Optimization-Based Control Concept with Feed-in and Demand Peak Shaving for a PV Battery Heat Pump Heat Storage System

Abstract

The increasing share of renewable energies in the electricity sector promotes a more decentralized energy supply and the introduction of new flexibility options. These flexibility options provide degrees of freedom that should be used optimally. Therefore, in this paper, a model predictive control-based multi-objective optimizing energy management concept for a hybrid energy storage system, consisting of a photovoltaics (PV) plant, a battery, and a combined heat pump/heat storage device is presented. The concept’s objectives are minimal operation costs and reducing the power exchanged with the electrical grid while ensuring user comfort. In order to prove the concept to be viable and its objectives being fulfilled, investigations based on simulations of one year of operation have been carried out. Comparisons to a simple rule-based strategy and the same model predictive control scheme with ideal forecasts prove the concept’s viability while showing improvement potential in the treatment of nonlinear system behavior, caused by nonlinear battery losses, and of forecast uncertainties.

Minimizing Energy Cost in PV Battery Storage Systems Using Reinforcement Learning

“…The simple and commonly used priority-based EM usually provides the best results with regard to the degree of self-sufficiency of a PVBSS [12,14]. However, rule-based EM concepts cannot be used for more complex EM tasks, such as the multi-objective optimization [15] discussed in this paper, or the management of hybrid energy storage systems [16], since an analytical derivation of an optimal control policy is not practical for these cases.…”

Cost analysis of distributed storage in AC and DC microgrids

“…For heat pumps applications, relevant research includes cost-optimized sizing strategies [42,43] and optimization-based model predictive control [44]. Some works even study heat pumps in elec-tric vehicles for combined space and battery cooling [45].…”

State of the Art on Heat Pumps for Residential Buildings

“…The authors found that the smart control strategy can contribute to 26.4% of final energy reduction, 60% of the self-consumption increase and 15% of the net annual electricity cost reduction compared to the case with independent PV and heat pump. Similarly, a predictive control-based multi-objective optimization energy management concept was proposed for a PV system combined with heat pumps, heat storage, and batteries [89]. This concept was designed to reduce operational costs and power exchange with the power grid while ensuring comfort for the user.…”