Abstract

In this paper, we investigate the problem of controlling a seasonal thermal energy storage (STES). The STES considered here is a large scale tank of heated water installed in a building and connected to a solar panel. The stored energy in the STES can be used for providing the building with the space heating (SP) and the domestic hot water (DHW). In order to utilize the STES efficiently, we design a suitable model predictive control (MPC) scheme. In this regard, we develop an appropriate model for the system with an emphasis on the computational tractability of problem. Toward this end, we introduce a bilinear model with analytical linearization. Subsequently, we solve the optimization problem using a sequential quadratic programming (SQP) framework in a reasonable computational time. For controlling the system, in addition to solving the corresponding optimization problem, the main challenge is incorporating seasonal features in the MPC. This issue is resolved by augmenting the cost function with an additional term which is defined based on the exergy of system. Moreover, we address the challenging question of deriving minimal achievable size of the STES tank while satisfying user demand of DHW and SP. Finally, the efficiency of the proposed method is verified numerically.

Highlights

  • The building sector consumes nearly 40% of the global energy in the U.S and Europe with the major part dedicated to heating demand [1]

  • We focused on the design problem of determining the minimal volume of the tank for which it is possible to supply the house with domestic hot water and space heating during one year of operation

  • While a seasonal thermal energy storage (STES) tank at temperature below 60◦C, e.g. 40◦C, can still provide the building with the space heating, it is not feasible to fulfill the requirements for domestic hot water

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Summary

Introduction

The building sector consumes nearly 40% of the global energy in the U.S and Europe with the major part dedicated to heating demand [1]. These newly developed resources are not available uniformly through the time. This highlights the importance of energy storage technologies for satisfying the demand at any time.

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Numerical Results
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