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AbstractShipbuilding is an energy-intensive industrial sector that produces a significant amount of waste, pollution and air emissions. However, the International Maritime Organization concentrates only on reducing emissions during the operational phase. In order to completely phase out emissions from the shipping industry, a life-cycle approach must be taken. The study implemented the proposed transdisciplinary energy management framework in a Bangladeshi shipyard. The framework aims to support shipyard decision makers in making rational and optimized decisions to make shipyards sustainable, while maintaining good product quality and reducing relative cost. This is achieved by applying the Fuzzy Analytical Hierarchy Process and Fuzzy Order of Preference by Similarity to Ideal Solution methods to identify optimal solutions. In addition to making shipyards more sustainable, the framework can enhance both the business and socio-economic prospects of the shipyard and promote the reputation of the shipyard and improve its competitiveness and, in line with this, lead to the promotion of nationally determined contributions under the Paris Agreement for States. The implementation of the framework shows that the political and legal discipline, the social criteria and the implementation of ISO 14001 and cyber security were the most important criteria and options for the yard's decision makers.

The hydraulic balance of heating network is considered as a pre-condition for the implementation of low temperature district heating (LTDH). Its imbalance result into high energy consumption and heat-losses in the network. In this study, a novel hydraulic model is presented which investigates hydraulic imbalance in the LTDH network, using real weather and hourly monitored operational heating data from an existing boiler based building. Analysis of delta t in space-heating system shows that the delta t is maximum when the outside air temperature is lowest and it decreases with increase in outside air temperature. Furthermore, the hydraulic imbalance is analysed for four different control scenarios with the aim to find an optimum scenario with minimum pumping power, energy consumption and heat-losses in the LTDH network. Results show that the hydraulic imbalance is due to the absence of flow-limiters and balancing valves on the return pipe and thermostatic radiator valves (TRVs) alone are unable to maintain hydraulic balance in the space-heating system of buildings. Moreover, the control scenario with variable flow-rate and fixed supply water temperature from the sub-station is found to be optimum. Compared to the constant flow-rate scenario, the pumping power, energy consumption and heat-losses in the LTDH network are reduced by approximately 2%, 63% and 14%, respectively.

The wind power forecasting error restricts the benefit of the wind farm in the electricity market. Considering the cooperation of wind power bidding and energy storage system (ESS) operation with uncertainty, this paper proposes a coordinated bidding/operation model for the wind farm to improve its benefits in the electricity market. The maximum entropy based deep reinforcement learning (RL) algorithm, Soft Actor-Critic (SAC) is used to construct the model. The maximum entropy framework enables the designed agent to explore various optimal possibilities, which means the learned coordinated bidding/operation strategy is more stable considering the forecasting error. Particularly, penalty terms are introduced into the benefit function to relax the constraints and improve the convergency. The case study illustrates that the learned policy can effectively improve the wind farm benefit while ensuring robustness.

Abstract The consumption of takeaway food is increasing worldwide. Single-use containers used for takeaway food represent a significant source of waste and environmental impacts due to their low recyclability. Consequently, it is important to identify the best available alternatives and improvement opportunities to reduce the environmental impacts of fast-food containers. For these purposes, this study estimates and compares for the first time the life cycle impacts of three most widely-used types of takeaway container: aluminium, polypropylene and extruded polystyrene. These are also compared to reusable polypropylene containers. The findings suggest that single-use polypropylene containers are the worst option for seven out of 12 impacts considered, including global warming potential. They are followed by the aluminium alternative with five highest impacts, including depletion of ozone layer and human toxicity. Overall, extruded polystyrene containers have the lowest impacts due to the lower material and electricity requirements in their manufacture. They are also the best option when compared to reused takeaway polypropylene containers, unless the latter are reused 3–39 times. The number of uses needed for the reusable “Tupperware” polypropylene food savers is even higher, ranging from 16 to 208 times, with terrestrial ecotoxicity being always higher than for extruded polystyrene, regardless of the number of uses. However, extruded polystyrene containers are currently not recycled and cannot be considered a sustainable option. If they were recycled in accordance with the European Union 2025 policy on waste packaging, most of their impacts would be reduced by >18%, while also reducing littering and negative effects on marine organisms. Most of the impacts of the other two types of container would also be reduced (>20%) through increased recycling. Implementing the European Union 2025 policy on recycling of waste packaging would reduce all the impacts by 2%–60%, including a 33% reduction in global warming potential. Based on 2025 million takeaway containers used annually in the European Union, the latter would save 61,700 t CO2 eq./yr, equivalent to the emissions of 55,000 light-duty vehicles. The outcomes of this study will be of interest to packaging manufacturers, food outlets, policy makers and consumers.

The successful electricity grid integration of solar energy into day-ahead markets requires at least hourly resolved 48 h forecasts. Technologies as photovoltaics and non-concentrating solar thermal technologies make use of global horizontal irradiance (GHI) forecasts, while all concentrating technologies both from the photovoltaic and the thermal sector require direct normal irradiances (DNI). The European Centre for Medium-Range Weather Forecasts (ECMWF) has recently changed towards providing direct as well as global irradiances. Additionally, the MACC (Monitoring Atmospheric Composition & Climate) near-real time services provide daily analysis and forecasts of aerosol properties in preparation of the upcoming European Copernicus programme. The operational ECMWF/IFS (Integrated Forecast System) forecast system will in the medium term profit from the Copernicus service aerosol forecasts. Therefore, within the MACC‑II project specific experiment runs were performed allowing for the assessment of the performance gain of these potential future capabilities. Also the potential impact of providing forecasts with hourly output resolution compared to three-hourly resolved forecasts is investigated. The inclusion of the new aerosol climatology in October 2003 improved both the GHI and DNI forecasts remarkably, while the change towards a new radiation scheme in 2007 only had minor and partly even unfavourable impacts on the performance indicators. For GHI, larger RMSE (root mean square error) values are found for broken/overcast conditions than for scattered cloud fields. For DNI, the findings are opposite with larger RMSE values for scattered clouds compared to overcast/broken cloud situations. The introduction of direct irradiances as an output parameter in the operational IFS version has not resulted in a general performance improvement with respect to biases and RMSE compared to the widely used Skartveit et al. (1998) global to direct irradiance conversion scheme. Cloudy situations and especially thin ice cloud cases are forecasted much better with respect to biases and RMSE, but large biases are introduced in clear sky cases. When applying the MACC aerosol scheme to include aerosol direct effects, an improvement especially in DNI biases is found for cloud free cases as expected. However, a performance decrease is found for water cloud cases. It is assumed that this is caused by the lack of an explicit modelling of cloud-aerosol interactions, while other meteorological forcings for cloud processes like the temperature field are modified by the aerosols.

A new sizing approach is applied in this paper to stand-alone PV systems design, which is based on systems configurations without shedding load. The investigation is based on a detailed study of the minimum storage requirement and an analysis of the sizing curves. The analysis reveals the importance of using daily series of measured solar radiation data instead of monthly average values. For high-reliability systems, it is important that these data series are as long as possible, while the configuration of large generator and small battery seems to deal better with the unpredictability of solar radiation.

With the continuous development of intelligent transportation technologies, new ways of energy usage in transportation continue to emerge, which puts forward new requirements for the planning and design of energy systems. However, comprehensive analyses on the characteristics of transportation energy systems and the development trend of energy usage patterns brought by intelligent technologies have rarely been carried out so far. This paper explores this subject by reviewing the recent development and utilization of intelligent technologies in the transportation system and its impacts on energy usage. This review is carried out from three aspects, covering the representative intelligent transportation and energy technologies on vehicles, infrastructures and systems. The scope is limited within road, railway and water transport domains, with a focus on the recent developments in China as a representative. In terms of vehicles, the development trend of the power systems for new energy vehicles, the characteristics of energy usages in electric vehicles and the effects on energy saving and emission reduction are summarized. In terms of infrastructures, new technologies on smart road, smart port, intelligent railway energy system and the usage of clear energy on electric grid for transportation are reviewed, with the consideration of their potential influences on energy usages and the energy consumption characteristics of typical facilities also being analyzed. As for the transportation system, this review has focused on intelligent and connected transportation systems, train control and autonomous systems, and intelligent shipping system, with the emphasis on the energy saving and emission reduction effects of applying these intelligent technologies. The overall development trend of the transportation energy system is then analyzed based on the above materials, in particular, the future energy usage patterns in transportation system are given and the major challenges and obstacles approaching the future scenarios are also identified.

AbstractThe integration of power plants and desalination systems has attracted increasing attention over the past few years as an effective solution to tackle sustainable development and climate change issues. In this light, this paper introduces a novel modelling and optimization approach for a combined-cycle power plant (CCPP) integrated with reverse osmosis (RO) and multi-effect distillation (MED) desalination systems. The integrated CCPP and RO–MED desalination system is thermodynamically modelled utilizing MATLAB and EES software environments, and the results are validated via Thermoflex software simulations. Comprehensive energy, exergic, exergoeconomic, and exergoenvironmental (4E) analyses are performed to assess the performance of the integrated system. Furthermore, a new multi-objective water cycle algorithm (MOWCA) is implemented to optimize the main performance parameters of the integrated system. Finally, a real-world case study is performed based on Iran's Shahid Salimi Neka power plant. The results reveal that the system exergy efficiency is increased from 8.4 to 51.1% through the proposed MOWCA approach, and the energy and freshwater costs are reduced by 8.4% and 29.4%, respectively. The latter results correspond to an environmental impact reduction of 14.2% and 33.5%. Hence, the objective functions are improved from all exergic, exergoeconomic, and exergoenvironmental perspectives, proving the approach to be a valuable tool towards implementing more sustainable combined power plants and desalination systems.