Load frequency control resilience of hybrid power system with renewable energy sources and superconducting magnetic energy storage using FO-Fuzzy-PID controller Misagh Jalilian, Abdollah Rastgou, Saeed Kharrati, Saman Hosseini-Hemati Results in Engineering, 2025 The integration of renewable energy sources (RES) such as wind and solar presents challenges for load frequency control (LFC) in power systems due to their unpredictability. This study investigates the use of superconducting magnetic energy storage (SMES) in LFC systems, combined with an innovative adaptive controller of the fractional order fuzzy proportional-integral-derivative (FO-Fuzzy-PID) type optimized by particle swarm optimization (PSO). Simulation results indicate that the FO-Fuzzy-PID adaptive controller significantly enhances system performance, achieving a remarkable reduction in peak undershoot by 70.3% (from 0.089 Hz to 0.026 Hz) and an improvement in settling time by 57.1% (from 28 seconds to 12 seconds) when integrated with SMES. In one scenario, the controller demonstrated a peak undershoot of -0.001 and a rapid settling time of 5 seconds. In other Scenario, it achieved the lowest integral of time-weighted absolute error (ITAE) value of 0.0061, representing a 44.5% improvement over the PSO-PID controller's ITAE of 0.11. These results highlight the effectiveness of combining SMES with advanced control strategies to enhance dynamic performance and stability in power networks, facilitating the reliable integration of RES. The adaptability of the proposed controller ensures its performance remains robust under varying conditions, emphasizing its potential for large-scale implementation in real-time control applications. • Renewable energy's unpredictability complicates load frequency control (LFC) in power systems. • This study uses a fractional order-Fuzzy PID controller optimized by particle swarm optimization. • The proposed controller reduced peak undershoot by 70.3% and improved settling time by 57.1% with SMES. • The FO-Fuzzy-PID controller shows strong adaptability for reliable performance in varying real-time conditions.
Planning and management of a smart home connected to microgrid in the presence of CHP sources Arash Karami, Abdollah Rastgou, Saman Hosseini-Hemati, Saeed Kharrati, Maryam Shirzadian Gilan Results in Engineering, 2025 In recent years, the access of many countries to microgrids has improved the quality and development of their economy. So far, a lot of research has been done in this regard. The results of this work show that there is a direct relationship between a country's level of development and its energy consumption. Many energy sources such as electricity and natural gas have so far been used separately. However, today, with the increased use and the advancement of production technologies, establishing a connection between energy systems has become a necessity. Therefore, energy sources are properly combined and integrated in order to increase the efficiency of the system. The use of combined heat and power and the presence of microgrids providing PV and wind energy in the network can effectively supply a part of the load. This paper considers linear programming, and smart home management based on connected microgrids to obtain electric and heating energy in a residential complex. The smart building is designed for 30 households with similar consumption habits. Next to each renewable source, a storage generator is considered which therefore constitutes an integrated resource. In order to protect the resources and observe their power limits, household appliances, demand response, charging, and discharging, and storage properties are taken into account in the problem. In order to manage equipment consumption, it is also necessary to adjust the performance interval, so that the cost for the consumer is optimized based on the hourly cost of power and the producer's profit. To this effect, the load profile of the complex is planned, and thus the cost functions under certain conditions. MATLAB tools for linear programming are used. We will see that for the four scenarios introduced, the total operating cost for the first scenario is ($)328.12, the second scenario is ($)267.54, the third scenario is ($)254.38, and the fourth scenario is the best cost with a value of ($)198.08. Also, the amount of CHP capacity has been examined based on different capacities from 5 kW to 100 kW.
Developing a cooperative approach under normal and contingency conditions for generation expansion planning of microgrids Saeed Shahbazian, Saeed Kharrati, Abdollah Rastgou Iet Renewable Power Generation, 2024 The issue of generation expansion planning in microgrids has become a challenging issue in electricity industry for two reasons: load growth and uncertainties in renewables' generation. Therefore, this issue is considered here. Here, the modelling of generation expansion planning problem has been developed in a network of microgrids in a decentralized manner, considering normal and contingency conditions. On the other hand, in order to further develop the study considered, decentralized generation expansion planning model of microgrids by considering contingency conditions has been addressed in a cooperative approach to minimize total costs. In developed model, investment decisions are made at the higher level and operational constraints has been considered at lower one. Also, case studies are defined in three different scenarios: islanding operation of microgrids as first scenario and peer‐to‐peer trading of microgrids in non‐cooperative and cooperative approaches as second and third scenarios, respectively. The results of simulations have shown that by facilitating the transactions between microgrids, their total costs are reduced. The costs of the whole set of microgrids in the non‐cooperative scenario are reduced by 9.4% compared to the islanding scenario; and the costs are reduced by 7.5% in the cooperative scenario compared to the non‐cooperative scenario.
Simultaneous costs minimizing in electricity and gas micro-grids with the presence of distributed generation Shahryar Behnia, Saeed Kharrati, Farshad Khosravi, Abdollah Rastgou Plos One, 2024 Distributed generation can actively participate in the day-ahead markets, real-time power balance, and wholesale gas markets to achieve various goals, such as supplying gas to various electric power generation plants. A multi-objective network with two types of loads is considered in this paper. The reason for the simultaneous optimization of these two networks is that these two energy carriers are dependent on each other and gas is needed to produce electricity, so this issue can be addressed with a multi-objective function. The simulation carried out in this article is coded in GAMS software as a mixed integer linear programming (MILP). The efficiency of gas turbines and fuel cells in this article is dependent on their working point, and considering the exact model of these resources and the relationships related to the calculation of their fuel consumption is non-linear. On the other hand, a binary variable has been used to show the charging and discharging state of the storage and the on-and-off state of the gas turbines. Therefore, the problem considered in this article is a MILP problem. The results of this article are the proper planning of charging and discharging of the energy storage system with the proper planning of the power generation of different energy sources considering the network loads in two optimized and non-optimized scenarios.
Utilizing RDPSO Algorithm for Economic-Environmental Load Dispatch Modeling Considering Distributed Energy Resources Farzad Habibi, , Farshad Khosravi, Saeed Kharrati, Shahram Karimi, , , and Electrica, 2021 There are many factors such as long construction time, high investment cost, and low competition between energy providers to justify penetrating the distributed energy resources (DERs) such as wind turbines (WTs) and demand response programs (DRPs) in power systems. The uncertainties about WTs’ power output have increased the complexity of the economic-environmental load dispatch (EELD) problem. Because it is very difficult to predict the output power of wind farms, additional costs are imposed to the EELD problem. The mean amount of wind energy density has been used to define the storage and additional costs in the developed model. In addition, the DRPs have been facing the problem in reduction of cost. Demand response programs have been considered in two approaches; in the first approach, a certain percentage of the buses’ load determines the maximum amount of participation of the DRPs and in the second one, a certain capacity of these programs determines the maximum amount of their participation. The efficiency of the developed model has been analyzed by simulation results on multi-area IEEE 118 bus test system. The operational constraints in the test system, including lines limit, supply–demand balance and the generation limit of generators, WTs, and DRPs have been considered in the EELD problem. Multi-objective Random Drift Particle Swarm Optimization (MORDPSO) has been used in this study to analyze the model. The effects of DERs have been analyzed on power loss, voltage profile, and static voltage stability of the test system. Cite this article as: F. Habibi, F. Khosravi, S. Kharrati and S. Karimi. “Utilizing RDPSO Algorithm for Economic-Environmental Load Dispatch Modeling Considering Distributed Energy Resources,” Electrica. vol. 21, no. 3, pp. 444-457, Sep. 2021.
Simultaneous Multi-area Economic-Environmental Load Dispatch Modeling in Presence of Wind Turbines by MOPSO Farzad Habibi, Farshad Khosravi, Saeed Kharrati, Shahram Karimi Journal of Electrical Engineering and Technology, 2020 Multi-objective particle swarm optimization (MOPSO) algorithm was proposed in this paper to solve the load dispatch problem among thermal and wind turbines considering the environmental factors in multi-area power systems. The unpredictable nature of wind generations has resulted in the higher complexity of the economic load dispatch (ELD) problem. As the wind farm’s generation is very difficult to predict, the extra cost during the evaluation of the ELD are taken into account as well. In the developed method, the storage and additional cost are defined in the objective function of the ELD problem, using the mean value of wind energy density. The operational constraints among multi-areas, including the transmission lines capacity limit and generation-demand balance constraints as well as the constraints of generation limit of generators are considered in the economic-environmental load dispatch (EELD) problem. The efficiency of the proposed method was evaluated based on the simulation results on IEEE 118 bus test system, considering twelve thermal power plants, two wind farms and three areas.
A modified hybrid prediction method for spinning reserve requirement Mohammad Ferdosian, Hamdi Abdi, Shahram Karimi, Saeed Kharrati 2017 International Conference on Energy Communication Data Analytics and Soft Computing Icecds 2017, 2018 Ancillary services is used to refer to a variety of operations beyond generation and transmission which are requested to maintain grid stability, security and reliability of power system. These services generally consist, frequency control, Spinning Reserves (SR) and operating reserves. Accordingly, an accurate day ahead forecast of SR requirement helps the Independent System Operator (ISO) to manage a reliable and economic operation of the power system. This prediction model needs a strong and accurate method to tackle the complexity, non-stationarity and volatility due to the load profile or equipment fault. Hence, a new hybrid forecasting model is proposed in this paper, to solve the SR requirement. The proposed structure consists of three stage Neural Network (NN) based forecast engine with different learning algorithms. Also, the input signal of this forecast engine is filtered by a new Improved Fuzzy Clustering Mechanism (IFCM) to find the high relevancy and low redundancy of features. The proposed strategy is implemented and tested on real data from Pennsylvania-New Jersey-Maryland (PJM) and is compared with other techniques. The resulting numerical results demonstrate the validity of proposed method.
