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Power system operators are confronted with a multitude of new forecasting tasks to ensure a constant supply security despite the decreasing number of fully controllable energy producers. With this paper, we aim to facilitate the selection of suitable forecasting approaches for the load forecasting problem. First, we provide a classification of load forecasting cases in two dimensions: temporal and hierarchical. Then, we identify typical features and models for forecasting and compare their applicability in a structured manner depending on six previously defined cases. These models are compared against real data in terms of their computational effort and accuracy during development and testing. From this comparative analysis, we derive a generic guide for the selection of the best prediction models and features per case.

Many eukaryotic genes play essential roles in multiple biological processes in several different tissues. Conditional mutants are needed to analyze genes with such pleiotropic functions. In vertebrates, conditional gene inactivation has only been feasible in the mouse, leaving other model systems to rely on surrogate experimental approaches such as overexpression of dominant negative proteins and antisense-based tools. Here, we have developed a simple and straightforward method to integrate loxP sequences at specific sites in the zebrafish genome using the CRISPR/Cas9 technology and oligonucleotide templates for homology directed repair. We engineered conditional (floxed) mutants of tbx20 and fleer, and demonstrate excision of exons flanked by loxP sites using tamoxifen-inducible CreERT2 recombinase. To demonstrate broad applicability of our method, we also integrated loxP sites into two additional genes, aldh1a2 and tcf21. The ease of this approach will further expand the use of zebrafish to study various aspects of vertebrate biology, especially post-embryonic processes such as regeneration.