Abstract The implementation of regional Integrated Energy System (IES) in urban areas enable the integration of multiple energy systems including electric, cooling and heating power systems. In this paper, we propose a stochastic programming planning method for IES based on Energy Hub model, in which energy price uncertainties from bulk energy systems are considered. In terms of investment planning for IES, the considered candidate options are combined cooling, heating and power (CCHP), gas boiler, centralized air conditioner with different sizes, which are described by several generalized constraints. Moreover, the operation cost of importing natural gas and electric power are considered, where several typical days based on annual load profile are included so that the cost can be simulated more accurately. The price uncertainties are described as normal distribution and simulated by multi-scene, thus a two-stage stochastic programming model is formulated with investment planning as first-stage problem and IES operation as second-stage problem. Case studies demonstrated the effectiveness of proposed model, in which the benefits of IES resulted from complementary and coordination between multi energy systems are illustrated.
[1]
Yi Wang,et al.
Mixed-integer linear programming-based optimal configuration planning for energy hub: Starting from scratch
,
2018
.
[2]
Samaneh Pazouki,et al.
Optimal planning and scheduling of energy hub in presence of wind, storage and demand response under uncertainty
,
2016
.
[3]
Abdullah Abusorrah,et al.
Optimal Expansion Planning of Energy Hub With Multiple Energy Infrastructures
,
2015,
IEEE Transactions on Smart Grid.
[4]
Sadegh Vaez-Zadeh,et al.
Optimal planning of energy hubs in interconnected energy systems: a case study for natural gas and electricity
,
2015
.
[5]
Behnam Mohammadi-Ivatloo,et al.
Optimal Stochastic Design of Wind Integrated Energy Hub
,
2017,
IEEE Transactions on Industrial Informatics.