Developing optimal energy management of integrated energy systems in the hybrid electricity and gas networks

Coordination of different energy resources provide specific opportunities to improve energy efficiency, higher service reliability, better power quality, reduce environmental pollution and flexibility of the energy supply. This paper presents a novel optimal operation and planning for the integrated energy systems (IESs). The IES inherits several forms of energy supply, energy storage system and energy conversion equipment, and achieves the coupling of different types of energy in different links such like network, charge and source. The main challenge and complicate of the operation of IESs is determining the optimal interaction between different energy types for supplying electric and thermal loads in order to improve overall energy utilization efficiency. To implement this challenge, an integration of natural gas network with a modified IEEE 33 bus electricity system connected to the upstream power grid has been used to examine the system performance over a wide range. In this research, the multi-objective optimization problem is employed in order to reduce total net emissions and operating costs simultaneously. Due to the uncertainty related to day-ahead forecasts (24 h), a Monte Carlo simulation is utilized to estimate renewable energy resources, thermal, and electric loads. The adaptive particle swarm optimization (APSO) technique is used to minimized the IES's operating costs. Using the APSO method, the operational costs are reduced by 2.96% and 4.62%, in comparison with PSO and genetic algorithm (GA), respectively. Also, the amounts of emissions are reduced by 4.68% and 6.03% than the PSO and GA methods, respectively. The proposed method can outperform others on system operating cost and distributed energy resource utilization with satisfactory energy-efficiency and environmental performance.

Automated summary

This paper introduces a novel optimal operation and planning method for integrated energy systems (IESs), aiming to improve overall energy utilization efficiency by coordinating and optimizing different energy types in various links.