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This paper proposes an approach to optimize sizing and placement of photovoltaic solar panels (PV) and batteries in systems which employ diesel generators (DGs) as their only source of electrical energy, forming a PV hybrid system. Three objectives have been defined: reduction of the levelized cost of electricity (economic objective); levelized CO2 equivalent life cycle emissions (environmental objective);...
We forecast hourly solar irradiance time series using a novel hybrid model based on SOM (self-organizing maps), SVR (support vector regression) and PSO (particle swarm optimization). In order to solve the noise and stationarity problems in the statistical time series forecasting modelling process, SOM is applied to partition the whole input space into several disjointed regions with different characteristic...
Time series methods are frequently used in solar irradiance forecasting when two dimensional cloud information provided by satellite or sky camera is unavailable. ETS (exponential smoothing) has received extensive attention in the recent years since the invention of its state space formulation. In this work, we combine these models with knowledge based heuristic time series decomposition methods to...
We forecast high-resolution solar irradiance time series using an exponential smoothing state space (ESSS) model. To stationarize the irradiance data before applying linear time series models, we propose a novel Fourier trend model and compare the performance with other popular trend models using residual analysis and the Kwiatkowski-Phillips-Schmidt-Shin (KPSS) stationarity test. Using the optimized...
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