The power-to-ammonia (P2A) technology possesses the potential to surmount the challenges posed by the variability
intermittency
and peak-shifting nature of renewable energy generation
which represents a pivotal strategy for facilitating the low-carbon and clean transformation of the energy system. To address the issues of integration challenges associated with a high proportion of wind and solar power
this paper proposes a model for optimizing the operation of a wind and solar power-based hydrogen production and ammonia synthesis system. This model encompasses electrolytic hydrogen production
ammonia synthesis
gas hydrogen blending
and coal-ammonia combustion technologies. By employing the sequential operations theory
the joint output probability of wind and solar power is calculated while establishing probability reserve constraints in the form of an opportunity constraint to balance expected renewable energy outputs with actual output deviations. To ensure supply-demand equilibrium
a system optimization model that considers integrated demand response and real-time energy price mechanisms is developed. Simulation and comparative analysis across different scenarios demonstrate that the proposed method can be adopted to reduce carbon emissions by 5.82% while achieving 98.3% absorption of wind and photovoltaic power. The system is capable of maintaining safe and reliable operation under uncertainty; when the hydrogen blending ratio of the gas turbine reaches 16%
Energy-saving Emission-reduction Dispatching of Electrical Power System Considering Uncertainty of Load with Wind Power and Plug-in Hybrid Electric Vehicles
Robust Allocation of Energy Storage System for Multiple Wind Farms
Research Progress of Fault Prediction and Health Management for On-board Traction Transformers
Miniature Probe for Simultaneously Measuring Pulsed Electromagnetic Fields
Combination Model of Chance-constrained Security Constraint Unit with Considering the Forecast Uncertainties of DLR and Wind Power
Related Author
RONG Hailong
ZHU Changping
ZHU Chensong
ZHAO Jinquan
XIE Jun
ZHANG Xiaohua
WEN Jinyu
CHEN Yan
Related Institution
School of Energy & Electric, Hohai University
College of Automation, Nanjing University of Posts and Telecommunications
Jiangsu Key Laboratory of Power Transmission and Distribution Equipment Technology
School of Urban Rail Transportation, Changzhou University