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Enhancing PV system modeling accuracy with the irradiance intensity selection technique
(2026-06-01)
Songtrai, Sasiwimon
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Chinnavornrungsee, Perawut
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Sriprapha, Kobsak
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Kobayashi, Tomonao
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Niemcharoen, Surasak
This study is a method to improve the accuracy of photovoltaic (PV) power modeling by the irradiance intensity segmentation. The developed model was compared with 2 years of data from PV system in Thailand and the original 1D5P and weight function models to determine accuracy. The results show that by applying the irradiance intensity selection technique with a 1D5P equivalent circuit model improved the accuracy of the proposed model. The proposed method achieved a significantly lower %root mean square error (%RMSE) compared with other models yielding %RMSE values of 0.26% under clear-sky and 2.80% under cloudy conditions. Seasonal evaluation further demonstrated improved prediction accuracy, with the lowest deviation observed during the rainy period, attributed to reduced dust accumulation. A 2 years comparison confirmed the proposed model exhibited the lowest deviation of 0.69%, outperforming conventional PV simulation programs. These findings indicate that irradiance segmentation enhances forecasting performance and provides accurate PV output estimation under real environmental conditions.
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An Intelligent Voltage Control With Power Loss Model Integration in Active Distribution Network
(2025-01-01)
Pinthurat, Watcharakorn
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Deanseekeaw, Anurak
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Surinkaew, Tossaporn
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Boonraksa, Terapong
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Boonraksa, Promphak
The increasing integration of renewable energy sources (RESs), particularly distributed PV systems, poses significant challenges to voltage stability in modern distribution systems. Existing studies use reactive power control to address voltage deviations but incur high losses, with no systematic solution achieving both voltage regulation and loss minimization. This paper proposes a novel voltage control strategy based on multi-agent deep reinforcement learning (MADRL), leveraging decentralized agent coordination to maintain voltage levels while minimizing PV inverter and system losses. Also, a new framework is formulated based on a Markov game, wherein each PV inverter operates as an autonomous agent that adjusts its reactive power output via a centralized training process. The agents, defined as PV inverters, employ the multi-agent twin-delayed deep deterministic policy gradient algorithm to collaboratively minimize voltage deviations. Through the use of local observations and shared global information during training, agents learn robust control policies that generalize to varying conditions and enable decentralized execution without ongoing coordination. Performance of the proposed control strategy is validated on a modified IEEE 33-node distribution system under high variability in PV generation and load demand. Results show that the proposed control strategy significantly improves voltage regulation and reduces power losses compared to state-of-the-art MADRL techniques.
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Potential of Photovoltaic on Small Stratospheric Satellite in Real-World Experiment
(2023-01-01)
Techavijit, Pirada
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Wongphuangfuthaworn, Natthapong
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Sukchalerm, Polkit
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Plodpai, Aniwat
This paper investigates the potential of monocrystalline photovoltaic (PV) panels to generate power when installed on stratospheric satellites through near-space flight experiments conducted at altitudes of 0-23 kilometers above sea level. It also compares the results with a mathematical model developed by ASHRAE in previous research, which reveals the differences caused by various factors such as atmospheric attenuation and high-level clouds. The main objective of this study is to identify the optimal altitude for deploying stratospheric satellites with appropriately sized PV panels that can generate sufficient power to meet the communication system's requirements for long-term operation.
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Coordinated PHEV, PV, and ESS for Microgrid Frequency Regulation Using Centralized Model Predictive Control Considering Variation of PHEV Number
(2018-01-01)
Pahasa, J.
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Ngamroo, I.
The integration of plug-in hybrid electric vehicles (PHEVs), photovoltaic (PV) generators, and energy storage systems (ESSs) into microgrids is highly anticipated. A coordinated control of PHEVs, PVs, and ESS will support frequency control in a microgrid. However, the size of the ESS depends on the surplus power of PV. The lower the surplus power is, the smaller the size of ESS. Furthermore, the number of available PHEVs vary with the cumulative number of the participating PHEVs. This variation of the number of PHEVs may reduce the PHEVs' control effect in the microgrid. This paper proposes a coordinated control of PHEVs, PVs, and ESSs for frequency control in the microgrid using a centralized model predictive control (CMPC) considering the variation of PHEV numbers. The objectives of the coordinated control are: 1) to suppress the system frequency fluctuation and 2) to minimize the surplus power of PV and, therefore, reduce the size of ESS. Simulation studies indicate that the coordinated control of PHEVs, PVs, and ESSs by the proposed CMPC is superior to that of the proportional integral derivative control and the distributed MPC in terms of minimizing the frequency fluctuation, the PV surplus power, and the ESS size.
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Design of active power controller of a BESS in AC microgrids
(2015-08-17)
Prompinit, Krisada
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Khomfoi, Surin
Active power control of a battery energy storage system (BESS) in ac microgrids is presented in this paper. PI controller design is also proposed. The simulation model using PSIM 9.0 is used to validate the designed controller. Actual data collected from data acquisition system in ac microgrids is used to validate the designed controller including photovoltaic (PV) generation profile, wind generation profile and demand load profile. All actual profiles are recorded from a real microgrid application. A BESS controller is validated into two scenarios. First, a BESS operates with PV generation and demand load. Second, a BESS operates with PV generation, wind generation and demand load. The simulation results suggest that the designed PI controller can perform active power compensation in the ac microgrid satisfactorily.
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Sugeno fuzzy logic control-based smart PV generators for frequency control in loop interconnected power systems
(2014-10-15)
Sa-Ngawong, Nattapol
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Ngamroo, Issarachai
This paper proposes a smart photovoltaic (PV) generator equipped with the Sugeno fuzzy logic controller (SFLC) for load frequency control (LFC) in a loop interconnected power system. With high computation efficient and without time consuming in defuzzification, the SFLC is used to quickly control the AC power output of the PV inverter so that the system frequency deviation is alleviated. Since the solar insolation change and system frequency deviation are used as the input signals, the SFLC can suitably adapt its control performance. Simulation results in a three-area loop interconnected power system confirm that the PV with the proposed SFLC not only effectively alleviates the fluctuation of system frequency and tie-line power flow, but also supply output power near the maximum power point during frequency control. Besides, the control effect of PV with SFLC is superior to that of the PV with maximum power point tracking control under random solar insolations and load changes.
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Transient stabilization of power swing by controllable PV farm equipped with optimal fuzzy gain scheduling of PID controller
(2014-10-15)
Chaiyatham, Theerawut
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Ngamroo, Issarachai
The severe faults in power systems may cause the power swing and transient instability. On the other hand, recently, the large photovoltaic (PV) farms have been extensively installed in power systems. With the ability of PV inverter, it is possible to control the PV output power quickly to stabilize the power swing. This paper proposes an optimal fuzzy gain scheduling of PID (FGS-PID) controller equipped with the PV inverter for stabilization of power swing. Without trial and error, the scale factors, membership functions and control rules of the FGS-PID controller are automatically obtained by a bee colony optimization. Simulation study in a single machine infinite bus system confirms the superior stabilizing effect of the PV with proposed FGS-PID in comparison to the PV with MPPT and the PV with PID.
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Round-robin measurement intercomparison of c-Si PV modules among Asian testing laboratories
(2013-08-01)
Hishikawa, Yoshihiro
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Liu, Haitao
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Hsieh, Hsin Hsin
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Inoue, Takamitsu
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Kim, Kyung Soo
Because of recent advances in the production and installation of photovoltaic (PV) systems, the international conformity of PV module performance measurement has become increasingly important. The increase in PV production sites is particularly significant in the Asian region. The present paper summarizes and discusses the results of a round-robin intercomparison of crystalline silicon modules among national laboratories and certified testing laboratories in the Asian region conducted from 2009 to 2011. Most of the values of P<inf>max</inf> measured at the different laboratories were within a ±2% range, although some P<inf>max</inf> results showed differences of up to about 3%. This result is comparable to that obtained in the recent intercomparison among international laboratories. Possible sources of difference in the measured values of I<inf>sc</inf>, V<inf>oc</inf>, FF, and P <inf>max</inf> are discussed, for further improvement of international conformity in PV measurement technologies. Copyright © 2012 John Wiley & Sons, Ltd. Results of a round-robin intercomparison of crystalline silicon modules among national laboratories and certified testing laboratories in the Asian region are discussed. Most of the values of P<inf>max</inf> measured at the different laboratories were within a ±2% range, although some P <inf>max</inf> results showed differences of up to about 3%. Possible sources of difference in the measured values of I<inf>sc</inf>, V<inf>oc</inf>, FF, and P<inf>max</inf> are discussed, for further improvement of international conformity in photovoltaic measurement technologies. Copyright © 2012 John Wiley & Sons, Ltd.
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Bee colony optimization of battery capacity and placement for mitigation of voltage rise by PV in radial distribution network
(2012-12-01)
Chaiyatham, Theerawut
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Ngamroo, Issarachai
At present, the penetration of photovoltaic (PV) power generation in the distribution network tends to increase considerably. However, when the PV sources are located at the ending bus of the radial network, they may cause a reverse power flow and a voltage rise problem. To reduce the voltage rise, the battery energy storage can be used. Nevertheless, the inevitable problem of battery is the high installation cost. The optimal placement and capacity of battery are the vital issue to be considered. In this paper, the bee colony optimization is applied to find the optimal placement and capacity of battery in the radial distribution network for alleviating the voltage rise due to PV sources. Simulation results under several scenarios indicate the superior control effect of the optimized battery over the non-optimal battery. © 2012 IEEE.

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