Projects per year
Abstract
This paper presents a solution to a predict then optimise problem which goal is to reduce the electricity cost of a university campus. The proposed methodology combines a multi-dimensional time series forecast and a novel approach to large-scale optimization. Gradient-boosting method is applied to forecast both generation and consumption time-series of the Monash university campus for the month of November 2020. For the consumption forecasts we employ log transformation to model trend and stabilize variance. Additional seasonality and trend features are added to the model inputs when applicable. The forecasts obtained are used as the base load for the schedule optimisation of university activities and battery usage. The goal of the optimisation is to minimize the electricity cost consisting of the price of electricity and the peak electricity tariff both altered by the load from class activities and battery use as well as the penalty of not scheduling some optional activities. The schedule of the class activities is obtained through evolutionary optimisation using the covariance matrix adaptation evolution strategy and the genetic algorithm. This schedule is then improved through local search by testing possible times for each activity one-by-one. The battery schedule is formulated as a mixed-integer programming problem and solved by the Gurobi solver. This method obtains the second lowest cost when evaluated against 6 other methods presented at an IEEE competition that all used mixed-integer programming and the Gurobi solver to schedule both the activities and the battery use. The code and data used for the paper are publicly available.
Original language | English |
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Pages (from-to) | 1-8 |
Number of pages | 8 |
Journal | 2022 IEEE Congress on Evolutionary Computation (CEC) proceedings |
Volume | 2022 |
DOIs | |
Publication status | Published - 6 Sep 2022 |
Event | 2022 IEEE World Congress on Computational Intelligence : 2022 IEEE Congress on Evolutionary Computation (CEC) - Centro Congressi - Fiera di Padova, Padova, Italy Duration: 18 Jul 2022 → 23 Jul 2022 Conference number: 12 https://wcci2022.org/ |
Bibliographical note
Published at the 2022 IEEE Congress on Evolutionary ComputationFingerprint
Dive into the research topics of 'Evolutionary scheduling of university activities based on consumption forecasts to minimise electricity costs'. Together they form a unique fingerprint.Projects
- 1 Finished
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VLAFLX2: ICON project: MAMuET - Machine learning for real-time Advanced Multi Energy Trading
Coosemans, T., Van Mierlo, J., Messagie, M., Gonzalez Fernandez De Bobadilla, A. & Arapoglou, S.
1/02/19 → 31/01/23
Project: Applied
Activities
- 2 Talk or presentation at a conference
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Evolutionary scheduling of university activities based on consumption forecasts to minimise electricity costs
Julian Jacques Ruddick (Speaker)
19 Jul 2022Activity: Talk or presentation › Talk or presentation at a conference
File -
SSCI 2021: CIS Technical Challenge Session
Julian Jacques Ruddick (Speaker) & Evgenii Genov (Speaker)
5 Dec 2021Activity: Talk or presentation › Talk or presentation at a conference
File
Prizes
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3rd prize for IEEE-CIS Technical Challenge on Predict+Optimize for Renewable Energy Scheduling (2000$)
Ruddick, Julian Jacques (Recipient) & Genov, Evgenii (Recipient), 7 Dec 2021
Prize: Prize (including medals and awards)