The Dutch government has set out to largely reach reductions in carbon emissions in the electricity sector with the utilization of offshore wind energy. Due to the intermittency of wind energy this poses new problems and challenges for the future electricity system in the Netherlands. The objective of this report is to identify the challenges for the electricity supply of offshore wind farms and to research how energy storage and alternative wind turbine design can aid in these challenges. The problems experienced and possible solutions are first identified by conducting a literature review and data analysis. Subsequently a Matlab model is constructed to simulate an offshore wind farm and energy storage system. This model is used to determine the most cost-efficient storage technique and the impact of this technique on the future electricity system. Of the challenges for future offshore wind farms do the short-term profile effects have the most influence. These effects negatively affect: 1. the security of supply in the electricity system, 2. the stability of the load on the high voltage grid and 3. the market value of the produced electricity. The impact of these effects is intensified by the strong correlation in power production between the connected (future) onshore and offshore wind farms. To reduce profile effects energy storage is used, the optimal configuration of the storage system has a power capacity between 0.23 and 0.27 times the rated power of the wind farm. For the optimal energy capacity, however, no optimum is found, and the design depends on the desired impact of the system. An analysis on the impact of an optimal design has shown that an offshore wind and energy storage system does not result in an economical feasible system. Short-term profile effect reduction with energy storage, however, is shown to be essential in a future electricity system that is dominated by wind and solar power. The short-term profile effects of wind energy production are correlated too much and will have a too high impact on the system if no energy storage is included in offshore wind electricity production.

AIM: To investigate whether subjective radiologist grading of motility on magnetic resonance enterography (MRE) is as effective as software quantification, and to determine the combination of motility metrics with the strongest association with symptom severity. MATERIALS AND METHODS: One hundred and five Crohn's disease patients (52 male, 53 female, 16–68 years old, mean age 34 years old) recruited from two sites underwent MRE, including a 20 second breath-hold cine motility sequence. Each subject completed a Harvey–Bradshaw Index (HBI) symptom questionnaire. Five features within normally appearing bowel were scored visually by two experienced radiologists, and then quantified using automated analysis software, including (1) mean motility, (2) spatial motility variation, (3) temporal motility variation, (4) area of motile bowel, (5) intestinal distension. Multivariable linear regression derived the combination of features with the highest association with HBI score. RESULTS: The best automated metric combination was temporal variation (p<0.05) plus area of motile bowel (p<0.05), achieving an R2 adjusted value of 0.036. Spatial variation was also associated with symptoms (p<0.05, R2 adjusted = 0.034); however, when visually assessed by radiologists, none of the features had a significant relationship with the HBI score. CONCLUSION: Software quantified temporal and spatial variability in bowel motility are associated with abdominal symptoms in Crohn's disease. Subjective radiologist assessment of bowel motility is insufficient to detect aberrant motility. Automated analysis of motility patterns holds promise as an objective biomarker for aberrant physiology underlying symptoms in enteric disorders.@en

AIM: To investigate whether subjective radiologist grading of motility on magnetic resonance enterography (MRE) is as effective as software quantification, and to determine the combination of motility metrics with the strongest association with symptom severity. MATERIALS AND METHODS: One hundred and five Crohn's disease patients (52 male, 53 female, 16–68 years old, mean age 34 years old) recruited from two sites underwent MRE, including a 20 second breath-hold cine motility sequence. Each subject completed a Harvey–Bradshaw Index (HBI) symptom questionnaire. Five features within normally appearing bowel were scored visually by two experienced radiologists, and then quantified using automated analysis software, including (1) mean motility, (2) spatial motility variation, (3) temporal motility variation, (4) area of motile bowel, (5) intestinal distension. Multivariable linear regression derived the combination of features with the highest association with HBI score. RESULTS: The best automated metric combination was temporal variation (p<0.05) plus area of motile bowel (p<0.05), achieving an R2 adjusted value of 0.036. Spatial variation was also associated with symptoms (p<0.05, R2 adjusted = 0.034); however, when visually assessed by radiologists, none of the features had a significant relationship with the HBI score. CONCLUSION: Software quantified temporal and spatial variability in bowel motility are associated with abdominal symptoms in Crohn's disease. Subjective radiologist assessment of bowel motility is insufficient to detect aberrant motility. Automated analysis of motility patterns holds promise as an objective biomarker for aberrant physiology underlying symptoms in enteric disorders.@en

AIM: To investigate whether subjective radiologist grading of motility on magnetic resonance enterography (MRE) is as effective as software quantification, and to determine the combination of motility metrics with the strongest association with symptom severity. MATERIALS AND METHODS: One hundred and five Crohn's disease patients (52 male, 53 female, 16–68 years old, mean age 34 years old) recruited from two sites underwent MRE, including a 20 second breath-hold cine motility sequence. Each subject completed a Harvey–Bradshaw Index (HBI) symptom questionnaire. Five features within normally appearing bowel were scored visually by two experienced radiologists, and then quantified using automated analysis software, including (1) mean motility, (2) spatial motility variation, (3) temporal motility variation, (4) area of motile bowel, (5) intestinal distension. Multivariable linear regression derived the combination of features with the highest association with HBI score. RESULTS: The best automated metric combination was temporal variation (p<0.05) plus area of motile bowel (p<0.05), achieving an R2 adjusted value of 0.036. Spatial variation was also associated with symptoms (p<0.05, R2 adjusted = 0.034); however, when visually assessed by radiologists, none of the features had a significant relationship with the HBI score. CONCLUSION: Software quantified temporal and spatial variability in bowel motility are associated with abdominal symptoms in Crohn's disease. Subjective radiologist assessment of bowel motility is insufficient to detect aberrant motility. Automated analysis of motility patterns holds promise as an objective biomarker for aberrant physiology underlying symptoms in enteric disorders.@en