Improving the Efficiency of Large-Scale Linear Programming Models for Energy Systems Using Graph Theory
Linear program (LP) models for energy system optimization can be made significantly more computationally efficient without sacrificing accuracy by leveraging graph theory to simplify the model structure and reduce the number of variables and constraints.
Optimizing Nigeria's 2050 Electricity Grid: A Comparative Analysis of Systems With and Without Grid-Scale Storage
Integrating grid-scale electricity storage in Nigeria's electricity grid is crucial for achieving a sustainable and efficient electricity system by 2050, enabling increased renewable energy integration and reduced CO2 emissions, despite a slight increase in total annual cost.
Long-Term Optimization of Unit Commitment and Investment Planning for Multi-Energy Systems: A Case Study on Berlin's District Heating Network
This paper introduces a novel mixed-integer linear programming (MILP) model for integrated unit commitment and long-term investment planning in multi-energy systems, demonstrating its effectiveness in a case study on Berlin's district heating network to identify cost-effective decarbonization pathways.
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