Novel probabilistic optimization model for lead-acid and vanadium redox flow batteries under real-time pricing programs

The integration of storage systems into smart grids is being widely analysed in order to increase the flexibility of the power system and its ability to accommodate a higher share of wind and solar power. The success of this process requires a comprehensive techno-economic study of the storage technology in contrast with electricity market behaviour. The focus of this work is on lead-acid and vanadium redox flow batteries. This paper presents a novel probabilistic optimization model for managing energy storage systems. The model is able to incorporate the forecasting error of electricity prices, offering with this a near-optimal control option. Using real data from the Spanish electricity market from the year 2016, the probability distribution of forecasting error is determined. The model determines electricity price uncertainty by means of Monte Carlo Simulation and includes it in the energy arbitrage problem, which is eventually solved by using an integer-coded genetic algorithm. In this way, the probability distribution of the revenue is determined with consideration of the complex behaviours of lead-acid and vanadium redox flow batteries as well as their associated operating devices such as power converters

Local Density of States at Metal-Semiconductor Interfaces: An Atomic Scale Study

We investigate low temperature grown, abrupt, epitaxial, nonintermixed, defect-free n-type and p-type Fe/GaAs(110) interfaces by cross-sectional scanning tunneling microscopy and spectroscopy with atomic resolution. The probed local density of states shows that a model of the ideal metal-semiconductor interface requires a combination of metal-induced gap states and bond polarization at the interface which is nicely corroborated by density functional calculations. A three-dimensional finite element model of the space charge region yields a precise value for the Schottky barrier height

Embedding quasi-static time series within a genetic algorithm for stochastic optimization: the case of reactive power compensation on distribution systems

This paper presents a methodology for the optimal placement and sizing of reactive power compensation devices in a distribution system (DS) with distributed generation. Quasi-static time series is embedded in an optimization method based on a genetic algorithm to adequately represent the uncertainty introduced by solar photovoltaic generation and electricity demand and its effect on DS operation. From the analysis of a typical DS, the reactive power compensation rating power results in an increment of 24.9% when compared to the classical genetic algorithm model. However, the incorporation of quasi-static time series analysis entails an increase of 26.8% on the computational time required

Contract design of direct-load control programs and their optimal management by genetic algorithm

A computational model for designing direct-load control (DLC) demand response (DR) contracts is presented in this paper. The critical and controllable loads are identified in each node of the distribution system (DS). Critical loads have to be supplied as demanded by users, while the controllable loads can be connected during a determined time interval. The time interval at which each controllable load can be supplied is determined by means of a contract or compromise established between the utility operator and the corresponding consumers of each node of the DS. This approach allows us to reduce the negative impact of the DLC program on consumers’ lifestyles. Using daily forecasting of wind speed and power, solar radiation and temperature, the optimal allocation of DR resources is determined by solving an optimization problem through a genetic algorithm where the energy content of conventional power generation and battery discharging energy are minimized. The proposed approach was illustrated by analyzing a system located in the Virgin Islands. Capabilities and characteristics of the proposed method in daily and annual terms are fully discussed, as well as the influence of forecasting errors

Impact of transport electrification on critical metal sustainability with a focus on the heavy-duty segment

The majority of transport electrification studies, examining the demand and sustainability of critical metals, have focused on light-duty vehicles. Heavy-duty vehicles have often been excluded from the research scope due to their smaller vehicle stock and slower pace of electrification. This study fills this research gap by evaluating the lithium resource impacts from electrification of the heavy-duty segment at the global level. Our results show that a mass electrification of the heavy-duty segment on top of the light-duty segment would substantially increase the lithium demand and impose further strain on the global lithium supply. The significant impact is attributed to the large single-vehicle battery capacity required by heavy-duty vehicles and the expected battery replacement needed within the lifetime of heavy-duty vehicles. We suggest that the ambition of mass electrification in the heavy-duty segment should be treated with cautions for both policy makers and entrepreneurs

Magnetism of 3d transition-metal monolayers on Rh(100)

We employ the full-potential linearized augmented plane-wave method to report a systematic density-functional theory study of the magnetic properties of the 3d transition-metal (V, Cr, Mn, Fe, Co, and Ni) monolayers deposited on the Rh(100) substrate. We find that all monolayer films are magnetic. The size of the local magnetic moments across the transition-metal series follows Hund's rule with a maximum magnetic moment of 3.77 mu(B) for Mn. The largest induced magnetic moment of about 0.46 mu(B) was found for Rh atoms adjacent to the Co film. When relaxations are included, we predict a ferromagnetic (FM) ground state for V, Co, and Ni, while Cr, Mn, and Fe favor a c(2 x 2) antiferromagnetic (AFM) state, a checkerboard arrangement of up and down magnetic moments. The magnetic anisotropy energies of these ultrathin magnetic films are calculated for the FM and AFM states. With the exception of Cr, the easy axis of the magnetization is predicted to be in the film plane. Rough estimates of the ordering temperatures are given. To gain an understanding of the c(2 x 2) AFM state of Fe/Rh(100), we analyze this result with respect to the trends of the magnetic order of 3d monolayers on other 4d substrates, such as Pd(100) and Ag(100)

Complex Magnetism of Iron Monolayers on Hexagonal Transition Metal Surfaces from First Principles

Using first-principles calculations, we demonstrate that an Fe monolayer can assume very different magnetic phases on hcp (0001) and fcc (111) surfaces of 4d- and 5d-transition metals. Due to the substrates' d-band filling, the nearest-neighbor exchange coupling of Fe changes gradually from antiferromagnetic (AFM) for Fe films on Tc, Re, Ru, and Os to ferromagnetic on Rh, Ir, Pd, and Pt. In combination with the topological frustration on the triangular lattice of these surfaces the AFM coupling results in a 120 degrees Neel structure for Fe on Re and Ru and an unexpected double-row-wise AFM structure on Rh, which is a superposition of left- and right-rotating 90 degrees spin spirals

A multi-criteria and multi-expert decision aid approach to evaluate the future Turkish power plant portfolio

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