Development of an energy monitoring and targeting methodology for the most efficient operation of chilled water systems : a thesis presented in partial fulfilment of the requirements for the degree of Master of Engineering in Energy Management at Massey University, Palmerston North, New Zealand
The increasing price of oil and the destabilisation of the world’s climate are urging
governments, businesses and individuals to constantly investigate energy-efficient
technologies and methodologies and pursue the adoption of energy efficiency
programmes in a global effort to reduce energy consumption, greenhouse gas emissions
and ultimately energy costs.
In New Zealand, one of the biggest industrial energy efficiency projects was started in
2002 by a multinational dairy company, the Fonterra Co-operative Group, in partnership
with the energy service company Demand Response Ltd; the project currently aims at
reducing by 15% the energy costs at all Fonterra’s major production sites throughout the
country. This thesis, undertaken as part of the above project, examines the development
and implementation of a structured and integrated energy monitoring and targeting
methodology (M&T) for the most efficient operation of all Fonterra’s chilled water
systems, with an initial focus on the ones installed at Clandeboye, one of the Fonterra’s
sites involved in the energy saving project.
A data collection system (Insite) was already in place at Clandeboye to enable storage
and analysis of some of the site’s utility metering data. After identification of key
chilled water system components and definition of data requirements for M&T
purposes, an analysis of past energy consumption trends (based on multiple regression
calculations) was carried out to develop an historical benchmark of the energy used,
compare it with current energy performance and thus identify opportunities for future
improvements. The creation of an M&T reporting system for presenting findings to
operators and management was the last essential part of the thesis development.
The study has highlighted that the robustness of the proposed regression model was
badly affected by the unreliability of the existing data collection system and the
uncertainty associated with poorly documented changes to operating conditions/plant
configuration that had occurred over time. The conclusion is that, while the developed
M&T methodology is theoretically valid and readily applicable, further developments
are necessary (and recommended) to make it suitable for other similar systems.