMihai Sanduleac; Lucian Toma; Mircea Eremia; Irina Ciornei; Constantin Bulac; Ion Triștiu; Andreea Iantoc; João F. Martins; Vitor F. Pires. 2019. "On the Electrostatic Inertia in Microgrids with Inverter-Based Generation Only—An Analysis on Dynamic Stability." Energies 12, no. 17: 3274.