Short-term hydrothermal coordination using water cycle algorithm with evaporation rate

Haroon, Shaikh Saaqib; Malik, Tahir Nadeem

doi:10.1002/etep.2349

Cited by 7 publications

(2 citation statements)

References 34 publications

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“…In the constant model of the water head, the generation of HEPs was determined by using discharge through water turbines [6], and the volume of dams could be either neglected [7] or considered [8]. In the variable model of water head, HEPs were separate [9] or a cascaded system with upper and lower dams [10]. The different assumptions of HEPs were integrated into one sole model of ThPPs, which was represented by a fuel costgeneration power function.…”

Section: B Literature Reviewmentioning

confidence: 99%

The Combination of Energy Storage and Renewable Energies to Reach a Maximum Profit for Power Systems

Kien,

Tuyet,

Phan

et al. 2023

IEEE Access

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This paper investigates the effectiveness of the water storage and electricity generation of a pumped-storage hydroelectric plant (PSP) for maximizing total electricity sale revenue of one day as it is integrated into a hybrid power system with the presence of wind power plants (WP) and solar photovoltaic power plants (SP). Four study cases with different rated powers of PSP, including 50, 75, 100 and 125 MW, are implemented to find the most suitable capacity, the optimal hours for water storage and the optimal generation for other hours of the considered PSP. Similarly, the four cases are also investigated for another hybrid power system with the same WP and SP, but PSP is replaced with another conventional hydroelectric plant (CHEP), which does not have a storage function. Five optimization algorithms, including Slime mould algorithm (SMA), Equilibrium optimizer (EO), Jellyfish Algorithm (JS), Coot optimization algorithm (COOT) and War Strategy optimization Algorithm (WSO), are implemented for two hybrid power systems. As a result, EO is the highest performance method with superiority over others in almost all cases. The second hybrid system with PSP can reach a greater revenue than the first hybrid system with CHEP by $31,638, which is about 11% of the total revenue of the first system. In addition, the second system only uses a PSP with a rated power of 75 MW, but the first system must use a higher rated power of 100 MW for CHEP. Clearly, PSP is very effective for hybrid power systems with the integration of renewable power plants in reaching maximum total revenue. However, the comparisons among study cases also indicate that the rated power of PSP should be carefully calculated, otherwise, PSP is no longer applicable.

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Section: B Literature Reviewmentioning

confidence: 99%

The Combination of Energy Storage and Renewable Energies to Reach a Maximum Profit for Power Systems

Kien,

Tuyet,

Phan

et al. 2023

IEEE Access

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show abstract

“…The clustered adaptive teaching-learning-based optimization (CATLBO) algorithm was utilized by Salkuti [18] to solve STHTS. Haroon et al [19] applied the evaporation rate-based water cycle algorithm (ERWCA) to hydrothermal coordination problems and compared the results with other techniques. Ghosh et al [20] applied the hybrid bat algorithm (BA) with an artificial bee colony (ABC) to solve the STHTS problem.…”

Section: Introductionmentioning

confidence: 99%

Introducing Adaptive Machine Learning Technique for Solving Short-Term Hydrothermal Scheduling with Prohibited Discharge Zones

et al. 2022

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The short-term hydrothermal scheduling (STHTS) problem has paramount importance in an interconnected power system. Owing to an operational research problem, it has been a basic concern of power companies to minimize fuel costs. To solve STHTS, a cascaded topology of four hydel generators with one equivalent thermal generator is considered. The problem is complex and non-linear and has equality and inequality constraints, including water discharge rate constraint, power generation constraint of hydel and thermal power generators, power balance constraint, reservoir storage constraint, initial and end volume constraint of water reservoirs, and hydraulic continuity constraint. The time delays in the transport of water from one reservoir to the other are also considered. A supervised machine learning (ML) model is developed that takes the solution of the STHTS problem without PDZ, by any metaheuristic technique, as input and outputs an optimized solution to STHTS with PDZ and valve point loading (VPL) effect. The results are quite promising and better compared to the literature. The versatility and effectiveness of the proposed approach are tested by applying it to the previous works and comparing the cost of power generation given by this model with those in the literature. A comparison of results and the monetary savings that could be achieved by using this approach instead of using only metaheuristic algorithms for PDZ and VPL are also given. The slipups in the VPL case in the literature are also addressed.

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A comprehensive review on water cycle algorithm and its applications

Nasir

Sadollah

Choi

et al. 2020

Neural Comput & Applic

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Short-term hydrothermal coordination using water cycle algorithm with evaporation rate

Cited by 7 publications

References 34 publications

The Combination of Energy Storage and Renewable Energies to Reach a Maximum Profit for Power Systems

The Combination of Energy Storage and Renewable Energies to Reach a Maximum Profit for Power Systems

Introducing Adaptive Machine Learning Technique for Solving Short-Term Hydrothermal Scheduling with Prohibited Discharge Zones

A comprehensive review on water cycle algorithm and its applications

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