## 5 Discussion
### Secondary Parameters  
Meteorological data, such as temperature data (e.g., ambient temperature, chilled water temperature) and weather data, impact several factors, such as cooling load, energy consumption, and costs [112; 118]. While collecting the data, a few factors need to be considered, such as the average temperature values of Melbourne and Barcelona, which could appear similar. However, this does not mean their temperature fluctuations are of the same magnitude and frequency [120]. Therefore, collecting time series data with variations and standard deviations is crucial for analyzing fluctuations that affect TCO in CWPs. Variations in occupancy impact the dynamic load on the system, as occupants can cause temperature fluctuations within rooms or building facilities [6,123,127]. However, capturing these occupancy variations in buildings can be challenging [6]. This difficulty arises because gathering data on parameters such as occupancy and certain weather conditions often requires integrating or deploying external sensors [127]. However, obtaining and installing such sensors may not always be possible due to budget limitations for chiller plant establishments [123]. Therefore, we categorized it as a secondary parameter. PLR reflects system efficiency under varying loads and affects energy costs and operational efficiency. Chillers operating at lower PLRs consume more energy per cooling unit, leading to higher energy costs and TCO [118]. To obtain PLR data, one needs to know the system's actual load and maximum capacity [30]. Several factors, such as seasonal variations, occupancy patterns, and energy costs, also contribute to time-varying PLR [30,118]. Power consumption, chiller type and configuration, and building attributes are secondary parameters that can impact the TCO of CWPs by influencing other primary and secondary factors [48,111,118]. For instance, power consumption is influenced by load demand, chiller efficiency, system design, control strategies, and ambient conditions, with higher consumption leading to increased energy costs, maintenance expenses, and reduced equipment lifespan [20,111]. Additionally, while chiller type and configuration can affect the TCO of CWPs, they are not as frequently examined in the current research as other parameters [6]. This observation may not be due to their lack of impact on the TCO outcome but rather the complexity involved in subsequently analyzing and validating their influence on the plant's TCO. For example, the extensive range of chiller types (e.g., centrifugal [3], electric [5,49,114], adsorption [113], and air-cooled [111,127]) and configurations (e.g., symmetrical, asymmetrical, single chiller, and multi-chiller) available on the market, coupled with their complex interactions with other system components, can pose challenges in precisely evaluating their effect on TCO. Furthermore, acquiring relevant data for various chiller types and configurations across different operating conditions may be difficult, adding to the complexity of the analysis [6]. It is important to note that installing high-efficiency equipment in a poorly designed plant can lead to increased operating costs [118]. Similarly, building attributes, including architectural design, energy efficiency, and CWP location, can affect the loading and efficiency of CWPs, with factors such as rooftop sun exposure and ventilation impacting heat dissipation [5]. However, our survey of the literature observed that no study comprehensively explored these building attributes that may influence the TCO of chillers. These secondary parameters indirectly influence TCO by affecting other primary and secondary parameters, such as cooling load and energy usage [112]. While these secondary factors alone are insufficient for directly estimating or forecasting TCO, incorporating them can enhance the accuracy of TCO predictions by providing a more comprehensive understanding of the system and data.