Efficient Buyer Groups for Prediction-of-Use Electricity Tariffs

Authors: Valentin Robu, Meritxell Vinyals, Alex Rogers, Nicholas Jennings

AAAI 2014 | Conference PDF | Archive PDF | Plain Text | LLM Run Details

Reproducibility Variable Result LLM Response
Research Type Experimental We propose a polynomial time algorithm to compute efficient buyer groups, and validate our approach experimentally, using a large-scale data set of domestic electricity consumers in the UK.
Researcher Affiliation Academia Valentin Robu Heriot-Watt University Edinburgh, Scotland, UK v.robu@hw.ac.uk Meritxell Vinyals, Alex Rogers and Nicholas R. Jennings University of Southampton Southampton, UK {mv2y11,acr,nrj}@ecs.soton.ac.uk
Pseudocode Yes The pseudocode of the method is given in Algorithm 1.
Open Source Code No The paper does not provide an explicit statement or link for open-source code for the described methodology.
Open Datasets No The paper mentions using 'a large dataset of around 3000 households (i.e. customers) in the UK' but does not provide concrete access information such as a link, DOI, or formal citation for public access.
Dataset Splits No The paper does not provide specific details regarding training, validation, or test dataset splits, such as percentages or sample counts.
Hardware Specification No The paper does not provide specific hardware details (e.g., CPU/GPU models, memory) used for running the experiments.
Software Dependencies No The paper does not provide specific ancillary software details with version numbers (e.g., library or solver names with versions) needed to replicate the experiment.
Experiment Setup Yes The evaluation considers three tariffs (F, P and P+) detailed as follows. Tariff F (Flat), corresponds to a flat tariff in which customers pay a fixed price ( 0.205) per k W consumed. Tariff P (Predictive) reduces the baseline price of tariff F at the cost of charging a penalty of 0.01/ 0.03 for each k W underconsumed/overconsumed respectively. Finally, tariff P+ (Highly Predictive) offers the lowest baseline price but severely penalizes any imbalance (with penalties of 0.17/ 0.26 per Kw underconsumed/overconsumed).