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Minimize renewable distributed generator costs while achieving high levels of system uniformity and voltage regulation

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AIN SHAMS ENGINEERING JOURNAL 2024年第6期15卷

作者： Pham, Thai Dinh Kien, Le Chi Nguyen, Thang Trung Ho Chi Minh City Univ Technol & Educ Fac Elect & Elect Engn Ho Chi Minh City Vietnam Ton Duc Thang Univ Fac Elect & Elect Engn Power Syst Optimizat Res Grp Ho Chi Minh City Vietnam

This research facilitates the placement of solar and wind-powered distributed generators (RDGs) in an unbalanced 3-phase IEEE 25-node distribution system intended to minimize the total expense of buying electricity from the grid and releasing carbon dioxide over twenty years. The probability distribution functions of Beta and Rayleigh are employed to attain solar illumination and wind velocity in a particular region. Unbalanced voltage deviation (UVD) and harmonic flows (HFs) from non-ideal loads and RDGs are considered. Metaheuristic methods are coded in MATLAB to find RDGs' location and capacity, and then OpenDSS is used to calculate power and harmonic issues. As a result, the total expenses can be reduced to $1.4141 million, which is 10.7% of the base system's. Additionally, HFs and UVDs at every node follow the IEEE Std. 519 and the IEEE Std. 45-2002, respectively. So, the placement of RDGs has a beneficial position in unbalanced distribution systems.

关键词： modified coyote optimization algorithm Photovoltaic module Wind turbine Power loss Voltage profile

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Integration of Photovoltaic Units, Wind Turbine Units, Battery Energy Storage System, and Capacitor Bank in the Distribution System for Minimizing Total Costs Considering Harmonic Distortions

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IRANIAN JOURNAL OF SCIENCE AND TECHNOLOGY-TRANSACTIONS OF ELECTRICAL ENGINEERING 2023年第4期47卷 1265-1282页

作者： Pham, Thai Dinh Ho Chi Minh City Univ Technol & Educ Fac Elect & Elect Engn Ho Chi Minh City Vietnam

This paper presents an effective method, named modified coyote optimization algorithm (MCOA), for determining the optimal integration of photovoltaic units (PVs), wind turbine units (WTs), battery energy storage system (BESS), and capacitor bank (CB) in the IEEE 69-bus radial distribution system. This research is developed with the goal of minimizing the total costs of investment, operation and maintenance (O&M) for PVs, WTs, BESS, and CB as well as energy purchase cost from the main grid considering time-varying load demand and generation units. The simulation results demonstrate total costs in operating the integrated system can be significantly minimized by the proper connection of PVs, WTs, BESS, and CB. On the other hand, the study also considers the test system under the condition of many nonlinear loads, and the approach has been successful in mitigating harmonics to the IEEE Std. 519. In addition, the proposed method (MCOA) is also compared with the original coyote optimization algorithm (COA) and slime mould algorithm (SMA) to prove its effectiveness in solving the optimization problems.

关键词： modified coyote optimization algorithm Wind turbine units Photovoltaic units Capacitor bank Battery energy storage system Harmonic flows

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Minimization of total costs for distribution systems with battery energy storage systems and renewable energy sources

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SCIENTIFIC REPORTS 2025年第1期15卷 1-24页

作者： Pham, Thai Dinh Nguyen, Thang Trung Kien, Le Chi Ho Chi Minh City Univ Technol & Educ Fac Elect & Elect Engn Ho Chi Minh City Vietnam Ton Duc Thang Univ Fac Elect & Elect Engn Power Syst Optimizat Res Grp Ho Chi Minh City Vietnam

The penetration of renewable energy distributed generation units in the distribution systems has become widespread due to its many techno-economic and environmental benefits. However, avoiding the unwanted effects of unplanned integration and maximizing the resulting benefits is challenging. Thus, this research introduces a powerful method called modified coyote optimization algorithm (MCOA) for identifying the optimal installation of wind turbine farms (WFs), photovoltaic farms (PVFs), and battery energy storage systems (BESS) in IEEE 123-bus unbalanced distribution system (UDS) and Nha Be 55-bus balanced distribution system (BDS) in Nha Be District, Ho Chi Minh City, Vietnam to minimize total costs. The considered costs include (1) investment, operation, and maintenance (O&M) costs of WFs, PVFs, and BESS;(2) imported energy cost for loads and power losses from the main power grid;and (3) generated emission cost from conventional power plants considering time-varying generation and consumption. Besides, this work also suggests an open-source simulator (OpenDSS) for addressing the power flow problem and develops a co-simulation between two active software (OpenDSS and MATLAB) through the component object model (COM) interface for addressing the continuous optimization problems. The proposed solution by MCOA has demonstrated superiority over other methods through total cost savings of up to 24.13% and 27.46% in IEEE 123-bus UDS and 55-bus BDS, while the values are only 23.11% and 26.50% for salp swarm algorithm (SSA) and 23.76% and 26.78% for coyote optimization algorithm (COA), respectively, as compared to the original cases. Besides, the optimal solution also satisfied the declared constraints as well as the standards for bus voltage, line current, and harmonic distortions.

关键词： modified coyote optimization algorithm Battery energy storage system Photovoltaic farms Unbalanced distribution system Wind turbine farms

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Optimal Power Flow for Transmission Power Networks Using a Novel Metaheuristic algorithm

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ENERGIES 2019年第22期12卷 4310-4310页

作者： Li, Zelan Cao, Yijia Le Van Dai Yang, Xiaoliang Thang Trung Nguyen Hunan Univ Coll Elect & Informat Engn Changsha 410082 Hunan Peoples R China Duy Tan Univ Inst Res & Dev Da Nang 550000 Vietnam Zhengzhou Univ Light Ind Coll Elect & Informat Engn Zhengzhou 450002 Henan Peoples R China Ton Duc Thang Univ Fac Elect & Elect Engn Power Syst Optimizat Res Grp Ho Chi Minh City 700000 Vietnam

In the paper, a modified coyote optimization algorithm (MCOA) is proposed for finding highly effective solutions for the optimal power flow (OPF) problem. In the OPF problem, total active power losses in all transmission lines and total electric generation cost of all available thermal units are considered to be reduced as much as possible meanwhile all constraints of transmission power systems such as generation and voltage limits of generators, generation limits of capacitors, secondary voltage limits of transformers, and limit of transmission lines are required to be exactly satisfied. MCOA is an improved version of the original coyote optimization algorithm (OCOA) with two modifications in two new solution generation techniques and one modification in the solution exchange technique. As compared to OCOA, the proposed MCOA has high contributions as follows: (i) finding more promising optimal solutions with a faster manner, (ii) shortening computation steps, and (iii) reaching higher success rate. Three IEEE transmission power networks are used for comparing MCOA with OCOA and other existing conventional methods, improved versions of these conventional methods, and hybrid methods. About the constraint handling ability, the success rate of MCOA is, respectively, 100%, 96%, and 52% meanwhile those of OCOA is, respectively, 88%, 74%, and 16%. About the obtained solutions, the improvement level of MCOA over OCOA can be up to 30.21% whereas the improvement level over other existing methods is up to 43.88%. Furthermore, these two methods are also executed for determining the best location of a photovoltaic system (PVS) with rated power of 2.0 MW in an IEEE 30-bus system. As a result, MCOA can reduce fuel cost and power loss by 0.5% and 24.36%. Therefore, MCOA can be recommended to be a powerful method for optimal power flow study on transmission power networks with considering the presence of renewable energies.

关键词： coyote optimization algorithm modified coyote optimization algorithm transmission power system success rate photovoltaic systems

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