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Biogas produced from anaerobic digestion processes has been considered as an important alternative to natural gas and plays a key role in the emerging market for renewable energy. By removing CO2, biogas can be upgraded to vehicle fuel. Chemical absorption is one of the widely used upgrading technologies, which advantages include high purity and low loss of biomethane. However, chemical absorption usually suffers from the high consumption of thermal energy, which is required by the regeneration of the solvent. Aiming at achieving a more sustainable and efficient biomethane production, this work proposed a novel system, which integrate concentrating photovoltaic/thermal hybrid (C-PV/T) in the upgrading of biogas. Due to the ability to produce electricity and heat simultaneously and efficiently, C-PV/T can provide the demands of both the electricity and heat. By doing dynamic simulation of the energy production of C-PV/T, the technical feasibility of such a system is analyzed. Based on the design to meet the heat demand of solvent regeneration, without energy storage, the produced heat can cover 17% of the heat demand of the solvent regeneration, but 51.1% of the electricity demand; meanwhile, 140.3 MWh excess electricity can be sold for one year. [ABSTRACT FROM AUTHOR]

The increasing penetration level of renewable energies requires more flexibility measures at the consumption side. Flexible energy prices have been placed by energy providers to promote flexibility measures from energy users. However, because of the current energy supply system in buildings, these flexible energy prices haven’t been fully taken advantage of. This study focuses on the integrated energy supply system in buildings. A Swedish office building is used as the case study. The integrated energy supply system is built by installing new components, including battery, heat pump and electrical heater, and hot water tank. Mixed Integer Linear Programming (MILP) problems are solved to determine the optimal component capacities and operation profiles. The results indicate that all the studied system configurations achieve lower net present cost (NPC) than the current system. It suggests that the integrated energy supply system can take advantage of the flexible energy prices and lower the overall energy cost in the building. Among the studied configurations, the combination of air source heat pump (ASHP) and electrical heater (EH) has the lowest investment cost. This combination also has the lowest NPC except in the scenario with low borehole cost. [ABSTRACT FROM AUTHOR]

To reduce the peak load, dynamic electricity price schemes have been widely used. Refrigerated warehouses consume a large amount of energy, most of which happens during the daytime due to the higher ambient temperature. This work evaluated the potential benefits of integrating energy storage in the refrigerated warehouses. Two types of energy storage systems have been considered, including a cold energy storage system and an electrical energy storage system. A dynamic model has been developed in TRNSYS to study the performance of those two energy storage systems and assess the benefits. Results show that using the cold energy storage to shift power consumption from daytime to nighttime can increase the energy efficiency of the refrigeration system. However, as the electrical energy storage system can shift more power consumption, it can achieve a large cost saving. Compared to the reference system without energy storage, the introductions of a cold energy storage system and an electrical energy storage system can reduce the operational cost by 10 and 53.7% respectively. [ABSTRACT FROM AUTHOR]

Selecting accurate and robust models is important for simulation and optimization of a clean energy system. This paper compares two photovoltaic (PV) models and two battery models in an open-source code, Opti-CE. The PV models are single diode model and its simplified model. The battery models are Improved Shepherd model and energy balance model. The models are compared from a perspective of overall system simulation and optimization in particular on both accuracy and computational time. The results indicate that simplified PV model causes 0.86% normalized root mean square error (nRMSE) compared with the single diode model, while decreases the simulation time from more than 800s to less than 0.01s. The energy balance battery model reduces simulation time from more than 5s to less than 0.03s. The energy balance model tends to underestimate the battery State of Charge (SOC) compared with the Improved Shepherd model. However, the error is not accumulative during the simulation. Compared to the Pareto front with single diode model and Improved Shepherd model, the simplified PV model increases the Pareto front values and result in both higher Self Sufficiency Ratio (SSR) and Net Present Value (NPV), while the energy balance battery model decreases the part of Pareto front, where individuals have low NPV. [ABSTRACT FROM AUTHOR]