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• The study makes the following main contributions: • 1) A mathematical layout is developed to include renewable resources for load scheduling in digital twin-based microgrids. • 2) Uncertainty modelling of PV production employing Beta PDF for load scheduling is utilized in digital twin environment. • 3) The load scheduling algorithm employing RL for minimizing the energy bills regarding a renewable resource is developed. Utility companies recognize the importance and necessity of demand response (DR) programs for reducing the increased production costs associated with rising energy demand. The advent of smart information and communication systems has made DR programs on the basis of cost a viable option to control load in smart microgrids. Small domestic consumers are rapidly using stochastic renewable energy resources such as photovoltaic (PV). The study examines an integrated layout for residential load scheduling or load commitment problems (LCP) with renewable energy resources no matter what kind of tariff is applied. Uncertainty-based decision-making problems are effectively solved using reinforcement learning (RL). The paper proposes an RL-enabled solution to the LCP in smart microgrids. An innovative aspect of the study is the development of an integrated layout containing an implementable solution that takes into account user satisfaction, stochastic renewable power, and tariffs. In simulation tests, the suggested layout is tested for its effectiveness and flexibility. An analysis of the algorithm's efficiency using a household user with schedule-able and non-schedulable devices, together with a PV resource, has been presented. [ABSTRACT FROM AUTHOR]

• Assessing solar power technical potential in China with high-resolution data. • Quantifying the gap between actual generation and technical potential at plant level. • Actual solar power generation is only 30% of the technical potential. • Technology, construction, and management factors cause the underperformance. Improving the power output of solar photovoltaic (PV) farms is critical to maximize the potential of PV power and reduce extensive land use in the context of large-scale deployment of renewable energy. In this paper we developed an integrated solar power potential assessment framework to quantify the gap between technical potential and actual generation of solar PV farms on national, provincial, and plant scales, and identify the key factors that cause the underperformance of PV farms. Specifically, to assess technical potential, hourly meteorological reanalysis data is adopted and the power generation-related parameters are calculated (i.e. optimal panel tilt, array spacing, packing factor etc.) with consideration of their spatial variability. For actual power generation, a detailed plant-level dataset is first established by this study which integrates technical, operational, and geospatial information from 145 solar farms across seven provinces in China. Our results show that the actual PV power generation per square meter is only 1/3 of the estimated technical potential. Technological factor is the primary factor, accounting for 48.43% of the underperformance, followed by engineering and management factors, accounting for 38.55% and 13.02%, respectively. The novelty of our study is revealing the underperformance level of solar farms in reality, identifying the causing factors, and highlighting the importance of integrating land-use efficiency indicators into solar power planning and development. [ABSTRACT FROM AUTHOR]

• Shape interpolations between four common front shape extrema of the Energy-saving Chinese Solar Greenhouse (ECSG) were studied. • Two kinds of optimal ECSG shapes were identified in this study. • PCA analysis were conducted to determine the optimal greenhouse construction parameters. • The proposed model framework allows the investigation of the effects of different shape variations of solar greenhouses for any arbitrary latitude. Determining the optimal shape for greenhouses that is suitable for cold northern regions is essential for non-seasonal fruit production. In the present study, a structural model was developed for energy-saving Chinese solar greenhouses (ECSG), which combines a greenhouse energy balance model with a detailed shape analysis. All possible greenhouse shape interpolations within four common front shape extrema were systematically analysed to determine an optimal ECSG shape with a maximal energy performance for use during winter. The analysis revealed a direct relationship between the interception of solar radiation in the greenhouse and the height of the ridge. Our results indicated that the flatter the curve of the front cover, the more radiation is intercepted by the ground and north wall of the greenhouse. As a result, compared to the commonly used greenhouse type, two types of optimal ECSG shapes were identified, each attaining an increase of 2°C in the minimum night temperature. The general model framework developed in this study allows the investigation of the effects of different variations in the many small detailed interpolation shapes of ECSGs for any arbitrary latitude which can be used directly to provide guidance for the construction of a new generation of energy-efficient solar greenhouses. Also, with the interpolation method proposed in this paper, large-scale shape statistical analysis now can be performed to help qualified decision-making during the process of greenhouse construction. [ABSTRACT FROM AUTHOR]

• Investigated strategies that can deliver NZE performance for high-rise residential buildings in Australia. • It was challenging for tropical, subtropical and cold temperate climates to meet the NZE targets. • Design and optimisation of the envelope was effective in overcoming the challenges imposed by the more demanding climates. • The impacts of shading from neighbouring buildings presented the largest obstacle to energy production through the façade. • Study demonstrated a need to include density factors in the design consideration for NZE high-rise residential designs. Net-Zero Energy (NZE) buildings are gaining popularity globally as a solution to reduce operational energy usage and limit greenhouse gas emissions in the building industry. Their deployment is occurring rapidly as many countries are planning to make it mandatory for new developments. Despite the advancements in research in the various aspects of NZE, significant barriers do exist to its successful adoption and implementation, particularly with respect to high-rise residential buildings which are becoming a major portion of the housing supply in Australia. One of the challenges attributed to the achievement of NZEB performance is the uncertainty involved in selecting appropriate solution strategies that could deliver quality performances. This paper investigated strategies that can deliver NZE performance for high-rise residential buildings in Australia. A calibrated model of 26 storey high-rise apartment building with 396 units was prepared for detailed analysis of NZE strategies using building simulation. The impact of various interventions was evaluated across cities in five climate zones in Australia and a guideline for solution sets that can deliver the goal for each climate zone is presented. The findings show that NZE performance for high-rise residential buildings can be realised in Australia, albeit with some limitations. While the tropical, subtropical and cold temperate climates appear to be more challenging, proper design and optimisation of the envelope proved to be effective in overcoming the challenges imposed by the more demanding climates. The impacts of shading from neighbouring buildings and objects presented the largest impediment to energy production through the façade. [ABSTRACT FROM AUTHOR]

Urban heat island and global warming increase the urban ambient temperature. Increased temperatures have a tremendous effect on the energy demand for cooling, with a great impact on peak and total electricity demand. Renewable technologies in the urban environment have been widely regarded as an increasingly important solution to deal with the climate change challenges and energy security. Significant effort is performed in the integration of photovoltaic panels (PV) and micro turbines in the urban context showing a substantial reduction in CO 2 emissions. At the same time attention is drawn to an often-overlooked aspect regarding renewable energy technologies, in that despite having low operating costs their overall benefits are often not well understood and consequently are often evaluated as being less profitable than fossil fuel alternatives, even though they are future proof about energy cost. The aim of the present paper is to describe the role of renewable energy technologies and zero carbon technologies in covering the future increased energy demand for cooling. The integration of photovoltaics in the urban environment through PV facades, pavements, and shading devices are discussed. The role of Information and Computer Technology and smart grids in the efficient management of renewables in urban scale is discussed. The role of smart metering, users ‘integration and demand response capabilities for future zero energy urban neighborhoods is revealed. [ABSTRACT FROM AUTHOR]

This paper concerns development and analysis of a solar-wind hybrid multigeneration system. Energy, exergy, exergoeconomic and exergoenvironmental analyses are performed. The analysis studies are undertaken by developing and constructing the codes in Engineering Equation Solver software. The effects of various input conditions on the system performance are investigated through both energy and exergy efficiencies, and an optimization study is undertaken of system efficiency and power output are obtained. The average number of Toronto suites that the system can supply is calculated. As a result, it is seen that energy and exergy efficiencies are higher than equivalent single energy systems. The system has 43% maximum energy efficiency and 65% maximum exergy efficiency. Maximum turbine output is 48 kW, while cooling effect is 28 kW and heating effect is 298.5 kW. There is resultant savings of 1614 tons of CO 2 per year by the system. This multigeneration system is capable of supplying at least at a minimum 49 suites. [ABSTRACT FROM AUTHOR]

Renewable hybrid systems with small capacities are widely installed for joining demand response in modern communities. Based on hybrid systems, renewable energy generation can be stored and used for power supply during peak load period. It is impractical to control power flow in such small-scale systems, because power flow dispatching asks for extra investment of expensive regulators and adaptors. In this paper, a switching grid connected photovoltaic system is studied for simplifying system installation. Optimal switching control model is proposed to sufficiently utilize the solar energy and to minimize electricity cost under the time-of-use program. As shown in results, optimal scheduling of the PV system can achieve promising cost savings. [ABSTRACT FROM AUTHOR]