Analysis and sizing of thermal energy storage in combined heating, cooling and power plants for buildings

Optimisation of the capacity and the dispatch of decentralised micro-CHP systems: A case study for the UK

“…Ref. [13] focuses on the optimal sizing of a thermal storage for a predetermined CHP system in the residential and tertiary context based on a simulation approach. The study considers a concave function of the investment for the thermal storage.…”

A data-driven feed-forward decision framework for building clusters operation under uncertainty

“…Other than utilizing building thermal mass, the operation strategies for TES which are derived by mathematical programming, model predictive control (MPC) and reinforcement learning approaches are demonstrated to outperform the conventional control strategy such as chiller-priority and storage-priority strategies [8][9][10][11][12][13][14]. The near-optimal TES control strategy proposed in [9] is comparable to optimal TES control strategy obtained by dynamic programming.…”

Reducing a semiarid city’s peak electrical demand using distributed cold thermal energy storage

“…These optimal capacities estimated by EPRI represent ratios of energy storage to cooling power of between 3.3 Wh/W and 10 Wh/W, with unit capacities up to 150 kW and 1500 kW h, with the upper end of this spectrum serving schools, public facilities, and medium-sized commercial operations. Sizing of energy storage systems is crucial in order to ensure cost effectiveness, especially for the smallest residential systems [70,77,78]. This paper does not attempt to determine optimal sizing, and relies on this cited literature as a basis of our estimates.…”