Operation optimization for integrated energy system based on hybrid CSP-CHP considering power-to-gas technology and carbon capture system

The roles of carbon capture, utilization and storage in the transition to a low-carbon energy system using a stochastic optimal scheduling approach

Carbon neutrality is an ambitious goal that has been promulgated to be achieved on or before 2060. However, most of the current energy policies focus more on carbon emission reduction, efficiency and high penetration of renewable energy. Thus, this paper presented a review strategy towards carbon neutrality by presenting the concept of a multi-energy system (MES) in terms of its technologies, configuration, modelling and feasibility as zero-emission equipment. The paper addressed some prominent challenges associated with zero-carbon multi-energy systems (ZCMES). Various proven solutions in the extant studies that have been affirmed to alleviate some of these challenges were presented. In the end, we identified and summarised the current research gaps, and the future directions to ensure the feasibility of ZCMES as a primary strategy towards the actualization of carbon neutrality. Hence, this review work serves as a reference for revising the current energy policies to incorporate a carbon neutrality framework. 

Strategic potential of multi-energy system towards carbon neutrality: A forward-looking overview

Multi-microgrid low-carbon economy operation strategy considering both source and load uncertainty: A Nash bargaining approach

This paper proposes a day-ahead optimization framework for the sustainable energy supply of an electric vehicle (EV) charging park and hydrogen refueling station (HRS) outfitted with the power-to‑hydrogen (P2H) conversion facility in a local multi-energy system (LMES). A novel integrated demand response (IDR) program with an incentive mechanism is used for power and heat demands, EV charging park, and HRS to further improve system flexibility and operational costs. A hybrid multi-objective information-gap decision theory/robust optimization (HMIRO) framework is also applied as an effective modeling technique for dealing with existing uncertainties with no need for a probability density function and scenario creation. The suggested HMIRO model is formulated as a tri-level mixed-integer linear programming (MILP) problem and converted into a single-level MILP problem using duality theory that enables the LMES operator to utilize two risk-averse strategies simultaneously due to the information-gap on uncertain parameters. The numerical results indicate that the proposed hybrid risk-averse strategy enables the LMES operator to guarantee a risk reduction of wind generation and HRS demand up to 20.6 % and 14.3 %, respectively, in day-ahead optimization while leading to a 5 % increase in the daily operation cost. Also, the daily energy cost can be reduced by up to 3.52 %, 2.88 %, 7.03 %, and 1.15 % with optimal IDR implementation for power load, heat load, EV charging park, and HRS in LMES, respectively. 

Sustainable energy supply of electric vehicle charging parks and hydrogen refueling stations integrated in local energy systems under a risk-averse optimization strategy

Feng Hong

Papers

Modeling and optimization of combined heat and power with power-to-gas and carbon capture system in integrated energy system