Abstract
• Methodology for the simultaneous optimization of load shifting and MES management. • Optimal dispatch strategy of real-world load profiles over one year. • Primary energy consumption reduction of about 1% compared to baseline scenario. • Operational cost reduction of about 8% compared to baseline scenario. The optimal management of a multi-generation energy system is one of the challenges that an ever-growing energy demand requires to deal with. To tackle this urgent issue, this paper presents a methodology to identify the optimal dispatching strategy for a multi-generation energy system. The so-called time-of-use rate is one of the main time-based demand response programs which allows shifting the critical loads from a time interval to another (e.g., shifting electricity use to lower-priced hours of a day when demand is lower). Thus, the time-of-use rate is adopted in this paper in order to add flexibility to the management of the multi-generation energy system and thus optimize the interaction between energy production and user demand. In this paper, the goal is the minimization of primary energy consumption or operating costs. Whatever the considered objective function, the goal can be achieved by simultaneously acting on two levels, i.e., optimization of the demand response program and identification of the most favorable management strategy of the multi-generation energy system. A mixed-integer linear programming algorithm is employed to identify the optimal strategy. The case study considers an entire year of operation with a time step of one hour, by means of a real-world load profile. The proposed methodology allows both saving primary energy (more than 1%) and reducing operating costs (more than 8%). The proposed methodology demonstrates that the implementation of a demand response program within the optimal strategy for energy dispatch allows both saving primary energy and reducing operating costs with respect to the baseline scenario (i.e., no load shifting). The reduction of both primary energy consumption and operational costs is higher in the scenario with higher load shifting (in this paper, 30% of the daily electrical energy peak).
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