Abstract
The increasing demand for energy carriers has expanded the use of energy hubs that employ distributed demand response programs to improve power system reliability and efficiency. Moreover, the unstable behavior of renewable resources, as well as the indeterminate electrical and thermal demands, create major problems for energy hub operation. Inspired by this, this paper presents a day-ahead scheduling framework for energy hubs (EH) in energy and reserve markets considering two main objectives of economy and pollution emission. The studied energy hub consists of a novel hybrid energy storage facility based on a fuel cell, wind power, photovoltaic energy, and a particular fuel cell unit in the presence of elastic demand. This multi-component system participates in energy and reserve markets as a single entity to optimize energy hub operation. The proposed method also models the uncertainty of wind speed, photovoltaic irradiance, and load using the Mont-Carlo method. The energy hub risk level is analyzed using the conditional value at risk (CVaR) approach to increase the EH operation and efficiency. The proposed multi-objective energy hub model is solved using the MINLP method in General Algebraic Modeling System (GAMS) to minimize operation cost and pollution emission. Finally, to prove the effectiveness of adding a new E-fuel energy storage system and considering uncertainties on energy hub operation, the proposed method is compared with other reported models.
Highlights
In [25], the performance of an energy hub integrated with the wind turbine, and a novel storage and demand response in the distribution network was optimized using two objective functions including operation costs, pollution emission considering the uncertainty of wind speed, price, and load
The data required for the proposed energy hub management are divided into two parts for accurate scheduling
In this paper, a bi-objective optimization model was implemented for the robust scheduling of an optimal operation energy hub in the day-ahead and reserve markets
Summary
As the CP unit and furnace are generated pollution emission so it is necessary to analyze this problem He et al [22] are applied the robustness and opportunity functions of IGDT to investigate the effect of load and market price uncertainty on the performance of simple hub energy. In [25], the performance of an energy hub integrated with the wind turbine, and a novel storage and demand response in the distribution network was optimized using two objective functions including operation costs, pollution emission considering the uncertainty of wind speed, price, and load. Important issues include the investigation of uncertainty factors with the most accurate methods and analysis of risk level and its impact on energy hub performance, and considering the impact of reserve market participation on system costs and pollution. Restricting the saved heat level, the amount of input and output heat through E-fuel storage is given by: αmfuin × Ccst,fu ≤ Cts,tN,fu ≤ αmfuax × Ccst,fu (39)
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
