• Energy Research
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AbstractDecarbonising the energy system requires high shares of variable renewable generation and sector coupling like power to heat. In addition to heat supply, heat pumps can be used in future energy systems to provide flexibility to the electricity system by using the thermal storage potential of the building stock and buffer tanks to shift electricity demand to hours of high renewable electricity production. Bridging the gap between two methodological approaches, we coupled a detailed building technology operation model and the open-source energy system model Balmorel to evaluate the flexibility potential that decentral heat pumps can provide to the electricity system. Austria in the year 2030 serves as an example of a 100% renewable-based electricity system (at an annual national balance). Results show that system benefits from heat pump flexibility are relatively limited in extent and concentrated on short-term flexibility. Flexible heat pumps reduce system cost, CO2 emissions, and photovoltaics and wind curtailment in all scenarios. The amount of electricity shifted in the assessed standard flexibility scenario is 194 GWhel and accounts for about 20% of the available flexible heat pump electricity demand. A comparison of different modelling approaches and a deterministic sensitivity analysis of key input parameters complement the modelling. The most important input parameters impacting heat pump flexibility are the flexible capacity (determined by installed capacity and share of control), shifting time limitations, and cost assumptions for the flexibility provided. Heat pump flexibility contributes more to increasing low residual loads (up to 22% in the assessed scenarios) than decreasing residual load peaks. Wind power integration benefits more from heat pump flexibility than photovoltaics because of the temporal correlation between heat demand and wind generation.

This experimental study explores the possibility of using an existing Trombe wall as a space for year-round cultivation to increase building resource efficiency. To do so with the least cost to the building, a small 0.75 m2/5.45 m3 Trombe wall cavity space was retrofitted with shelves placed behind the glazing, additional ventilation, and a watering network to be able to grow 400 hydroponic Kratky basil plants in individual glass jars. Historical thermal observations made at the site over a year-long timespan were contrasted with the experimental readings. When fully equipped, the Trombe wall’s thermal mass increased by 51%, which had a balancing effect on the system, lowering the average daily thermal oscillations from 35.41 °C to 17.88 °C. The living plants and water have also had significant cooling (26.99 °C to 22.91 °C) and humidifying (39.88 to 47.74%) effects. The system’s energy efficiency, however, decreased from 26 to 18% (absorption) and from 85 to 46 (dissipation), lowering its energy contribution to the building by about 30%. The average plant’s lifespan within the Trombe wall was 46 days, with 15% of the specimens surpassing the 100-day mark. Over the course of a year, 20.55 kg of edible greens were grown in the Trombe wall. The experiment has shown that it is possible to grow the plants inside the Trombe wall cavity during the warmer half of the year, revealing many possible ways to improve the space’s comfort, yields, and energy efficiency.

Abstract The ability of the Distributed Generation (DG) to solve problems such as power system deregulation and power demand problems appropriate to its purpose, which is to inject electricity in a distributed manner at a point close to the load, causes the distributed generation to become the latest trend in electricity generation technology. Proper position of distributed generation is necessary in order to achieved maximum benefit from DG, which could be due to an incorrect allocation of DG sources to the power network would not only result in increased power losses, but could also jeopardize the operation of the system. This paper introduces an ACO-algorithm for optimal location of DGs using a real network in one of a rural area of Malaysia. The method is used to determine the effectiveness of DG by comparing the losses of power and the improvement of the voltage profile. As for the confirmation to the ACO method, another method known as brute force method is use to compare the data gain as validation purposes.

Hydrothermal liquefaction (HTL) is an effective way to treat solid wastes with high moisture content. The co-hydrothermal liquefaction (co-HTL) experiments of oily scum and poplar sawdust biochar at the different hydrothermal temperatures were performed in this work. The changes of the appearance and components of the liquid products were comprehensively studied. The results showed that the addition of biochar into oily scum significantly reduced the moisture content of the residue hydrochars obtained after co-HTL. As the hydrothermal temperature increased, the liquid products obtained from co-HTL turned clearer and lighter in color, and the recovery rate of the liquid products significantly increased. The co-HTL of bi-ochar and oily scum could effectively improve the liquid quality and enhance the recovery rate of hydrochars. The carbon numbers of the liquid products obtained from co-HTL were concentrated in C5-C11, which were main compositions of gas-oline. This work can provide basic data and theoretical reference for oily scum efficient treatment and engineering practice.

High penetration of renewable energy sources into isolated microgrids (µGs) is considered a critical challenge, as µGs’ operation at low inertia results in frequency stability problems. To solve this challenge, virtual inertia control based on an energy storage system is applied to enhance the inertia and damping properties of the µG. On the other hand, utilization of a phase-locked loop (PLL) is indispensable for measuring system frequency; however, its dynamics, such as measurement delay and noise generation, cause extra deterioration of frequency stability. In this paper, to improve µG frequency stability and minimize the impact of PLL dynamics, a new optimal frequency control technique is proposed. A whale optimization algorithm is used to enhance the virtual inertia control loop by optimizing the parameters of the virtual inertia controller with consideration of PLL dynamics and the uncertainties of system inertia. The proposed controller has been validated through comparisons with an optimized virtual inertia PI controller which is tuned utilizing MATLAB internal model control methodology and with H∞-based virtual inertia control. The results show the effectiveness of the proposed controller against different operating conditions and system disturbances and uncertainties.

To mitigate the temperature increase in urban environments and reduce its impact on energy consumption and the quality of the environment, urban retrofitting technologies have been developed and applied worldwide. High albedo in urban surfaces and additional vegetation are the most efficient strategies to accomplish these goals. The objective of this study is to estimate the weight of these strategies, both individually and integrated, on the cooling potential of two Latin American cities. To do this, 36 low and high urban density scenarios were simulated with the ENVI-Met software. The simulation models were calibrated using air temperature curves which were monitored during the summer periods from 2010 to 2013. A Principal Components Analysis was carried out to establish possible associations between the proposed mitigation strategies and then the weight of anthropogenic heat was evaluated according to the configuration. The results show that the integrated mitigation strategies in urban areas -i. e. increase vegetation and albedo on horizontal surfaces- has a great potential to mitigate urban warming, showing a more significant impact on low-density urban configuration. The contribution of anthropogenic heat mainly produced by motorized transport and air conditioning systems, is a crucial input data for the urban microclimate simulations. Its impact on the urban densification processes may cancel out the benefits derived by the application of the mitigation strategies considered.

AbstractService unavailability of transmission lines, due to the direct and indirect lightning strikes, is evaluated as a challenging issue within electric companies. The lightning event can produce dangerous overvoltage, equipment failures, and power supply interruptions. Here, externally gapped line arresters (EGLAs) performances installed on a 63 kV transmission line are modelled using EMTP‐ATP to investigate their capability to withstand current and energy discharged by lightning strokes during back flashover phenomena. Frequency behaviour of the grounding system impedance, first and subsequent lightning current parameters effects on insulators back flashover and lightning flashover failure rate have been considered by Monte‐Carlo method. Then, extensive analysis has been carried out to study the absorbed energy of the EGLA and its expected life. The results show the dependency of failure rate and the EGLA expected life on the soil resistivity and lightning strike parameters. The selected EGLA must be provided sufficient lightning protection to the transmission line based on its absorbed energy capability, the soil and lightning parameters and be complied with the discharge energy capability requirement specified by the utility company.

The Box–Jenkins model is a polynomial model that uses transfer functions to express relationships between input, output, and noise for a given system. In this article, we present a Box–Jenkins linear model for a lithium-ion battery cell for use in electric vehicles. The model parameter identifications are based on automotive drive-cycle measurements. The proposed model prediction performance is evaluated using the goodness-of-fit criteria and the mean squared error between the Box–Jenkins model and the measured battery cell output. A simulation confirmed that the proposed Box–Jenkins model could adequately capture the battery cell dynamics for different automotive drive cycles and reasonably predict the actual battery cell output. The goodness-of-fit value shows that the Box–Jenkins model matches the battery cell data by 86.85% in the identification phase, and 90.83% in the validation phase for the LA-92 driving cycle. This work demonstrates the potential of using a simple and linear model to predict the battery cell behavior based on a complex identification dataset that represents the actual use of the battery cell in an electric vehicle.

Bu çalışma, 1990-2016 döneminde koordineli piyasa ekonomileri için tarımsal katma değerin, orman alanlarının, ekonomik büyümenin ve yenilenebilir ve yenilenemez enerji tüketiminin çevresel kalite üzerindeki etkisini panel Common Corelated Effects (CCE) modelini kullanarak incelemeyi amaçlamaktadır. Panel CCE modelinden elde edilen uzun dönem katsayılara göre orman alanlarının çevre kalitesini arttırdığı, başka bir ifadeyle karbondioksit emisyonunu azalttığı, yenilenemez enerji tüketiminin ve ekonomik büyümenin ise çevre kalitesi üzerinde negatif bir etki oluşturduğu tespit edilmiştir. Ayrıca, incelenen dönemde tarımsal katma değerin ve yenilenebilir enerji tüketiminin çevre kalitesi üzerinde bir etki oluşturmadığı görülmüştür. Son olarak değişkenler arasındaki nedensellik ilişkisi Dumitrescu–Hurlin testi ile araştırılmıştır. Uygulanan nedensellik testi ile tarım ile karbondioksit emisyonları, tarım ile yenilenemez enerji tüketimi, yenilenebilir enerji tüketimi ile yenilenemez enerji tüketimi arasında çift yönlü nedensellik ilişkisi elde edilmiştir.