Quality versus speed in energy demand prediction for district heating systems

TL;DR

This paper compares different energy demand prediction algorithms for district heating systems, focusing on their prediction accuracy and computational costs during training and execution, using real-world data.

Contribution

It introduces two novel algorithms and evaluates their performance against neural networks, emphasizing computational costs alongside prediction quality.

Findings

The proposed algorithms perform competitively with neural networks.

Computational costs vary significantly between methods.

Some algorithms are more suitable for real-time applications due to lower costs.

Abstract

In this paper, we consider energy demand prediction in district heating systems. Effective energy demand prediction is essential in combined heat power systems when offering electrical energy in competitive electricity markets. To address this problem, we propose two sets of algorithms: (1) a novel extension to the algorithm proposed by E. Dotzauer and (2) an autoregressive predictor based on hour-of-week adjusted linear regression on moving averages of energy consumption. These two methods are compared against state-of-the-art artificial neural networks. Energy demand predictor algorithms have various computational costs and prediction quality. While prediction quality is a widely used measure of predictor superiority, computational costs are less frequently analyzed and their impact is not so extensively studied. When predictor algorithms are constantly updated using new data, some computationally expensive forecasting methods may become inapplicable. The computational costs can be split into training and execution parts. The execution part is the cost paid when the already trained algorithm is applied to predict something. In this paper, we evaluate the above methods with respect to the quality and computational costs, both in the training and in the execution. The comparison is conducted on a real-world dataset from a district heating system in the northwest part of Poland.