Multistage Expansion Planning of Integrated Biogas and Electric Power Delivery System Considering the Regional Availability of Biomass

• Published in: IEEE transactions on sustainable energy Vol. 12; no. 2; pp. 920 - 930
• Main Authors: Yang, Hanyu, Li, Canbing, Shahidehpour, Mohammad, Zhang, Cong, Zhou, Bin, Wu, Qiuwei, Zhou, Long
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 01-04-2021; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Approximation; Approximation method; Availability; Biogas; Biomass; Biomass energy; Cooking; Decisions; District heating; Electric power; Electric power distribution; Electrical loads; expansion planning of integrated energy system; Integer programming; Linear programming; Mixed integer; Mixed integer linear programming; Natural gas; Power system planning; Power systems; Regional planning; Stochastic processes; stochastic programming; Stochasticity; Transportation networks
• ISSN: 1949-3029; 1949-3037
• DOI: 10.1109/TSTE.2020.3025831

Centralized biogas plant (CBP) provides an attractive solution to the energy supply for district heating, electric loads, and residential cooking in remote areas via a local biogas delivery network. To overcome the challenges of biomass availability for CBPs, an integrated expansion planning model is proposed in this paper. The model makes investment decisions on the sequential planning of integrated electric power distribution and biogas delivery networks and uses the constrained biomass transportation network to optimally determine CBP locations in the integrated network. The proposed approach also considers the biomass availability and the cost of biomass supply in the integrated model. The proposed multistage stochastic planning problem makes investment decisions considering the gradual realization of uncertainties as loads grow and biomass is made available. The polyhedral approximation method is applied to convert the proposed mixed-integer second-order cone programming (MISOCP) problem to a mixed-integer linear programming (MILP) problem for making the problem more tractable for large-scale cases. The effectiveness of the proposed integrated model is validated using an 8-node and a 24-node test system.