Effects of variable solar irradiance on the reactive power compensation for large solar farm

Howard, Dustin F.; Harley, R.G.; Liang, Jiaqi; Venayagamoorthy, G.K.

doi:10.1109/irep.2010.5563254

Cited by 113 publications

(10 citation statements)

References 6 publications

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“…Thus, assuming the minimum working gas pressure for p, the mass flow rate limit is a function of the pipe dimensions. The pressure of the high pressure gas storage tank and the pipe dimensions connecting the gas storage tank to the engine play a major part in the control system performance [1] and [2].…”

Section: Pressure Control System (Psc)mentioning

confidence: 99%

“…In the same way, the PCS measures the pressure in the Stirling engine, and makes an adjustment to the valve positions, to match the mean pressure with the measured pressure [1] and [2]. The pressure commanded by the temperature control system (TCS) follows a pattern as illustrated in Table 1.…”

Section: Temperature Control Systemmentioning

confidence: 99%

“…The reason is that the higher the solar irradiance, the higher the temperature produced, and the higher the efficiency of Stirling engine as well. [1][2][3] When the irradiance is too low and measured heater temperature occurs at below the set point TSET of the temperature, the mean pressure stays at its idle point. In this condition, the heater temperature varies with irradiance.…”

Section: Thermal Losses and Srirling Engine Gross Power Outputmentioning

confidence: 99%

“…The temperature is controlled by varying the working gas pressure, achieved by adding or removing working gas to/from the engine. Changing the pressure of the Stirling engine working gas changes the quantity of mass flow through the heater, thereby changing the amount of heat removed from the heater as shown in Figure 1 [1]. …”

Section: Introductionmentioning

confidence: 99%

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Sensitivity Analysis and Comparison between 25 kW Parabolic Dish System

et al. 2016

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Section: Pressure Control System (Psc)mentioning

confidence: 99%

Section: Temperature Control Systemmentioning

confidence: 99%

Section: Thermal Losses and Srirling Engine Gross Power Outputmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Sensitivity Analysis and Comparison between 25 kW Parabolic Dish System

et al. 2016

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“…However, the scale of the conventional grid-connected DS system using squirrel-cage induction generators (SCIGs) is restricted due to the lack of control capability to meet the grid code requirements such as to provide frequency and voltage support. Although frequency support, such as a fixed-speed generation system, could be achieved by changing the working temperature [15], the significant reactive power injected to the grid system can still cause a severe voltage stability problem especially in a weak grid, as has been investigated in works [16,17].…”

Section: Introductionmentioning

confidence: 99%

Particle Swarm Optimization-Based Power and Temperature Control Scheme for Grid-Connected DFIG-Based Dish-Stirling Solar-Thermal System

Li¹,

Xiong²,

Su³

et al. 2019

Energies

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Variable-speed operation of a dish-Stirling (DS) concentrated solar-thermal power generating system can achieve higher energy conversion efficiency compared to the conventional fixed-speed operation system. However, tuning of the controllers for the existing control schemes is cumbersome due to the presence of a large number of control parameters. This paper proposes a new control system design approach for the doubly-fed induction generator (DFIG)-based DS system to achieve maximum power point tracking and constant receiver temperature regulation. Based on a developed thermo-electro-pneumatic model, a coordinated torque and mean pressure control scheme is proposed. Through steady-state analysis, the optimal torque is calculated using the measured insolation and it serves as the tracking reference for direct torque control of the DFIG. To minimize the tracking error due to temperature variation and the compressor loss of the hydrogen supply system, four optimal control parameters are determined using particle swarm optimization (PSO). Model-order reduction and the process of the pre-examination of system stability are incorporated into the PSO algorithm, and it effectively reduces the search effort for the best solution to achieve maximum power point tracking and maintain the temperature around the set-point. The results from computational simulations are presented to show the efficacy of the proposed scheme in supplying the grid system with smoothened maximum power generation as the solar irradiance varies.

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