• Energy Research
• Open Access close
• Restricted close
• other engineering and technologies close

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.

Abstract not Available.

One of the main uncertainties in long‐term distribution network planning is load forecasting error. This paper presents a probabilistic multistage expansion planning method to consider the load forecasting error as well as pseudo dynamic behavior of network parameters and geographical constraints. The optimal routes of MV feeders as backbone of distribution networks are obtained for both mid and long‐term case with deterministic and probabilistic modeling. The Imperialist Competitive Algorithm (ICA) is adapted for the optimal expansion planning of MV distribution network. To check and maintain the radial configuration of the MV distribution network during ICA random operators, a novel algorithm is employed. Comparative tabular and graphical results are given for deterministic and probabilistic planning. In probabilistic case the results is also represented by histogram of statistics data, mean and standard deviation of input and output variables using Monte Carlo Simulation (MCS). Based on the results it is possible to design the MV network at the presence of uncertainties more robust and flexible with respect to deterministic planning without reasonable increase in total cost. The efficiency and capability of the method is tested on a relatively large‐scale distribution network.

A successful rice production on swampland would require a planting material from high yielding varieties adaptated to the swampy ecosystem. This study was carried out to compare the growth and yield characteristics of five rice lines and a check variety as grown on non-tidal swampland. The lines were F4 generation of bulk selection from the crosses involving Bengkulu swamp rice landraces (Hanafi Putih, Tigo-tigo, Harum Curup, and Lubuk Durian) and high yielding varieties for the irrigated field (Sidenuk and Bestari). The trial was conducted on a shallow non-tidal swampland with stagnant inundation no more than 50 cm in depth often occurred during the plant life cycle. The lines and the check variety (Inpara 4) were arranged in a randomized complete block design with three replications. Observations were made for the agronomic performances of the plant, including plant height, total tiller number clump-1, effective tiller number clump-1, heading date, maturity date, panicle length, grain number panicle-1, 100-grain weight, and grain yield clump-1. Significant variation among the genotypes was found for all observed traits. On average, the evaluated lines showed comparable growth and yield performances to the check variety. Tigo-tigo × Bestari was the tallest line and potential for medium depth swampland. This line showed good overall agronomic performances and yielded relatively higher than the check variety, but delayed in attaining maturity. For shallow swampland, Hanafi Putih x Sidenuk exhibited the most potent line by having good overall agronomic and yield performances, except late in maturity. For early maturing line, Lubuk Durian x Hanafi Putih showed its potential for shallow swampland. Although this line was not the best, it showed better overall agronomic performances than the check variety. Keywords: F4 lines, growth and yield performance, rice landrace, swampland, plant maturity

Using phase detection in Surface Plasmon Resonance (SPR) sensing has potential improvements to the conventional intensity detection based SPR. Other than the phase detection and intensity detection based SPR in the visible range of the spectrum, employing SPR sensing principles in the infrared range by the use of silicon has also some promising advantages. Combining these two, in this paper, phase detection-based SPR sensing in the infrared range is studied using a mathematical model and numerical simulations. The results are compared with the results obtained by the simulations in the visible range. Performance improvements are noted by the use phase detection in the infrared range.

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.