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Optimal integration location and sizing of renewable energy systems in AC railways for cost optimisation
(2026-01-01)
Chinomi, Nutthaka
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Tian, Zhongbei
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Kano, Nakaret
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Chow, Chompoo inwai
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Jiang, Lin
This study presents a bi-level optimisation framework for the optimal integration of Photovoltaic (PV) systems and Energy Storage Systems (ESS) in AC railway traction power supply networks. The framework addresses two key objectives: determining the optimal capacities and selecting effective integration locations for PV and ESS to enhance energy efficiency and reduce operational costs. At the master level, a grid search explores combinations of PV and ESS sizes and locations, while the slave level employs a mixed-integer linear programming model solved with CPLEX to optimise ESS charge/discharge operations under variable energy conditions. Case studies demonstrate that integrating a 10 MW PV system with a 1 MWh, 2 MW ESS can reduce daily operational costs by 30 % (from 20152 £/d to 14007 £/d). The system shows resilience to short-term fluctuations in solar irradiance but exhibits higher sensitivity during extended low-irradiance periods. These findings highlight the importance of carefully balancing system configuration, operational strategies, and renewable energy variability. Overall, the proposed approach provides a structured methodology for achieving cost-effective and sustainable PV-ESS integration in railway electrification systems, supporting both economic and operational performance objectives.
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Design of DC/AC Unidirectional Inverter Based on DSP with Second-Order Switching Sequence Control in Photovoltaic DC Nano-Grids
(2025-01-01)
Bi, Chenxing
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Jiriwibhakorn, Somchat
Conventional inverters predominantly utilize Pulse-Width Modulation (PWM) control, operating in an intermediate state between the averaged and actual switching models. However, this approach often results in suboptimal output power quality and limited dynamic performance, which can compromise the operational stability of AC load systems. To address these limitations, this paper proposes a second-order Switching Sequence Control (SSC) strategy based on sliding mode theory, offering discrete-time control with enhanced robustness and precision. A comprehensive mathematical model of a single-phase LC inverter is developed and discretized. The SSC control algorithm is implemented using a TMS320F28335 Digital Signal Processor (DSP), with code generated via MATLAB/Simulink to streamline development and ensure real-time execution. Extensive simulations under various conditions demonstrate that the proposed inverter achieves excellent tracking accuracy, strong dynamic response, and reduced Total Harmonic Distortion (THD) is only 0.48%. Compared with conventional PWM, Selective Harmonic Elimination (SHE), and FPGA-based control methods, the SSC strategy significantly improves waveform fidelity and transient performance. These results confirm its suitability for high-performance applications in photovoltaic DC nanogrids, smart energy systems, and critical load support scenarios.
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Optimum Generated Power for a Hybrid DG/PV/Battery Radial Network Using Meta-Heuristic Algorithms Based DG Allocation
(2023-07-01)
Abdelwareth, Mohamed Els S.
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Riawan, Dedet Candra
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Chompoo-inwai, Chow
This paper presents four optimization outcomes for a diesel generator (DG), photovoltaic (PV), and battery hybrid generating radial system, to reduce the network losses and achieve optimum generated power with minimum costs. The effectiveness of the four utilized meta-heuristic algorithms in this paper (firefly algorithm, particle swarm optimization, genetic algorithm, and surrogate optimization) was compared, considering factors such as Cost of Energy (COE), the Loss of Power Supply Probability (LPSP), and the coefficient of determination (R<sup>2</sup>). The multi-objective function approach was adopted to find the optimal DG allocation sizing and location using the four utilized algorithms separately to achieve the optimal solution. The forward-backward sweep method (FBSM) was employed in this research to compute the network’s power flow. Based on the computed outcomes of the algorithms, the inclusion of an additional 300 kW DG in bus 2 was concluded to be an effective strategy for optimizing the system, resulting in maximizing the generated power with minimum network losses and costs. Results reveal that DG allocation using the firefly algorithm outperforms the other three algorithms, reducing the burden on the main DG and batteries by 30.48% and 19.24%, respectively. This research presents an optimization of an existing electricity network case study located on Tomia Island, Southeast Sulawesi, Indonesia.
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Optimum Operation and Cost Scenarios of a Hybrid Wind/PV/Battery in a Radial Network using Genetic Algorithm and Particle Swarm Optimization
(2022-01-01)
Abdelwareth, Mohamed Els S.
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Riawan, Dedet Candra
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Chompoo-Inwai, Chow
Hybrid generation systems took the attention of many researchers searching for the best energy source that can be optimum, reliable, and scalable instead of dependency on the traditional fossil fuels sources; researchers are developing Artificial Intelligence (AI) algorithms to optimize those systems. This paper will study the optimum generating power from a Wind turbine, PV, and Battery linked to the radial network in Tomia Island, considering the optimum cost using Particle Swarm Optimization (PSO) and Genetic Algorithm (GA).
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Design of zero energy consumption system for small DC residential home based on off-grid PV system
(2018-01-01)
Chandanachulaka, Nidchabendha
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Khan-Ngern, Werachet
This research presents the design of a zero energy consumption system (ZECS) based on off-grid photovoltaic (PV) system for small DC system whose load demand is less than 1 kWh/day. This system consists of 3 parts: 300 W PV panel, energy conversion or solar charger, and 12 V 200 Ah energy storage. The used electrical utilizing system consists of 3 types: 20 W LED lighting system, 35 W fan for air cooling system, and 100 W electrical boiler or heating system, whose average load requirement is 0.795 kWh/day. This research defines 6 key sustainability parameters and key performance indicators in order to evaluate the benefits of ZECS, which are design, energy security, system availability, efficiency, environment and investment. The result has been analyzed and it was found that ZECS can achieve more than 80% of the energy conversion efficiency and it can operate for 2 days without charging the battery. The battery charging and discharging from PV are demonstrated to confirm ZECS energy security. The utilization ratio or the energy that required per one square meter is less than 50 Wh/m2. DC ZECS and DC electric appliances are available, affordable and easy to be maintained. ZECS is designed in order to provide the electricity for low-income people in remote areas, and its social benefits are more important than the return on investment. It can be concluded that DC utilizing system is reliable for ZECS which can benefit to apply this system in remote area where it cannot connect to the grid.
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A novel power output model for photovoltaic system
(2017-10-19)
Kittisontirak, Songkiate
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Dawan, Promphak
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Atiwongsangthong, Narin
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Titiroongruang, Wisut
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Chinnavornrungsee, Perawut
This paper proposed the novel concept model for forecasting the PV power output. The model was used two meteorology to input model which are solar irradiance and module temperature. This model was improve the accuracy of model from simplified model is 1D5P by using the weight function. The proposed model was verified by comparison with measured data. The results showed that the model has high accuracy. The RMSE ranges from 0.02 to 0.07 and average RMSE is 0.04.
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A simplified model for the estimation of energy production of PV Module
(2017-10-19)
Bupi, Aekkawat
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Kittisontirak, Songkiate
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Sriprapha, Kobsak
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Siriwongrungsan, Wilailak
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Titiroongruang, Wisut
This paper describes the objective of the model to produce electricity from solar cell applications MATLAB / SIMULINK Compared with the data of electricity from photovoltaic power systems in Cambodia. Using models 1D5P (equivalent circuit analysis of one of the diodes, solar cells based on 5 parameters are the main factors in the equation that represents the equivalent circuit). 2 parameters are used to simulate the solar irradiance and module temperature from the retention of a calculation to determine the solar farm to generate electricity. And compared with the actual electricity. By comparing the results of the simulation with high accuracy. And display of the RMSE range of 0.01 to 0.18 and with an average of RMSE is 0.09.
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Comparison of PV estimation model with measured PV power output
(2017-10-19)
Kittisontirak, Songkiate
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Niemcharoen, Surasak
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Titiroongruang, Wisut
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Limmanee, Amornrat
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Sitthiphol, Nopphadol
This paper describes a comparison of proposed model with simulation software and measurement data of PV power plant in Cambodia. The proposed model is based on behavior of PV module at a particular site. The parameters which affected to PV power output as solar irradiance and module temperature were used as input in this model. Weight function technics were used to improve accuracy of single diode five parameters (1D5P). It was found that the proposed model can improve the accuracy of PV power output estimation model.
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Comparison of PV module power output measurements
(2017-10-19)
Bupi, Aekkawat
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Kittisontirak, Songkiate
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Sriprapha, Kobsak
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Suriyaammaranon, Chabar
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Titiroongruang, Wisut
This paper describes the objective of the model to produce electricity from solar program. MATLAB / SIMULINK Compared with actual production data from electricity plants. This information is taken from the program PVSYST (crawlers electricity from real factories). The models created from an analysis of the equivalent circuit model of a diode, solar cell, with 5 parameters are the main factors used in the calculations were called 1 D5 P. The comparison takes into account the impact on solar irradiance and module temperature. The result of the comparison. The model has high accuracy and is close to the actual data to generate electricity.
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Comparison of distributed and Centralized control for partial shading in PV parallel based on Particle Swarm Optimization Algorithm
(2014-10-15)
Jumpasri, Nattawat
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Pinsuntia, Kittapas
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Woranetsuttikul, Kaweepoj
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Nilsakorn, Taywin
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Khan-Ngern, Werachet
This paper presents the comparison of Distributed Control and Centralized Control for partial shading in PV parallel based on the Particle Swarm Optimization Algorithm. The distributed control is the connection of PV 1 panel with 1 MPPT and the centralized control is the connection of many PV panels with 1 MPPT. Both methods have difference advantage, efficiency, cost and maintenance. The simulation of both methods made in Powersim and Matlab Simulink. The analysis and conclusion were included.

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