Outdoor PV System Monitoring—Input Data Quality, Data Imputation and Filtering Approaches

Abstract

Photovoltaic monitoring data are the primary source for studying photovoltaic plant behavior. In particular, performance loss and remaining-useful-lifetime calculations rely on trustful input data. Furthermore, a regular stream of high quality is the basis for pro-active operation and management activities which ensure a smooth operation of PV plants. The raw data under investigation are electrical measurements and usually meteorological data such as in-plane irradiance and temperature. Usually, performance analyses follow a strict pattern of checking input data quality followed by the application of appropriate filter, choosing a key performance indicator and the application of certain methodologies to receive a final result. In this context, this paper focuses on four main objectives. We present common photovoltaics monitoring data quality issues, provide visual guidelines on how to detect and evaluate these, provide new data imputation approaches, and discuss common filtering approaches. Data imputation techniques for module temperature and irradiance data are discussed and compared to classical approaches. This work is intended to be a soft introduction into PV monitoring data analysis discussing best practices and issues an analyst might face. It was seen that if a sufficient amount of training data is available, multivariate adaptive regression splines yields good results for module temperature imputation while histogram-based gradient boosting regression outperforms classical approaches for in-plane irradiance transposition. Based on tested filtering procedures, it is believed that standards should be developed including relatively low irradiance thresholds together with strict power-irradiance pair filters.

Considerations on Current and Voltage Unbalance of Nonlinear Loads in Residential and Educational Sectors

“…In the last seven decades, there have been many ways of defining and measuring the apparent power and power factor, both in single-and three-phase systems. Even today, these concepts have not been defined in one general and universally accepted way [2,[5][6][7][8][9][10][11][12].…”

“…A good power theory should explain and describe power-related phenomena in electrical systems for all possible situations and should be able to be used for filter design and reactive compensation to improve the power factor [5,8]. Among the numerous approaches to the power theory, the Current Physical Components (CPC) theory, developed by Czarnecki [8,15,23], the Conservative Power Theory (CPT), developed by Tenti [6] and the p-q instantaneous power theory, developed by Akagi [12], are the most distinguished.…”

“…Power quality contents include impulsive transients, interruptions, oscillatory transients, voltage sags, voltage swells, harmonic distortions of the voltage and current, and unbalance and flicker. A number of power quality indices are defined in the time domain (e.g., crest factors, RMS values, voltage sags, power factor) and others power quality in-2 of 29 dices are defined in the frequency domain (e.g., total harmonic distortion, THD, K-factor), depending on the purpose of the application [7][8][9][10][11][12].…”

“…Today, the proliferation of power quality analyzers has forced a new definition of power quality to accommodate the needs of microelectronic equipment. No longer limited to power engineers, power quality now involves control, electronic, and manufacturing engineers [8,[13][14][15].…”

“…In residential and educational buildings, the number of single-phase, low-voltage consumers is higher than the number of three-phase, large-power consumers. The total load of the residential and educational buildings is about tens or hundreds of kW (usually up to 200 kW), distributed among the three-phase, low-voltage network (e.g., 400V/50 Hz) [8,19,28,31].…”