Methodology of advanced data validation and reconciliation application in industrial thermal processes

A Novel Data Management Methodology and Case Study for Monitoring and Performance Analysis of Large-Scale Ground Source Heat Pump (GSHP) and Borehole Thermal Energy Storage (BTES) System

“…However, none of them questioned the accuracy and checked for the consistency of the acquired measured data. Data validation and reconciliation (DVR) in industrial thermal processes is a technique addressed in several research studies [17,18]. The role of DVR is to extract reliable and accurate information from raw measured data and to produce a consistent dataset resulting in the most probable process operation.…”

“…The role of DVR is to extract reliable and accurate information from raw measured data and to produce a consistent dataset resulting in the most probable process operation. DVR belongs to a more general category of data management [17]. The DVR procedure normally intends to correct measurement errors and can be expressed mathematically as an optimization problem for optimally correcting the measurement data in a way that the adjusted values are consistent with the laws of conservation.…”

“…The DVR procedure normally intends to correct measurement errors and can be expressed mathematically as an optimization problem for optimally correcting the measurement data in a way that the adjusted values are consistent with the laws of conservation. The objective function is based on the least squares method with various sets of constraints, e.g., in thermal processes-constraints normally based on flow, mass, or energy balance [17].…”

“…The novelty of this paper is to introduce a specifically developed DVR methodology for data management adjusting the measured data for consistency in order to achieve the necessary energy balances on both sides of the GSHP. Application of the generalized DVR method, which handles raw measured data with unmeasured quantities (GSHP condenser and evaporator loads), tends to decrease the uncertainty after data reconciliation [17,18] and is a certainly indispensable solution to cope with the inherent high uncertainty of ANCC thermal energy meters. The present work also develops a method for reconstruction of some essential missing measurements before April/May 2020 by applying linear regression techniques based on different correlated measured data (Section 2.5).…”

Application of Data Validation and Reconciliation to Improve Measurement Results in the Determination Process of Emission Characteristics in Co-Combustion of Sewage Sludge with Coal

“…During the same period, numerous interesting research studies were published in world literature concerning both general principles involving the application of data validation and reconciliation [11,12,14,[26][27][28][29][30] as well as its application for solving more specific problems. For example, they were presented in the publications covering the problems of nuclear power plants [31][32][33], chemical industry [34][35][36][37][38][39][40], power plants and combined heat and power plants [41][42][43][44][45][46], refrigeration [47], and biotechnology [48].…”