Locational-based Coupling of Electricity Markets: Benefits from Coordinating Unit Commitment and Balancing Markets

We formulate a series of stochastic models for committing and dispatching electric generators subject to transmission limits. The models are used to estimate the benefits of electricity locational marginal pricing (LMP) that arise from better coordination of day-ahead commitment decisions and real-time balancing markets in adjacent power markets when there is significant uncertainty in demand and wind forecasts. The unit commitment models optimise schedules under either the full set of network constraints or a simplified net transfer capacity (NTC) constraint, considering the range of possible real-time wind and load scenarios. The NTC-constrained model represents the present approach for limiting day-ahead electricity trade in Europe. A subsequent redispatch model then creates feasible real-time schedules. Benefits of LMP arise from decreases in expected start-up and variable generation costs resulting from consistent consideration of the full set of network constraints both day-ahead and in real-time. Meanwhile, using LMP to coordinate adjacent balancing markets provides benefits because it allows intermarket flow schedules to be adjusted in real-time in response to changing conditions. These models are applied to a stylised four-node network, examining the effects of varying system characteristics on the magnitude of the locational-based unit commitment benefits and the benefits of intermarket balancing. Although previous www.eprg.group.cam.ac.uk EPRG WORKING PAPER studies have examined the benefits of LMP, these usually examine one specific system, often without a discussion of the sources of these benefits, and with simplifying assumptions about unit commitment. We conclude that both categories of benefits are situation dependent, such that small parameter changes can lead to large changes in expected benefits. Although both can amount to a significant percentage of operating costs, we find that the benefits of balancing market coordination are generally larger than the unit commitment benefits

The Industrial Organization of Transport Markets: modeling pricing, investment and regulation in rail and road networks

Verhoef, E.T. [Promotor]Berg, V.A.C. van den [Copromotor

The FLC, enhanced fromavbility, and incremental sheet forming

The FLC is a well known concept in the sheet metal forming world. It is used to map the material’s formability and the make-ability of a product. The FLC is valid only within certain restrictions. These restrictions are: A: a straight strain path; B: absence of bending; C: absence of through-thickness shear; D: a condition of plane stress.\ud The formability of a material can be increased significantly if one is allowed to violate any of these restrictions, meaning either: use a complex strain path, incorporate bending, incorporate through-thickness shear, or apply a contact stress. Both shear and contact stress change the stress state, and both lower the yield stress in tension and raise the necking limit up to a certain level. Bending creates a non-uniform stress distribution over the thickness of the sheet, resulting in a reduction of the yield force in tension, and it creates a range of stable elongation depending on the sheet thickness at each passage of the punch. The effect of a complex strain path depends on the particular situation; in incremental sheet forming it is based on non-isotropic hardening.\ud In general it will not be possible to create such conditions in the entire product at once. However it is possible to do this intentionally in a small, restricted zone by creating special situations there. By moving this zone over the entire product the whole part can be made with increased formability. This technique of incremental forming is explained briefly. The special conditions around the punch indeed violate the FLC restrictions mentioned above. The enhanced formability obtained in incremental sheet forming is illustrated with many examples

Planning electricity transmission to accommodate renewables: Using two-stage programming to evaluate flexibility and the cost of disregarding uncertainty

We develop a stochastic two-stage optimisation model that captures the multistage nature of electricity transmission planning under uncertainty and apply it to a stylised representation of the Great Britain (GB) network. In our model, a proactive transmission planner makes investment decisions in two time periods, each time followed by a market response. This model allows us to identify robust first-stage investments and estimate the value of information in transmission planning, the costs of ignoring uncertainty, and the value of flexibility. Our results show that ignoring risk has quantifiable economic consequences, and that considering uncertainty explicitly can yield decisions that have lower expected costs than traditional deterministic planning methods. Furthermore, the best plan under a risk-neutral criterion can differ from the best under risk-aversion

Planning electricity transmission to accommodate renewables: Using two-stage programming to evaluate flexibility and the cost of disregarding uncertainty

We develop a stochastic two-stage optimisation model that captures the multistage nature of electricity transmission planning under uncertainty and apply it to a stylised representation of the Great Britain (GB) network. In our model, a proactive transmission planner makes investment decisions in two time periods, each time followed by a market response. This model allows us to identify robust first-stage investments and estimate the value of information in transmission planning, the costs of ignoring uncertainty, and the value of flexibility. Our results show that ignoring risk has quantifiable economic consequences, and that considering uncertainty explicitly can yield decisions that have lower expected costs than traditional deterministic planning methods. Furthermore, the best plan under a risk-neutral criterion can differ from the best under risk-aversion

Targets and tools for optimizing lignocellulosic biomass quality of miscanthus

Miscanthus is a perennial energy grass characterized by a high productivity and resource-use efficiency, making it an ideal biomass feedstock for the production of cellulosic biofuels and a wide range of other biobased value-chains. However, the large-scale commercialization of converting biomass into cellulosic biofuel is hindered by our inability to efficiently deconstruct the plant cell wall. The plant cell wall is a complex and dynamic structure and its components are extensively cross-linked into an unyielding matrix. The production of biofuel depends on the extraction, hydrolysis and fermentation of cell wall polysaccharides, which currently requires energetically and chemically intensive processing operations that negatively affect the economic viability and sustainability of the industry. To address this challenge it is envisioned that the bioenergy feedstocks can be compositionally tailored to increase the accessibility and extractability of cell wall polysaccharides, which would allow a more efficient conversion of biomass into biofuel under milder processing conditions. Extensive phenotypic and genetic diversity in cell wall composition and conversion efficiency was observed in different miscanthus species, including M. sinensis, M. sacchariflorus and interspecific hybrids between these two species. In multiple experiments a twofold increase in the release of fermentable sugars was observed in ‘high quality’ accessions compared to ‘low quality’ accessions. The exhaustive characterization of eight highly diverse M. sinensis genotypes revealed novel and distinct breeding targets for different bioenergy conversion routes. The key traits that contributed favourably to the conversion efficiency of biomass into biofuel were a high content of hemicellulosic polysaccharides, extensive cross-linking of hemicellulosic polysaccharides (revealed by a high content of trans-ferulic acids and a high ratio of arabinose-to-xylose), a low lignin content and extensive incorporation of para-coumaric acid into the lignin polymer. Lignin is widely recognized as one of the key factors conveying recalcitrance against enzymatic deconstruction of the cell wall. The incorporation of para-coumaric acid into the lignin polymer is hypothesized to make lignin more easily degradable during alkaline pretreatment, one of the most widely applied processing methods that is used to pretreat biomass prior to enzymatic hydrolysis. Previous studies have shown that reducing lignin content is often implicated in reduced resistance of plants to lodging. We hypothesize that extensively cross-linked hemicellulosic polysaccharides may fulfil a similar function in supporting cell wall structural rigidity and increasing the content of hemicellulosic polysaccharides may be a way to reduce lignin content without adversely affecting cell wall rigidity. This strategy can be used to improve biomass quality for biobased applications, as hemicellulosic polysaccharides are more easily degradable during industrial processing than lignin. Furthermore, hemicellulosic polysaccharides adhere to cellulose, which negatively affects the level of cellulose crystallinity. Crystalline cellulose is harder to degrade than its more amorphous form. Therefore the reduction of cellulose crystallinity is another mechanism through which increasing the content of hemicellulosic polysaccharides positively contributes to cell wall degradability. These results provided new insights into the traits that may be targeted to improve the quality of lignocellulose feedstocks. However, evaluation of complex biochemical traits for selection purposes is hindered by the fact that their accurate quantification is a costly, lengthy and laborious procedure. To overcome these limitations an accurate and high-throughput method was developed based on near-infrared spectroscopy. Through extensive calibration we developed accurate prediction models for a wide range of biomass quality characteristics, which may be readily implemented as a phenotyping tool for selection purposes. Additionally, progress through breeding may substantially be improved by marker-assisted selection, which will reduce the need for the evaluation of genotype performance in multi-year field trials. To this end, a biparental M. sinensis mapping population of 186 individuals was developed and genotyped using a genotyping-by-sequencing approach. A total of 564 short-sequence markers were used to construct a new M. sinensis genetic map. Cell wall composition and conversion efficiency were observed to be highly heritable and quantitatively inherited properties. This is the first genetic study in miscanthus to map quantitative trait loci (QTLs) for biomass quality properties and is a first step towards the application of marker-assisted selection for biomass quality properties. Through the evaluation of a diverse set of miscanthus genotypes in multiple locations we demonstrated that in addition to genotypic variation, growing conditions may have a substantial influence on cell wall composition and conversion efficiency. While further research is needed to identify which specific environmental parameters are responsible for the observed effects, these results clearly indicate that the environmental influence on biomass quality needs to be taken into account in order to match genotype, location and end-use of miscanthus as a lignocellulose feedstock. Moreover, significant genotype-by-environment interaction effects were observed for cell wall composition and conversion efficiency, indicating variation in environmental sensitivity across genotypes. Although the magnitude of the genotypic differences was small in comparison to genotype and environmental main effects, this affected the ranking of accession across environments. Stability analysis indicated some stable accessions performed relatively across diverse locations. In addition to trialing miscanthus in diverse locations, we also evaluated miscanthus biomass quality under drought conditions for a number of reasons: 1) drought stress is linked to a differential expression of cell wall biosynthesis genes, 2) incidence of drought events is increasing due to climate change, 3) irrigation is likely to be uneconomical during the cultivation of miscanthus and 4) miscanthus has many characteristics that make it a crop with a good potential for cultivation on marginal soils, where abiotic stresses such as drought may prevail. Drought stress was shown to result in a large reduction in cell wall and cellulose content and a substantial increase in hemicellulosic polysaccharides and cellulose conversion rates. We hypothesized that the reduction in cellulose content was due to an increase in the production of osmolytes, which are well-known for their role in plant protection against drought. The results indicated that drought stress had a positive effect on the cell wall degradability of miscanthus biomass. Overall the compendium of knowledge generated within the framework of this thesis provided insights into the variation in biomass quality properties in miscanthus, increased our understanding of the molecular, genetic and environmental factors influencing its conversion efficiency into biofuel and provided tools to exploit these factors to expand the use of miscanthus as a lignocellulose feedstock.</p

Global Sensitivity Analysis for Offshore Wind Cost Modelling

Abstract The costs of offshore wind are decreasing rapidly. However, there is a need to better understand the key drivers behind these cost reductions. New environmental regulations, economic policies, technological advancements and financing structures have resulted in a set of relationships that need to be considered in order to define risks and profitability for the next generation of offshore wind farms. We use an industry‐leading offshore wind cost modelling tool which integrates site characteristics, technology specificities and financial modelling expertise and apply state‐of‐art global sensitivity analysis methods for different classes of offshore wind farms, ranking the contribution of around 150 input parameters that influence the cost of offshore wind development. We show that the top 5 parameters when building an offshore wind investment business case are the wind speed, target equity rate of return, turbine costs, drilling costs and debt service coverage ratio. The contribution of this paper can help guide additional efforts towards reducing the uncertainty of those key parameters to decrease costs and provide a framework to choose global sensitivity analysis techniques for offshore wind techno‐economic models