An Improved PSO-GA based Fuzzy Controller of STATCOM for Cascaded Induction Motors of Drilling System

Dehghani, Majid; Bagheri, Mehdi; Nurmanova, Venera; Taghipour, Mohammad; Karimyan, Peyman; Gharehpetian, Gevork B.; Abedi, Mehrdad

doi:10.1109/eeeic/icpseurope49358.2020.9160618

Cited by 9 publications

(2 citation statements)

References 25 publications

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“…The Particle Swarm Optimization algorithm (PSO) is one of the most important optimization algorithms that is placed in the domain of Swarm Intelligence. In the PSO algorithm, members of the population have contact directly, and they address solving the problem through exchanging information and reminding the last memories [39]. The genetic algorithm (GA) is another well-known and useful one.…”

Section: Scenario 1: Isomentioning

confidence: 99%

A Game Theory Approach Using the TLBO Algorithm for Generation Expansion Planning by Applying Carbon Curtailment Policy

Jalalzad¹,

Yektamoghadam

Haghighi

et al. 2022

Energies

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In the present climate, due to the cost of investments, pollutants of fossil fuel, and global warming, it seems rational to accept numerous potential benefits of optimal generation expansion planning. Generation expansion planning by regarding these goals and providing the best plan for the future of the power plants reinforces the idea that plants are capable of generating electricity in environmentally friendly circumstances, particularly by reducing greenhouse gas production. This paper has applied a teaching–learning-based optimization algorithm to provide an optimal strategy for power plants and the proposed algorithm has been compared with other optimization methods. Then the game theory approach is implemented to make a competitive situation among power plants. A combined algorithm has been developed to reach the Nash equilibrium point. Moreover, the government role has been considered in order to reduce carbon emission and achieve the green earth policies. Three scenarios have been regarded to evaluate the efficiency of the proposed method. Finally, sensitivity analysis has been applied, and then the simulation results have been discussed.

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Section: Scenario 1: Isomentioning

confidence: 99%

A Game Theory Approach Using the TLBO Algorithm for Generation Expansion Planning by Applying Carbon Curtailment Policy

Jalalzad¹,

Yektamoghadam

Haghighi

et al. 2022

Energies

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“…It also becomes possible to compensate reactive power and intensively support the network when its voltage value and frequency deviate due to the energy accumulation and further supply to the line since ESS can be integrated into all rig power systems fed from 6 to 0 kV HV lines (Dehghani et al 2020).…”

Section: Ess For Drilling Rigsmentioning

confidence: 99%

Energy storage systems for drilling rigs

Chupin

Фролов

Korzhavin

et al. 2021

J Petrol Explor Prod Technol

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Energy storage systems are an important component of the energy transition, which is currently planned and launched in most of the developed and developing countries. The article outlines development of an electric energy storage system for drilling based on electric-chemical generators. Description and generalization are given for the main objectives for this system when used on drilling rigs isolated within a single pad, whether these are fed from diesel gensets, gas piston power plants, or 6–10 kV HV lines. The article studies power operating modes of drilling rigs, provides general conclusions and detailed results for one of more than fifty pads. Based on the research, a generic architecture of the energy storage module is developed, and an engineering prototype is built. The efficiency of using a hybrid energy accumulation design is proven; the design calls for joint use of Li-ion cells and supercapacitors, as well as three-level inverters, to control the storage system. The article reviews all possible options for connecting the system into a unified rig power circuit, and the optimum solution is substantiated. The research into the rig operating modes and engineering tests yielded a simplified mathematical model of an energy storage unit integrated into the power circuit of a drilling rig. The model is used to forecast the payoff period of the system for various utilization options and rig operating modes. The findings of this study can help to better understand which type of storage system is the most efficient for energy systems with temporary high load peaks, like drilling rigs.

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