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An improved mayfly algorithm is proposed for the energy saving optimization of parallel chilled water pumps in central air conditioning system, with the minimum energy consumption of parallel pump units as the optimization objective and the speed ratio of each pump as the optimization variable for the solution. For the problem of uneven random initialization of mayflies, the variable definition method of Circle chaotic mapping is used to make the initial position of the population uniformly distributed in the solution space, and the mayfly fitness value and the optimal fitness value are incorporated into the calculation of the weight coefficient, which better balances the global exploration and local exploitation of the algorithm. For the problem that the algorithm is easy to fall into the local optimum at the later stage, a multi-subpopulation cooperative strategy is proposed to improve the global search ability of the algorithm. Finally, the performance of the improved mayfly algorithm is tested with two parallel pumping system cases, and the stability and time complexity of the algorithm are verified. The experiments show that the algorithm can get a better operation strategy in solving the parallel water pump energy saving optimization problem, and can achieve energy saving effect of 0.72% 8.68% compared with other optimization algorithms, and the convergence speed and stability of the algorithm have been significantly improved, which can be better applied to practical needs. [ABSTRACT FROM AUTHOR]

Reasonable distribution of cooling load between chiller and ice tank is the key to realize the economical and energy-saving operation of ice-storage air-conditioning (ISAC) system. A multi-objective optimization model based on improved firefly algorithm (IFA) was established in this study to fully exploit the energy-saving potential and economic benefit of the ISAC system. The proposed model took the partial load rate of each chiller and the cooling ratio of the ice tank as optimization variables, and the lowest energy consumption loss rate and the lowest operating cost of the ISAC system were calculated. Chaotic logic self-mapping was used to initialize population to avoid falling into local optimum, and Cauchy mutation was used to increase the population's diversity to improve the algorithm's global search ability. The experimental results show that compared with the operation strategy based on constant proportion, particle swarm optimization (PSO) algorithm, and firefly algorithm (FA), the optimal operation strategy based on IFA can achieve more significant energy-saving and economic benefits. Meanwhile, the convergence accuracy and stability of the algorithm are significantly improved. Practical application: The optimized operation strategy of the ice-storage air-conditioning system can reduce energy loss and operating costs. The traditional operation strategies have the problems of low optimization precision and poor optimization effect. Therefore, this study presents an optimal operation strategy based on IFA. The convergence accuracy and stability of the algorithm are increased after the algorithm is improved. The operation strategy can get the maximum energy-saving effect and economic benefit of the ISAC system. [ABSTRACT FROM AUTHOR]

In this paper, fault diagnosis (FD) algorithm for LED lamp driven by segmented linear solution via illumination waveform fluctuation similarity calculation is proposed for indoor environment application. The proposed FD algorithm can be divided into four steps: illumination signal pre-processing, illumination waveform fluctuation similarity calculation, similarity assessment, and fault recognition. In illumination signal pre-processing, smoothing the original illumination signal using average filter algorithm, and illumination data normalization with min-max normalization method. Calculating illumination waveform fluctuation similarity with euclidean distance between the illumination signal of detected-lamp and standard illumination templates. Diagnosing the detected-lamp whether occurs fault or not and confirming the fault-type with illumination waveform fluctuation similarity value. To validate the proposed FD algorithm, an experimental setup is established in indoor environment and illumination signal of LED lamps are captured using Light Flicker Analyzer. The experimental results demonstrate the proposed FD algorithm can effectively diagnose faulty LED lamps driven by segment linear solution in indoor environment. The proposed algorithm developed here can benefit the fault diagnosis technology of LED lamp driven by segmented linear solution. [ABSTRACT FROM AUTHOR]

Fault detection and diagnosis (FDD) algorithms based on first-order difference calculation and peak-detection methods for HV-LED lamp driven by segmented linear solution is proposed. The proposed FDD algorithms analyze the illuminance fluctuation characteristics of HV-LED lamp, and then identify whether the HV-LED lamp occurs fault or not and confirm the fault-type. The proposed FDD algorithms can be divided into five steps: illuminance signal smoothing, illuminance signal process using first-order difference calculation, difference-value sequence smoothing, peak detection of difference-value sequence, and fault-type recognition. Taking the HV-LED lamp driven by four-segment linear driver for example, the illuminance data sets of the fault-free and three different faults are investigated for algorithm verification experiments. The experimental results demonstrate the proposed FDD algorithms can effectively detect and diagnose the fault-type of HV-LED lamp driven by segmented linear driver, and locate the faulty HV-LED sub-strings. [ABSTRACT FROM AUTHOR]