Face-centered cubic crystallization of atomistic configurations

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Optimal strategies for operating energy storage in an arbitrage or smoothing market

We characterize cost-minimizing operating strategies for an energy store over a given interval of time [0, T]. The cost functional here can represent, for example, a traditional economic cost or a penalty for time-variation of the output from a storage-assisted wind farm or more general imbalance between supply and demand. Our analysis allows for leakage, operating inefficiencies and general cost functionals. In the case where the cost of a store depends only on its instantaneous power output (or input), we present an algorithm to determine the optimal strategies. A key feature is that this algorithm is localized in time, in the sense that the action of the store at a time t ∈ [0, T] requires cost information over only some usually much shorter subinterval of time [t, tk] ⊂ [t, T]

Impact of storage competition on energy markets

We study how storage, operating as a price maker within a market environment, may be optimally operated over an extended period of time. The optimality criterion may be the maximisation of the profit of the storage itself, where this profit results from the exploitation of the differences in market clearing prices at different times. Alternatively it may be the minimisation of the cost of generation, or the maximisation of consumer surplus or social welfare. In all cases there is calculated for each successive time-step the cost function measuring the total impact of whatever action is taken by the storage. The succession of such cost functions provides the information for the storage to determine how to behave over time, forming the basis of the appropriate optimisation problem. We study particularly competition between multiple stores, where the objective of each store is to maximise its own income given the activities of the remainder. We show that, at the Cournot Nash equilibrium, multiple stores which between them have market impact collectively erode their own abilities to make profits: essentially each store attempts to increase its own profit over time by overcompeting at the expense of the remainder. We quantify this for linear price functions. We give examples throughout based on electricity storage and Great Britain electricity spot-price market data

Analysing the potential economic value of energy storage [WP]

This paper examines the likely market for electrical energy storage from a market viewpoint, taking market prices as given and determining the extent to which a strategy of arbitrage across the day, buying at the lowest price times at night and selling at the highest times during the early evening, generates profits in the British context. The paper sets out the potential problems as the market moves to absorb increasing amounts of wind, then characterises the nature of prices, which reveals the importance of a strategy in which power is absorbed into store for a relatively few hours of the day and discharged over a relatively few hours. The paper models the ongoing costs of operation and compares them with revenues, but does not consider construction costs. It argues that additional incentives may need to be put into place in order to render storage over relatively longer periods more attractive

Control of Energy Storage with Market Impact: Lagrangian Approach and Horizons

We study the control of large scale energy storage operating in a market. Re-optimization of deterministic models is a common pragmatic approach when prices are stochastic. We apply Lagrangian theory to develop such a model and to establish decision and forecast horizons when storage trading affects these prices, an important aspect of some energy markets. The determination of these horizons also provides a simple and efficient algorithm for the determination of the optimal control. The forecast horizons vary between one and fifteen days in realistic electricity storage examples. These examples suggest that modelling price impact is important

The North American tree-ring fire-scar network

Fire regimes in North American forests are diverse and modern fire records are often too short to capture important patterns, trends, feedbacks, and drivers of variability. Tree-ring fire scars provide valuable perspectives on fire regimes, including centuries-long records of fire year, season, frequency, severity, and size. Here, we introduce the newly compiled North American tree-ring fire-scar network (NAFSN), which contains 2562 sites, >37,000 fire-scarred trees, and covers large parts of North America. We investigate the NAFSN in terms of geography, sample depth, vegetation, topography, climate, and human land use. Fire scars are found in most ecoregions, from boreal forests in northern Alaska and Canada to subtropical forests in southern Florida and Mexico. The network includes 91 tree species, but is dominated by gymnosperms in the genus Pinus. Fire scars are found from sea level to >4000-m elevation and across a range of topographic settings that vary by ecoregion. Multiple regions are densely sampled (e.g., >1000 fire-scarred trees), enabling new spatial analyses such as reconstructions of area burned. To demonstrate the potential of the network, we compared the climate space of the NAFSN to those of modern fires and forests; the NAFSN spans a climate space largely representative of the forested areas in North America, with notable gaps in warmer tropical climates. Modern fires are burning in similar climate spaces as historical fires, but disproportionately in warmer regions compared to the historical record, possibly related to under-sampling of warm subtropical forests or supporting observations of changing fire regimes. The historical influence of Indigenous and non-Indigenous human land use on fire regimes varies in space and time. A 20th century fire deficit associated with human activities is evident in many regions, yet fire regimes characterized by frequent surface fires are still active in some areas (e.g., Mexico and the southeastern United States). These analyses provide a foundation and framework for future studies using the hundreds of thousands of annually- to sub-annually-resolved tree-ring records of fire spanning centuries, which will further advance our understanding of the interactions among fire, climate, topography, vegetation, and humans across North America

Optimal strategies for operating energy storage in an arbitrage market

We characterise profit-maximising operating strategies, over some time horizon [0, T], for an energy store which is trading in an arbitrage market. Our theory allows for leakage, operating inefficiencies and general cost functions. In the special case where the operating cost of a store depends only on its instantaneous power ouput (or input), we present an algorithm to determine the optimal strategies. A key feature is that this algorithm is localised in time, in the sense that the action of the store at a time t ∈ [0, T] only requires information about electricity prices over some subinterval of time [t, τ ] ⊂ [t, T]