Group Regulation Efficiency Analysis for Thermal Power Plant Auxiliaries

Kruhol, Mykola; Lasurenko, Oleksandr; Ванин, В. А.; Tomashevskyi, Roman

doi:10.1109/ess.2019.8764242

Cited by 4 publications

(2 citation statements)

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“…The specific consumption measure-the ratio between power and kilograms of fuel-is an indicator of thermal efficiency, but there is also another important measure that will be addressed in this work: the energy consumption of auxiliary equipment [2]. This equipment plays the function of ensuring that the parameters of the main devices (e.g., boilers, engines, generators, and turbines) responsible for the production of energy are controlled and, therefore, consume electricity from the production itself to maintain its operation [3].…”

Section: Introductionmentioning

confidence: 99%

“…The activation of such equipment occurs through directly starting electric motors, which, without smooth current and voltage control, increase energy consumption. The electrical configuration of the power plant is made to operate at its highest generating capacity; however, at times, the generation is reduced, causing the auxiliary equipment to work in inefficient areas, as informed by the manufacturers [3].…”

Section: Introductionmentioning

confidence: 99%

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Digital Twins of the Water Cooling System in a Power Plant Based on Fuzzy Logic

Araújo

Villanueva

Almeida

et al. 2021

Sensors

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In the search for increased productivity and efficiency in the industrial sector, a new industrial revolution, called Industry 4.0, was promoted. In the electric sector, power plants seek to adapt these new concepts to optimize electric power generation processes, as well as to reduce operating costs and unscheduled downtime intervals. In these plants, PID control strategies are commonly used in water cooling systems, which use fans to perform the thermal exchange between water and the ambient air. However, as the nonlinearities of these systems affect the performance of the drivers, sometimes a greater number of fans than necessary are activated to ensure water temperature control which, consequently, increases energy expenditure. In this work, our objective is to develop digital twins for a water cooling system with auxiliary equipment, in terms of the decision making of the operator, to determine the correct number of fans. This model was developed based on the algorithm of automatic extraction of fuzzy rules, derived from the SCADA of a power plant located in the capital of Paraíba, Brazil. The digital twins can update the fuzzy rules in the case of new events, such as steady-state operation, starting and stopping ramps, and instability. The results from experimental tests using data from 11 h of plant operations demonstrate the robustness of the proposed digital twin model. Furthermore, in all scenarios, the average percentage error was less than 5% and the average absolute temperature error was below 3 °C.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%