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The use of Cyber Physical Systems (CPS) to optimise industrial energy systems is an approach which has the potential to positively impact on manufacturing sector energy efficiency. The need to obtain data to facilitate the implementation of a CPS in an industrial energy system is however a complex task which is often implemented in a non-standardised way. The use of the 5C CPS architecture has the potential to standardise this approach. This paper describes a case study where data from a Combined Heat and Power (CHP) system located in a large manufacturing company was fused with grid electricity and gas models as well as a maintenance cost model using the 5C architecture with a view to making effective decisions on its cost efficient operation. A control change implemented based on the cognitive analysis enabled via the 5C architecture implementation has resulted in energy cost savings of over €7400 over a four-month period, with energy cost savings of over €150,000 projected once the 5C architecture is extended into the production environment. [ABSTRACT FROM AUTHOR]

Increasing the level and diversifying the sources of flexible capacity available to transmission system operators will be a pivotal factor for maintaining reliable control of national electricity grids. These response capacities are widely available; however, one area with large capacities that could benefit from advancements is the industrial sector. This sector's highly regulated nature ensures that structured procedures and thorough investigations are required to implement significant change. This study presents a systematic methodology to effectively categorise assets and evaluate their perceived risk of participation in demand response, allowing industries to present a sustainable portfolio of flexible capacity to the grid. Following implementation on an internationally relevant industrial site, this methodology identified several assets for participation, determining that it is realistic to expect 35 to 75 kW of flexible capacity from only air handling units on a single site. A selected unit was further evaluated using an internal air-temperature modelling tool. This demonstrated its ability to respond safely to the actual 2019 and 2020 grid frequency events and even remain off, at no risk to the indoor thermal environment for at least 20 min in each case. The potential impact of advancing industrial participation is presented, with the highest scenario providing almost 15 MW of flexible capacity to the Irish national grid. The financial benefit achievable on a site from the most conservative assets was found to be between EUR 993 and EUR 2129 annually for a single response category and up to EUR 6563 based on payment multipliers. Overall, this research demonstrates the significant flexible capacities available within the industrial sector and illustrates the low-risk capabilities and considerable benefits achievable on a single site and for the wider national electricity grids with this concept. [ABSTRACT FROM AUTHOR]

Increasing participation in demand response within the industrial sector may be crucial to growing the levels of available flexible capacity required to reliably control national electricity grids as renewable generation increases to satisfy emission targets. This research aims to assist the uptake of demand response in the industrial sector by investigating risk to indoor thermal environments on industrial sites offering air handling unit capacity for demand response. This evaluation uses a systematic model-based approach, calibrated and validated with empirical data from a relevant case study industrial building to assess risk through a number of scenarios. The conditions investigated cover several relevant grid response times and durations, and national and international extreme external ambient temperatures in the past, present and future under a variety of temperature limits. The study demonstrated that there is very low risk to the case study site participating in demand response, with only 15 of 264 initial and 284 of 936 total scenarios triggering any risk. The major factors affecting risk levels identified were more stringent temperature limits and the influence of more extreme climates. The development and implementation of this concept has considerable potential to benefit industrial participants and the wider national electricity grids. [ABSTRACT FROM AUTHOR]