Applied Energy, Vol.170, 278-285, 2016
Modeling a power-to-renewable methane system for an assessment of power grid balancing options in the Baltic States' region
The explicit tendency to increase the power generation from stochastic renewable resources forces to look for technological solutions of energy management and storage. In the recent years, the concept of power-to-gas, where the excess energy is converted into hydrogen and/or further methanized into renewable methane, is gaining high popularity among researchers. In this study, we assess the power to-renewable methane system as the potential technology for power grid balancing. For the assessment, a mathematical model has been developed that assists in understanding of whether a power-to renewable methane system can be developed in a region with specific installed and planned capacities of wind energy and biogas plants. Considering the varying amount of excess power available for H-2 production and the varying biogas quality, the aim of the model is to simulate the system to determine, if wind power generation meets the needs of biogas plants for storing the excess energy in the form of methane via the methanation process. For the case study, the Baltic States (Estonia, Latvia, and Lithuania) have been selected, as the region is characterized by high dependence on fossil energy sources and electricity import. The results show that with the wind power produced in the region it would be possible to increase the average CH4 content in the methanized biogas by up to 48.4%. Yet, even with a positive H-2 net production rate, not in all cases the maximum possible quality of the renewable methane would be achieved, as at moments the necessary amount of H-2 for methanation would not be readily available, and the reaction would not be possible. Thus, in the region, the wind power capacities would not meet the biogas plant capacities nor now, nor until 2020. For the system's development, two potential pathways are seen as possible for balancing the regions' power grid. (C) 2016 Elsevier Ltd. All rights reserved.