Abstract
Due to the capacity of thermal storage, electric water heater (EWH) is one of the best candidates for demand response programs. However, few attentions are given to the modeling and optimization of EWHs with thermostatically-controlled automatic water mixer (TCAWM). In this paper, differential thermodynamic model is established for EWHs with TCAWM and a piecewise linear approximation method is performed for the nonlinear thermodynamic model. The multi-objective optimization model is established by introducing an index reflecting the comfort degree of users, so that the optimal energy usage of the EWH can be obtained by mixed integer linear programming. Testing examples verify the effectiveness of the proposed method.
Highlights
With the increasing penetration of renewable energy, the safety and stability of the power system are facing more challenges
Electric water heater (EWH) are often considered in Demand response (DR) projects because of the capacity of load profiling by saving energy during peak hours that was previously stored during off-peak hours [13, 14]
The linear formulation of the multi-objective optimization model based on mixed integer linear programming (MILP) is designed to optimize the energy usage of an EWH with thermostatically-controlled automatic water mixer (TCAWM), which can be summarized by the following: À a linearized version of the objective function (13); ` subject to (14)–(18), (23)– (25)
Summary
With the increasing penetration of renewable energy, the safety and stability of the power system are facing more challenges. When considering TCAWM, the dynamics of the EWHs becomes complex and nonlinear, and cannot be solved using standard optimization algorithms such as mixed integer linear programming (MILP). The heuristic algorithms are direct, random, and easy to fall into local optimum, and have problems such as the long calculation time, weak global search ability [20] To fill this gap, this paper detailedly formulates the piecewise linear approximation functions of the nonlinear thermodynamic model and adopts a MILP method to optimize the energy usage of an EWH with TCAWM. By this way, the electricity cost can be saved and specific requests of users can be met.
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