Day-ahead economical planning of multi-vector energy district considering demand response program

Increasing technology developments and economic considerations have also made the use of renewable energy sources (RESs) and energy storage systems (ESSs) inevitable. To achieve the holistic planning of a microgrid consisting of several energy resources, this paper proposes a novel multi-vector energy system based on elec-tricity, heating, and water generation sources. To supply electrical energy from heat generation units, a water-power nexus (WPN), an ESS, photovoltaic (PV) sources, and a combined heat and power (CHP) system are used. Considering the importance of Hydro generation in planning, combined energy-water and water-only systems are used to supply water demand, while heat-power and heating generation systems are used to supply heating. To make the model more realistic, the effects of the valve point, maximum and minimum generation constraints, increasing/decreasing rate, energy, water, and heating demand balance were taken into account. The main objective function of this study was to minimize multi-vector energy system costs in 24 h. To promote demand -side performance, the price-based demand response program was used to reduce the final costs in the entire study period. The proposed models have been formulated as a mixed-integer linear problem solved by the CPLEX solver in GAMS. Simulation results show that the use of RES and their proper management can reduce the generation of a thermal generator, which reduces the costs considerably. With the demand response program, the costs were reduced by 1.03%. This paper presents a systematic method for optimal system control that can provide a regulatory basis for the use of integrated generation sources.

Automated summary

This paper proposes a novel multi-vector energy system based on electricity, heating, and water generation sources for the holistic planning of a microgrid. Various energy resources such as water-power nexus, energy storage systems, photovoltaic sources, and combined heat and power systems are utilized to supply electrical energy and meet water and heating demands. The model takes into account various constraints and aims to minimize the costs of the multi-vector energy system. Simulation results demonstrate that the use of renewable energy sources and proper management can significantly reduce costs, especially when combined with a demand response program.