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Editorial Complex Optimization and Simulation in Power Systems

Abstract To achieve the EU climate and energy objectives, a transition towards a future sustainable energy system is needed. The integration of the huge potential for industrial waste heat recovery into smart energy system represents a main opportunity to accomplish these goals. To successfully implement this strategy, all the several stakeholders' conflicting objectives should be considered. In this paper an evolutionary multi-objective optimization model is developed to perform a sustainability evaluation of an energy system involving an industrial facility as the waste heat source and the neighbourhood as district heating network end users. An Italian case study of heat recovery from a steel casting facility shows how the model allows to properly select the district heating network set of users to fully exploit the available waste energy. Design directions such as the thermal energy storage capacity can be also provided. Moreover, the model enables the analysis of the trade-off between the stakeholders’ different perspectives, allowing to identify possible win-win solutions for both the industrial sector and the citizenship.

The electrical resistance of Ni 50 Ti 30 Hf 20 and Ni 50 Ti 40.5 Hf 9.5 alloys during Stress Assisted Two Way Memory Effect was investigated with the aim to deduce the relationship between electrical resistance and deformation across the transformation range. Results show an almost linear relationship although a crossing point between increasing and decreasing deformation may compromise the use of these alloys actuators.

Laboratory corrosion and scaling testing of metallic materials exposed in high temperature and pressure environments generally involves complex, multi-instrument measurement setups. Here, we present a setup including an autoclave that is instrumented for in-situ electrochemical testing and that contains a ZrO2-based solid-state pH electrode and devices for temperature control and solution stirring. We show results highlighting the importance of adequate pre-calibration of the pH measurement, due to the hysteresis depending on temperature sweep. Additionally, we illustrate how interfacing the autoclave and the electrochemical cell to measuring and controlling instruments, using different data communication interfaces, can create ground loops. These ground loop interferences can introduce significant errors in the measurement, such as a potential shift of >100 mV. In complex, multi-instrument setups, a complete understanding of ground loops may often be difficult. Thus, we recommend systematic checks to identify the ground loops and we propose measures to avoid them. Measurement, 155 ISSN:0263-2241 ISSN:1873-412X

A detailed analysis of the effects of ground grid configuration on grounding performance has been carried out for uniform and horizontally stratified soils with multiple layers. The results of the analysis reveal that the most efficient and cost-effective design is highly dependent on soil structure type and characteristics. In the absence of ground rods, grounding grids with uniform mesh size are quite efficient in soils having a thin (relative to grid size) high resistivity (relative to the lower layers) top soil, while grids with small mesh size at the periphery of the grid provide optimum performance in uniform soils and soils with low resistivity top soils. Ground rods were found to be effective only when a significant portion of their length is in contact with a low resistivity soil, as expected.

Short-term generation scheduling is an important function in daily operational planning of power systems. It is defined as optimal scheduling of power generators over a scheduling period while respecting various generator constraints and system constraints. Objective of the problem includes costs associated with energy production, start-up cost and shut-down cost along with profits. The resulting problem is a large scale nonlinear mixed-integer optimization problem for which there is no exact solution technique available. The solution to the problem can be obtained only by complete enumeration, often at the cost of a prohibitively computation time requirement for realistic power systems. This paper presents a hybrid algorithm which combines Lagrangian Relaxation (LR) together with Evolutionary Algorithm (EA) to solve the problem in cooperative and competitive energy environments. Simulation studies were carried out on different systems containing various numbers of units. The outcomes from different algorithms are compared with that from the proposed hybrid algorithm and the advantages of the proposed algorithm are briefly discussed.

UV/visible light is a promising radiation source for biomass pretreatment, but very little knowledge is available on the effect of UV on the thermal behavior of lignocellulose in comparison with more classical, physical pretreatment methods. In this paper, we investigate the effects of ball-milling and UV irradiation on two species of softwood and two species of hardwood, using X-ray diffractometry (XRD), evolved gas analysis-mass spectrometry (EGA-MS), and pyrolysis-gas chromatography coupled to mass spectrometry (Py-GC/MS). The XRD data showed that the crystalline fraction of cellulose was destroyed by milling, but not by irradiation. The EGA-MS data and isoconversional kinetic analysis showed that both milling and irradiation can reduce the thermal stability of wood up to a limit value. The Py-GC/MS data showed that irradiation caused the most significant changes in the pyrolytic behavior of the wood species, increasing the ratio of holocellulose to lignin pyrolysis products and the reactivity of cellulose toward the derivatizing agent. Softwoods were more affected by irradiation than hardwoods. This paper shows that UV irradiation can decrease the recalcitrance of biomass toward pyrolysis, but its efficiency is highly dependent on the type of lignocellulosic substrate.

The assessment of voltage stability margins is a promising direction for wide-area monitoring systems. Accurate monitoring architectures for long-term voltage instability are typically centralized and lack scalability, while completely decentralized approaches relying on local measurements tend towards inaccuracy. Here we present distributed linear algorithms for the online computation of voltage collapse sensitivity indices. The computations are collectively performed by processors embedded at each bus in the smart grid, using synchronized phasor measurements and communication of voltage phasors between neighboring buses. Our algorithms provably converge to the proper index values, as would be calculated using centralized information, but but do not require any central decision maker for coordination. Modifications of the algorithms to account for generator reactive power limits are discussed. We illustrate the effectiveness of our designs with a case study of the New England 39 bus system. 10 pages, submitted for publication