Contract Design for Energy Demand Response
Authors: Reshef Meir, Hongyao Ma, Valentin Robu
IJCAI 2017 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Extensive simulations show that compared to the current mechanism deployed by SCE, the DR-VCG mechanism achieves higher participation, increased reliability, and significantly reduced total expenses. |
| Researcher Affiliation | Academia | Reshef Meir Technion Israel Institute of Technology Haifa, Israel reshefm@ie.technion.ac.il Hongyao Ma Harvard University Cambridge, MA, US hma@seas.harvard.edu Valentin Robu Heriot-Watt University Edinburgh, UK V.Robu@hw.ac.uk |
| Pseudocode | No | The paper describes the DR-VCG mechanism in text and through mathematical formulations but does not include any pseudocode or algorithm blocks. |
| Open Source Code | No | The paper does not provide any statement or link indicating that source code for the methodology is openly available. It only mentions that 'All omitted proofs are available in the full version of this paper [Meir et al., 2017]'. |
| Open Datasets | No | The paper states, 'To set up a realistic scenario of a typical demand response event, we used [Patterson et al., 2014] that summarize previous DR programs.' and describes how agent data was sampled from distributions, but it does not provide concrete access information (e.g., a URL, DOI, or repository) for a publicly available dataset used in experiments. |
| Dataset Splits | No | The paper describes the simulation settings, including how agent data is generated and parameters like effort levels and capacities, but it does not specify explicit training, validation, or test dataset splits. |
| Hardware Specification | No | The paper does not provide any specific details about the hardware (e.g., CPU, GPU models, memory) used to run the simulations. |
| Software Dependencies | No | The paper does not list any specific software dependencies or their version numbers that were used for the implementation or experiments. |
| Experiment Setup | Yes | In each economy we sample n agents i.i.d., where each agent has T {1, 3, 5} effort levels. For each agent i N and effort level t T: the capacity (in k Wh) is qit Zipf(1, 500) 10; individual reliability is pi U[0.7, 1]; and agents investment costs (in $) are cit U[0.2, 1], multiplied by qi.3 Note that only agents with maxt cit qit 0.5 will submit bids in DR-SCE. We generated populations of 3 sizes: n = 100 (small), n = 200 (medium) and n = 400 (large), and for each population varied the safety margin between γ [1, 2]. |