Economic dispatch incorporation solar energy using particle swarm optimization

Augusteen, W A; Geetha, S.; Rengaraj, R.

doi:10.1109/icees.2016.7510618

Cited by 19 publications

(7 citation statements)

References 8 publications

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“…In this section, both the wind and solar generators were connected to the first power system, as described in Figure 8. The related data about the power output of wind power plants (Windpower), the power output of solar power plants (PV power), and the electricity price for each hour were taken from [30], [31], and [32], respectively. These data are presented again in Figure 9.…”

Section: The Results Achieved In Case Studymentioning

confidence: 99%

Minimize Total Cost and Maximize Total Profit for Power Systems with Pumped Storage Hydro and Renewable Power Plants Using Improved Self-Organizing Migration Algorithm

Tran,

Phan

2024

J. Eng. Technol. Sci.

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This study presents the application of an improved self-organizing migration algorithm (ISOMA) for minimizing the total electricity production expenditure (TEPE) and maximizing the total electricity sale profit (TPRF) for hydrothermal power systems (HTPS) without and with renewable energies. Two power system configurations were employed to test the real efficiency of ISOMA while dealing with two objective functions. In the first configuration, there was one thermal power plant and one hydropower plant, while in the second configuration, wind and solar energy were both connected to the first system. The results achieved in the first configuration with the first objective function indicated that ISOMA not only outperformed SOMA according to all comparison criteria but was also superior to other methods such as evolutionary programming (EP), acceleration factor-based particle swarm optimization (AFPSO), and accelerated particle swarm optimization (APSO). The evaluation of the results achieved by ISOMA in the second configuration with the objective function of maximizing the TPRF revealed that ISOMA could reach better profits than SOMA in terms of maximum, mean and minimum TPRF values over fifty trial runs. As a result, it was concluded that pumped storage hydropower plants are very useful in integrating with renewable power plants to cut total cost for thermal power plants and in reaching the highest profit for the whole system. Also, ISOMA is a suitable algorithm for the considered problem.

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Section: The Results Achieved In Case Studymentioning

confidence: 99%

Minimize Total Cost and Maximize Total Profit for Power Systems with Pumped Storage Hydro and Renewable Power Plants Using Improved Self-Organizing Migration Algorithm

Tran,

Phan

2024

J. Eng. Technol. Sci.

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“…e load demand [38] and energy loss over 24 hour are plotted in Figure 4. e whole data of the system and solar radiation can be reached by using [39,40].…”

Section: Resultsmentioning

confidence: 99%

Coot Optimization Algorithm for Optimal Placement of Photovoltaic Generators in Distribution Systems Considering Variation of Load and Solar Radiation

Kien

Nga

Phan

et al. 2022

Mathematical Problems in Engineering

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In this paper, photovoltaic generators (PVGs) are placed in radial distribution networks (RDNs) for reducing active power loss of one operation day by using three recently published metaheuristic algorithms including coot optimization algorithm (COOA), transient search algorithm (TSA), and crystal structure algorithm (CRSA). In one operation day, the variation of loads is considered, and the change of solar radiation over daytime is also taken. The study has two main contributions regarding the effectiveness of COOA: energy loss reduction and voltage improvement. COOA can reach high energy loss reduction, better solutions, and faster search speed than TSA and CRSA. In fact, COOA finds better energy loss than the algorithms by 1% and 1.77% for the IEEE 69-node system and 0.75% and 1.4% for the IEEE 85-node system. Furthermore, COOA is at least three times faster than CRSA and two times faster than TSA. As compared to a base system without PVGs, COOA can find better energy loss up to 60.96% and improve voltage up to 4.5%. Thus, COOA is a highly effective optimization tool with the optimal solution, high stability, and fast computation process for placing PVGs in RDNs.

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“…From those data, the power of wind and solar photovoltaic power plants can be determined by Refs. [ 50 , 51 ]:

Where,

and

are the lowest and highest wind speeds that wind turbines in the w th WP can produce electricity.

is the rated power of the w th wind power plant.…”

Section: Problem Formulationmentioning

confidence: 99%

Jellyfish search algorithm for optimization operation of hybrid pumped storage-wind-thermal-solar photovoltaic systems

Ha,

Dinh,

Phan

et al. 2024

Heliyon

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Economic dispatch incorporation solar energy using particle swarm optimization

Cited by 19 publications

References 8 publications

Minimize Total Cost and Maximize Total Profit for Power Systems with Pumped Storage Hydro and Renewable Power Plants Using Improved Self-Organizing Migration Algorithm

Minimize Total Cost and Maximize Total Profit for Power Systems with Pumped Storage Hydro and Renewable Power Plants Using Improved Self-Organizing Migration Algorithm

Coot Optimization Algorithm for Optimal Placement of Photovoltaic Generators in Distribution Systems Considering Variation of Load and Solar Radiation

Jellyfish search algorithm for optimization operation of hybrid pumped storage-wind-thermal-solar photovoltaic systems

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