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Current energy market designs and pricing schemes fail to give investors the appropriate market signals. In particular, energy prices are not high enough to attract investors to build new or maintain existing power capacity. In this paper we propose a method to compute second-best Pareto optimal equilibrium prices for any market exhibiting non-convexities and, based on this result, an energy market design able to restore the correct energy price signals for supply investors.

The unpredictable nature of wind energy makes its integration to the electric grid highly challenging. However, these challenges can be addressed by incorporating storage devices (batteries) in the system. We perform an overall assessment of a single domestic power system with a wind turbine supported by an energy storage device. The aim is to investigate the best operation mode of the storage device such that the occurrence of large power spills can be minimized. For estimating the small probability of large power spills, we use the splitting technique for rare-event simulations. An appropriate Importance Function for splitting is formulated such that it reduces the work-load of the probability estimator as compared to the conventional Crude Monte Carlo probability estimator. Simulation results show that the ramp constraints imposed on the charging/discharging rate of the storage device plays a pivotal role in mitigating large power spills. It is observed that by employing a new charging strategy for the storage device large power spills can be minimized further. There exists a trade-off between reducing the large power spills versus reducing the average power spills.

Abstract This paper summarizes observations and ideas on cellulose pyrolysis products and structural studies on cellulose chars with a focus on conceptual integration. Information is presented on the larger gas phase oligosaccharides in cellulose pyrolysates, their mechanism of formation and the implications for the processes in the initial stages of char formation. A model for the formation of a new thermally synthesized three-dimensional network polymer is proposed.

AbstractAutotrophs play an essential role in the cycling of carbon and nutrients, yet disease‐ecosystem relationships are often overlooked in these dynamics. Importantly, the availability of elemental nutrients like nitrogen and phosphorus impacts infectious disease in autotrophs, and disease can induce reciprocal effects on ecosystem nutrient dynamics. Relationships linking infectious disease with ecosystem nutrient dynamics are bidirectional, though the interdependence of these processes has received little attention. We introduce disease‐mediated nutrient dynamics (DND) as a framework to describe the multiple, concurrent pathways linking elemental cycles with infectious disease. We illustrate the impact of disease–ecosystem feedback loops on both disease and ecosystem nutrient dynamics using a simple mathematical model, combining approaches from classical ecological (logistic and Droop growth) and epidemiological (susceptible and infected compartments) theory. Our model incorporates the effects of nutrient availability on the growth rates of susceptible and infected autotroph hosts and tracks the return of nutrients to the environment following host death. While focused on autotroph hosts here, the DND framework is generalizable to higher trophic levels. Our results illustrate the surprisingly complex dynamics of host populations, infection patterns, and ecosystem nutrient cycling that can arise from even a relatively simple feedback between disease and nutrients. Feedback loops in disease‐mediated nutrient dynamics arise via effects of infection and nutrient supply on host stoichiometry and population size. Our model illustrates how host growth rate, defense, and tissue chemistry can impact the dynamics of disease–ecosystem relationships. We use the model to motivate a review of empirical examples from autotroph–pathogen systems in aquatic and terrestrial environments, demonstrating the key role of nutrient–disease and disease–nutrient relationships in real systems. By assessing existing evidence and uncovering data gaps and apparent mismatches between model predictions and the dynamics of empirical systems, we highlight priorities for future research intended to narrow the persistent disciplinary gap between disease and ecosystem ecology. Future empirical and theoretical work explicitly examining the dynamic linkages between disease and ecosystem ecology will inform fundamental understanding for each discipline and will better position the field of ecology to predict the dynamics of disease and elemental cycles in the context of global change.

As part of its efforts to progress and innovate in the field of Smart Grid technologies, Enexis developed and currently operates a Battery Energy Storage System (BESS) called the Smart Storage Unit (SSU), part of the Smart Storage Project (SSP). The SSU is a 400 kVA, 232 kWh storage system, equipped with internet-connected control hardware in order to add ¿smartness¿ into the equation. The objective of the project is to enable field-testing and research on advanced electricity storage solutions in the LV distribution grid. This paper mainly focusses on the development of an addition to the controller system for the purpose of minimizing grid losses and maximizing grid asset utilization. Its principles rely on using historic data for load prediction, in order to flatten the power demand at the transformer, through peak-reduction and valley-filling.

The development of the gapless metal oxide (ZnO) surge arrester has presented the arrester engineer with new materials and an opportunity for new designs. This situation arises because the gapless surge arrester is electrically active throughout its lifetime whereas its predecessor, the silicon carbide arrester, was electrically passive being electrically isolated with gap structures. The prime consideration is one of reliably estimating the lifetime of a gapless ZnO surge arrester under continuous ac stress while maintaining the capability not only to limit surge voltages but also to absorb energy inputs resulting from lightning or switching surges and temporary overvoltages. In this paper we establish a procedure for reliably estimating the lifetime of gapless metal oxide surge arresters for ac application by incorporating the device characteristics into design requirements. This method is illustrated for metal oxide surge arrester elements that exhibit a predictable linear resistive current versus time1/2 behavior as a function of applied voltage and temperature.