A Scalable Interdependent Multi-Issue Negotiation Protocol for Energy Exchange
Authors: Muddasser Alam, Enrico H. Gerding, Alex Rogers, Sarvapali D. Ramchurn
IJCAI 2015 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Here, we set up a realistic example to demonstrate (i) the benefit of energy exchange via the EEP and (ii) its comparison to the EEP-A by Alam et al. [2013b] which is the state-of-the-art. We use data for July 2011, estimate the average generation for a day and scale it to match the output of a 1.5k W wind turbine and a 1.75k W solar panel. At present, the load requirements of homes in remote areas are not available, so we use load data recorded and provided by a UK electric company in low-income homes equipped with smart meters. Figure 3 shows this consumption along with the generation (solar and wind). |
| Researcher Affiliation | Academia | Muddasser Alam, Enrico H. Gerding, Alex Rogers and Sarvapali D. Ramchurn Electronics and Computer Science, University of Southampton, U.K. {moody,eg,acr,sdr}@ecs.soton.ac.uk |
| Pseudocode | Yes | Figure 1: The Energy Exchange Protocol (EEP) 1. Negotiation starts at a specified time with round zero where all agents simultaneously broadcast their exchange type. Only et1 is allowed to make offers from now on, while et2 can only respond to offers. 2. Subsequent offer rounds take place at specified intervals. If there are at least one maker and one receiver, offer rounds continue as follows: All makers make simultaneous offers. Each maker is required to make a valid flow offer f = 0 to all receiver it is connected to. An offer f is valid if: The offer comprises of exactly two exchange periods. Each exchange period consists of an equal number of consecutive time periods. The amount of energy exchanged in each exchange period must be the same. f = (f1, .....ft) | i=t/2+1 fi (r1) The amount of energy in each time period is equal. f = (f1, .....ft) | fi f : |fi| = |fi+1| (r2) On receiving offers, each receiver simultaneously broadcasts a valid flow f B = 0 to all agents which must not exceed the minimum offer it received. (r3) The agreed flow l A in this offer round is the minimum flow in the set of all broadcast flows F B, i.e., l A = min (F B). (r4) All receivers simultaneously broadcast a boolean signal to their respective makers to indicate if they wish to receive offers in the next offer round. The current offer round terminates. 3. The EEP terminates. |
| Open Source Code | No | The paper does not include an unambiguous statement that the authors are releasing the code for the work described in this paper, nor does it provide a direct link to a source-code repository. |
| Open Datasets | No | The paper mentions using "data for July 2011" from "www.sotaventogalicia.com" (wind) and "www.re.jrc.ec.europa.eu/apps/radday.php" (solar), and "load data recorded and provided by a UK electric company in low-income homes equipped with smart meters". However, it does not provide concrete access information (specific link, DOI, or formal citation with authors/year) for a publicly available or open dataset for all data utilized, especially the load data. |
| Dataset Splits | No | The paper describes simulation setups where communities are created repeatedly, but it does not specify explicit training, validation, or test dataset splits in the context of typical machine learning or data analysis experiments. |
| Hardware Specification | Yes | In our case, the EEP-A takes over 8 hours and the EEP takes less than 10 minutes for 100 agents on a 72TFlops (4 nodes each containing an 8-core with each core 2.27 Ghz) supercomputer. |
| Software Dependencies | No | The paper does not provide specific ancillary software details, such as library or solver names with version numbers, needed to replicate the experiment. |
| Experiment Setup | Yes | Here, we set up a realistic example to demonstrate (i) the benefit of energy exchange via the EEP and (ii) its comparison to the EEP-A by Alam et al. [2013b] which is the state-of-the-art. To this end, we consider an example of energy exchange in a community where each agent has either a 1.5k W wind turbine or a 1.75k W solar panel with equal probability. ... We assume that agents have identical batteries [s = 20k Wh, c = 4k W, d = 4k W, e = 90%]. Given this setup, we repeatedly (50 times) create a fully connected P2P community of 20 agents and simulate energy exchange via the EEP and EEP-A. ... To demonstrate scalability, we use the same experimental setup (no repetition) to simulate exchange in the communities of up to 100 agents... |