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Recycled waste materials obtained from industrial and agricultural processes are becoming promising thermal and acoustic insulating solutions in building applications; their use can play an important role in the environmental impact reduction. The aim of the present paper is the evaluation of the thermal performance of recycled waste panels consisting of cork scraps, rice husk, coffee chaff, and end-life granulated tires, glued in different weight ratios and pressed. Six panels obtained from the mixing of these waste materials were fabricated and analyzed. In particular, the scope is the selection of the best compromise solutions from the thermal and environmental points of view. To this aim, thermal resistances were measured in laboratory and a Life Cycle Assessment (LCA) analysis was carried out for each panel; a cross-comparative examination was performed in order to optimize their properties and find the best panels solutions to be assembled in the future. Life Cycle Analysis was carried out in terms of primary Embodied Energy and Greenhouse Gas Emissions, considering a ‘‘cradle-to-gate” approach. The obtained thermal conductivities varied in the 0.055 to 0.135 W/mK range, in the same order of magnitude of many traditional systems. The best thermal results were obtained for the panels made of granulated cork, rice husk, and coffee chaff in this order. The rubber granulate showed higher values of the thermal conductivity (about 0.15 W/mK); a very interesting combined solution was the panel composed of cork (60%), rice husk (20%), and coffee chaff (20%), with a thermal conductivity of 0.08 W/mK and a Global Warming Potential of only 2.6 kg CO2eq/m2. Considering the Embodied Energy (CED), the best solution is a panel composed of 56% of cork and 44% of coffee chaff (minimum CED and thermal conductivity).

The growth of energy consumption has led to the depletion of fossil energy and the increasing greenhouse effect. In this case, low carbonization has become an important trend in the world’s energy development, in which clean energy occupies an important position. The uncertainties brought by the large-scale integration of wind power, photovoltaic and other renewable energy sources into the grid pose a serious challenge to system dispatch. The participation of demand response (DR) resources can flexibly cooperate with renewable energy, optimizing system dispatch and promoting renewable energy consumption. Thus, we propose a flexible DR scheduling strategy based on multiple response modes in this paper. We first present a DR resource operation model based on multivariate response modes. Then, the uncertainties are considered and dealt with by scenario generation and reduction technology. Finally, a day-head dispatch strategy considering flexible DR operation and wind power uncertainties is established. The simulation results show that the proposed strategy promotes wind power consumption and reduces system operation costs.

Energy consumption is a critical evaluation index of embedded systems, and it has impacts on battery-life, thermal design, as well as device security and reliability. Since energy is the time integral of power, power consumption should be considered, along with the impact of “time”; thus, we propose two designs of automatic energy consumption measuring platforms utilizing General Purpose Input/Output (GPIO). Using these designs, we developed software and introduced auxiliary hardware for solutions with better timing and synchronization. A series of test sets were designed to verify our designs’ capabilities and accuracy levels. Both of our designs showed an accuracy similar to that of traditional measuring methods, which can satisfy the needs of different occasions. In addition, our designs provide real-time energy consumption data, as well as unattended automated measurements.

Façade elements are a building component that satisfies multiple performance parameters. Among other things, “advanced façades” take advantage of hybrid solutions, such as assembling laminated materials. In addition to the enhanced mechanical properties that are typical of optimally composed hybrid structural components, these systems are energy-efficient, durable, and offer lighting comfort and optimal thermal performance, an example of which is the structural solution developed in collaboration with the University of Zagreb and the University of Ljubljana within the Croatian Science Foundation VETROLIGNUM project. The design concept involves the mechanical interaction of timber and glass load-bearing members without sealing or bonding the glass-to-timber surfaces. Following earlier research efforts devoted to the structural analysis and optimization of thus-assembled hybrid Cross-Laminated Timber (CLT)-glass façade elements, in this paper, special focus is given to a thermal and energy performance investigation under ordinary operational conditions. A simplified numerical model representative of a full-size building is first presented by taking advantage of continuous ambient records from a Live-Lab mock-up facility in Zagreb. Afterwards, a more detailed Finite Element (FE) numerical analysis is carried out at the component level to further explore the potential of CLT–glass façade elements. The collected numerical results show that CLT–glass composite panels can offer stable and promising thermal performance for façades similar to national and European standard requirements.

In the process of high-concentration photovoltaic (HCPV) power generation, multijunction cells work in the conditions of high radiation and high current. Non-uniformity of focusing, the mismatch between the focusing spectrum caused by the dispersion effect and the spectrum of multijunction solar cell design and the increase in cell temperature are the key factors affecting the photoelectric performance of the multijunction solar cell. The coupling effect of three factors on the performance of multijunction solar cell intensifies its negative impact. Based on the previous research, the light intensity and spectral characteristics under Fresnel lens focusing are calculated through the optical model, and the optical–electrical–thermal coupling model under non-uniform illumination is established. The results show that obvious changes exist in the concentration spectrum distribution, energy and non-uniformity along different optical axis positions. These changes lead to serious current mismatch and transverse current in the multijunction solar cell placed near the focal plane which decreases the output power. The lost energy makes the cell temperature highest near the focal plane. In the condition of passive heat dissipation with 500 times geometric concentration ratio, the output power of the solar cell near the focal plane decreases by 35% and the temperature increases by 15%. Therefore, optimizing the placement position of the multijunction cell in the optical axis direction can alleviate the negative effects of optical–electrical–thermal coupling caused by focusing non-uniformity, spectral mismatch and rising cell temperature, and improve the output performance of the cell. This conclusion is verified by the experimental result.

DC arc faults are dangerous to photovoltaic (PV) systems and can cause serious electric fire hazards and property damage. Because the PV inverter works in a high−frequency pulse width modulation (PWM) control mode, the arc fault detection is prone to nuisance tripping due to PV inverter noises. An arc fault detection method based on the autoregressive (AR) model is proposed. A test platform collects the database of this research according to the UL1699B standard, in which three different types of PV inverters are taken into consideration to make it more generalized. The arc current can be considered a nonstationary random signal while the noise of the PV inverter is not. According to the difference in randomness features between an arc and the noise, a detection method based on the AR model is proposed. The Burg algorithm is used to determine model coefficients, while the Akaike Information Criterion (AIC) is applied to explore the best order of the proposed model. The correlation coefficient difference of the model coefficients plays a role as a criterion to identify if there is an arc fault. Moreover, a prototype circuit based on the TMS320F28033 MCU is built for algorithm verification. Test results show that the proposed algorithm can identify an arc fault without a false positive under different PV inverter conditions. The fault clearing time is between 60 ms to 80 ms, which can meet the requirement of 200 ms specified by the standard.

With the development of smart home technology, more and more electrical appliances can participate in demand response, providing support for active power balance of the power grid. However, the conventional centralized control method faces vast amounts of electrical appliances, resulting in problems such as communication congestion and dimension curse. This paper proposes a distributed control strategy for electrical appliances based on a multi-agent consensus algorithm. Considering the discrete response characteristics of the on/off loads, a priority ranking mechanism is established, and the customer cost function is established by a fitting method. Based on the incremental cost consensus (ICC) algorithm, the optimal power allocation of customers is realized through distributed control. Simulation and analysis of the examples verify the effectiveness of the proposed strategy.