Integrating Demand Response and Renewable Energy In Wholesale Market
Authors: Chaojie Li, Chen Liu, Xinghuo Yu, Ke Deng, Tingwen Huang, Liangchen Liu
IJCAI 2018 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | The effectiveness of the proposed model is illustrated by extensive simulations. |
| Researcher Affiliation | Academia | 1 School of Engineering, RMIT University 2 School of Science, RMIT University 3 Texas A&M University at Qatar 4 School of ITEE, University of Queensland |
| Pseudocode | Yes | Algorithm 1 Seeking Cournot NE By Accelerated Best Response Strategy, Algorithm 2 Seeking SAA SSCN Equilibrium |
| Open Source Code | No | The paper does not provide an explicit statement or link for the open-sourcing of its code. |
| Open Datasets | Yes | To initialize the experiment, the data set regarding RES is collected from Australia Energy Market Operation (AEMO)1 in the summer from Jan. 1, 2017 to April. 30, 2017, where the historical electricity prices and local demands in West Victoria can be obtained. 1http://www.aemo.com.au/ |
| Dataset Splits | No | The paper does not provide specific details on training, validation, and test dataset splits. |
| Hardware Specification | No | The paper does not explicitly describe the hardware used for running its experiments. |
| Software Dependencies | No | The paper does not provide specific software dependencies with version numbers. |
| Experiment Setup | Yes | Take θn = 0.95, η = 0.1 and ϵ = 0.01. |