In this report, the details of an investigation into the e ect of the low induction wind turbines on the Levelised Cost of Electricity (LCoE) in a 1GW o shore wind farm is outlined. The 10 MW INNWIND.EU conventional wind turbine and its low induction variant, the 10 MW AVATAR wind turbine, are considered in a variety of 10x10 layout configurations. The Annual Energy Production (AEP) and cost of electrical infrastructure were determined using two in-house ECN software tools, namely FarmFlow and EEFarm II. Combining this information with a generalised cost model, the LCoE from these layouts were determined. The optimum LCoE for the AVATAR wind farm was determined to be 92.15 e/MWh while for the INNWIND.EU wind farm it was 93.85 e/MWh. Although the low induction wind farm o ered a marginally lower LCoE, it should not be considered as definitive due to simple nature of the cost model used. The results do indicate that the AVATAR wind farms require less space to achieve this similar cost performace, with a higher optimal wind farm power density (WFPD) of 3.7 MW/km2 compared to 3 MW/km2 for the INNWIND.EU based wind farm.
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Decentralised renewable energy production in the form of fuels or electricity can have large scale deployment in future energy systems, but the feasibility needs to be assessed. The novelty of this paper is in the design and implementation of a mixed integer linear programming optimisation model to minimise the net present cost of decentralised hydrogen production for different energy demands on neighbourhood urban scale, while simultaneously adhering to European Union targets on greenhouse gas emission reductions. The energy system configurations optimised were assumed to possibly consist of a variable number or size of wind turbines, solar photovoltaics, grey grid electricity usage, battery storage, electrolyser, and hydrogen storage. The demands served are hydrogen for heating and mobility, and electricity for the households. A hydrogen residential heating project currently being developed in Hoogeveen, The Netherlands, served as a case study. Six scenarios were compared, each taking one or multiple energy demand services into question. For each scenario the levelised cost of hydrogen was calculated. The lowest levelised cost of hydrogen was found for the combined heating and mobility scenario: 8.36 €/kg for heating and 9.83 €/kg for mobility. The results support potential cost reductions of combined demand patterns of different energy services. A sensitivity analysis showed a strong influence of electrolyser efficiency, wind turbine parameters, and emission reduction factor on levelised cost. Wind energy was strongly preferred because of the lower cost and the low greenhouse gas emissions, compared to solar photovoltaics and grid electricity. Increasing electrolyser efficiency and greenhouse gas emission reduction of the used technologies deserve further research.
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This paper assesses wind resource characteristics and energy yield for micro wind turbines integrated on noise barriers. An experimental set-up with sonic anemometers placed on top of the barrier in reference positions is realized. The effect on wind speed magnitude, inflow angle and turbulence intensity is analysed. The annual energy yield of a micro wind turbine is estimated and compared using data from a micro-wind turbine wind tunnel experiment and field data. Electrical energy costs are discussed as well as structural integration cost reduction and the potential energy yield could decrease costs. It was found that instantaneous wind direction towards the barrier and the height of observation play an influential role for the results. Wind speed increases in perpendicular flows while decreases in parallel flow, by +35% down to −20% from the reference. The azimuth of the noise barrier expressed in wind field rotation angles was found to be influential resulted in 50%–130% changes with respect to annual energy yield. A micro wind turbine (0.375 kW) would produce between 100 and 600 kWh annually. Finally, cost analysis with cost reductions due to integration and the energy yield changes due to the barrier, show a LCOE reduction at 60%–90% of the reference value. https://doi.org/10.1016/j.jweia.2020.104206
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Power-to-gas technologies are considered to be part of the future energy sys- tem, but their viability and applicability need to be assessed. Therefore, models for the viability of farm-scale bio-power-to-methane supply chains to produce green gas were analysed in terms of levelised cost of energy, energy efficiency and saving of greenhouse gas emission. In bio-power-to-methane, hydrogen from electrolysis driven by surplus renewable electricity and carbon dioxide from biogas are converted to methane by microbes in an ex situ trickle-bed reactor. Such bio-methanation could replace the current upgrading of biogas to green gas with membrane technology. Four scenarios were compared: a refer- ence scenario without bio-methanation (A), bio-methanation (B), bio-methanation combined with membrane upgrading (C) and the latter with use of renewable energy only (all-green; D). The reference scenario (A) has the lowest costs for green gas production, but the bio-methanation scenarios (B-D) have higher energy efficiencies and environmental benefits. The higher costs of the bio-methanation scenarios are largely due to electrolysis, whereas the environmental benefits are due to the use of renewable electricity. Only the all- green scenario (D) meets the 2026 EU goal of 80% reduction of greenhouse gas emissions, but it would require a CO2 price of 200 € t−1 to achieve the levelised cost of energy of 65 €ct Nm−3 of the reference scenario. Inclusion of the intermittency of renewable energy in the scenarios substantially increases the costs. Further greening of the bio-methanation supply chain and how intermittency is best taken into account need further investigation.
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In Europe, green hydrogen and biogas/green gas are considered important renewable energy carriers, besides renewable electricity and heat. Still, incentives proceed slowly, and the feasibility of local green gas is questioned. A supply chain of decentralised green hydrogen production from locally generated electricity (PV or wind) and decentralised green gas production from locally collected biomass and biological power-to-methane technology was analysed and compared to a green hydrogen scenario. We developed a novel method for assessing local options. Meeting the heating demand of households was constrained by the current EU law (RED II) to reduce greenhouse gas (GHG) emissions by 80% relative to fossil (natural) gas. Levelised cost of energy (LCOE) analyses at 80% GHG emission savings indicate that locally produced green gas (LCOE = 24.0 €ct kWh−1) is more attractive for individual citizens than locally produced green hydrogen (LCOE = 43.5 €ct kWh−1). In case higher GHG emission savings are desired, both LCOEs go up. Data indicate an apparent mismatch between heat demand in winter and PV electricity generation in summer. Besides, at the current state of technology, local onshore wind turbines have less GHG emissions than PV panels. Wind turbines may therefore have advantages over PV fields despite the various concerns in society. Our study confirms that biomass availability in a dedicated region is a challenge.
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