Stochastic electrical and thermal energy management of energy hubs integrated with demand response programs and renewable energy: A prioritized multi-objective framework

Energy hubs (EH) are known as multi-carrier systems that integrate multiple energy resources to enable greater flexibility in the energy provision. In this study, a multi-objective decision-making framework is proposed to determine the optimal scheduling of EHs. The proposed model considers the total cost of the EH, emissions, power losses, and average reserve of EH, simultaneously. These objectives are prioritized based on the EH preference that can be different for each EH. In this strategy, the cost of the EH has the highest priority and is considered as the main objective. The emission, system losses, and system reserve simultaneously have been considered as secondary objectives. According to the prioritization made among objectives, a lexicography optimization is performed in which cost minimization is considered in the first step, and the secondary objectives are evaluated in the second step of optimization. The intermittency nature of the electrical and thermal loads, renewable generation, and market prices are applied to the model by stochastic techniques. The proposed multiobjective model has been tested on the non-real benchmark system (standard IEEE 5-bus test system). The simulation results show that the proposed model improves the reserve capacity, emission, and system losses.

Automated summary

This study proposes a multi-objective decision-making framework for determining the optimal scheduling of energy hubs (EHs), considering cost, emissions, power losses, and reserve simultaneously. Prioritization based on EH preferences and lexicography optimization are used to improve reserve capacity, emissions, and system losses in the proposed model, tested on a non-real benchmark system (IEEE 5-bus test system) with stochastic techniques applied to intermittency nature and renewable generation.