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The train generates regenerative braking energy (RBE) during braking. When the RBE generated by the braking train is too large to be absorbed and utilized, the OCS voltage will rise rapidly. It may even exceed the rated voltage threshold, resulting in hidden dangers for driving safety. How to use RBE efficiently and reasonably has become a hot issue in recent years. This paper presents a metro timetable optimization method for multi-train operation to improve the RBE utilization efficiency of trains. Firstly, an energy-saving multi-objective model for multi-train operation is established, which takes the total energy consumption and travel time as the objective functions and the dwell time and departure interval as the constraints. Then, the genetic algorithm (GA) is used to generate the composition sequence of dwell time and departure interval, and the multi-node nonlinear model is used to calculate the total energy consumption of the metro line. Finally, Guangzhou metro line 7 is selected as an example to illustrate the effectiveness of the developed optimization model. The results show that the energy consumption of the whole line can be effectively reduced by adjusting the dwell time and departure interval. Meanwhile, the timetable optimization model with GA has better energy-saving effects by comparative analysis. • A metro timetable optimization method based on improved genetic algorithm is developed. • The multi-node nonlinear model is developed to calculate the total energy consumption. • The developed optimization model has better energy-saving effects than previous methods. [ABSTRACT FROM AUTHOR]

The inefficient operation of cooling equipment is a significant impact factor to the high energy consumption of cooling system in data center. This study proposes an advanced model predictive control (MPC) strategy for a hybrid cooling with water storage system to improve energy efficiency and reduce the accumulation of cold storage losses. Mixed integer linear programming (MILP) in MPC strategy is used to optimize the operating parameters under free cooling, hybrid cooling, and mechanical cooling modes, further solving the problem of precise optimization for different modes. Taking Guangzhou city as an example, the equipment scheduling and the appropriate volume of cold water storage tank for MPC strategy are analyzed. The results indicate that, the emergency cold water storage tank 500 m3 only supports the efficient operation of cooling system under the maximum 60 % IT load rate, meanwhile, the optimal tank volume 1400 m3 could meet the 60–100 % IT load rate. Compared to Baseline strategy, the biggest reduction of annual energy consumption using MPC strategy would be attained by 12.19 % under free cooling mode, by 4.04 % under hybrid cooling mode, and by 22.15 % under mechanical cooling conditions at the 55 % IT load rate. Therefore, the MPC strategy proposed in this paper has important guiding significance for energy conservation and carbon reduction in global data centers. • A novel advanced MPC strategy and MILP solver is developed for hybrid cooling system of data center. • The energy consumption of MPC strategy decreases by 12.19 % under free cooling mode at 55 % IT load. • The relationship between the water tank volume and IT load rate under MPC strategy is studied. [ABSTRACT FROM AUTHOR]

The energy crisis caused by climate change is the most significant challenge of the 21st century. Single-objective and multi-objective optimization studies for buildings often only consider the building itself, without considering the impacts of climate change. However, in the future, energy-efficient design and appropriate operating parameters will be crucial considerations in the face of global climate change. This paper aims to discuss the impact of climate change in the humid-hot region over the past 60 years on the energy consumption of office buildings and propose countermeasures. Firstly, the meteorological data of Guangzhou from 1960 to 2020 is statistically analyzed, and four typical meteorological years and corresponding air conditioning design days are established. Secondly, Energyplus is used to simulate the building's energy consumption, and the energy consumption factors are analyzed for sensitivity using jEplus. Finally, a multi-objective optimization is performed using jEPlus + EA with the Non-dominated Sorting Genetic Algorithm (NSGA-II). The results found that climate change led to a significant increase in the duration of high outdoor temperatures during summer. Specifically, the daily dry-bulb temperature for air conditioning design increased by 0.4–0.7 °C, and due to climate change, the energy consumption of the office building increased by about 4.6 %. The main factor affecting the cooling energy consumption in summer was the indoor cooling set point (8.29%–30%), infiltration air volume (1.0%–8.6%), fresh air volume (3.2%–16.06%), the glazing solar transmission rate (1.25%–9.0%), building orientation (0%–1.43%), and relatively small influence of envelope insulation performance. The operation scheme determined by multi-objective optimization can reduce the cooling energy consumption of the building by 10.6%–16.8%, which can mitigate the rise in energy consumption resulting from climate change to a greater extent. [Display omitted] • Discuss the impact of climate change over the past 60 years on the energy consumption of office buildings. • There was a significant increase in the duration of high outdoor temperatures during the summer. • Multi-objective optimization is performed using jEPlus + EA. • Climate change caused energy consumption to increase by about 4.6 %. • Optimal solutions can reduce the cooling energy consumption of the building by 10.6%–16.8%. [ABSTRACT FROM AUTHOR]

Natural cooling energy and high-efficient radiant cooling techniques are essential to mitigate energy resources shortage crisis, breakthrough on traditional convective air-conditioning systems in isolation between indoor and outdoor environment with high indoor air quality. In this paper, a polyethylene aerogel (PEA) and phase change material (PCM) integrated novel Trombe wall was proposed, involving natural cooling energy harvesting, cooling energy storage, indoor ventilation and radiant cooling. A two-dimensional unsteady numerical model based on surface-to surface (S2S) radiation model and effective specific heat capacity method was developed in the commercial software Ansys Fluent to evaluate the cooling performance and dynamic heat-transfer mechanism of the novel Trombe wall. Subsequently, climate-responsive operation strategies on ventilation modes were proposed to maximize natural cooling energy utilization and fresh air supply. Parametrical and comparative studies were conducted on optimal structural design and robust operation. Our results showed that, with the novel design and advanced operation strategies, passive cooling capacity of 0.64 kWh/m2·day can be provided, together with fresh air supply of 2705.2 kg/day (1.4 m2 Trombe wall), corresponding to air change rate per hour (ACH) of 1.15. In terms of active cooling system, the integration of PEA and PCM can effectively prevent moisture condensation and shift peak cooling load. Hence, radiant cooling capacity of 0.99 kWh/m2·day and radiant cooling ratio of 47 % can be achieved by the novel Trombe wall, with electricity consumption only at valley period. Moreover, economic saving of 55.0 CNY/day and decarbonization potential of 23.8 kg CO 2,e /day can be achieved when the novel Trombe wall is integrated into a typical office building in subtropical climate Guangzhou. This study provides a novel structural design and optimal operation strategies on a Trombe wall, together with guidelines on techno-economic-environmental performance improvement, promoting effective natural cooling energy utilization and energy-flexible/efficient radiant cooling for decarbonization of buildings in cooling-dominant regions. • A novel Trombe wall for natural cooling energy harvesting and radiant cooling. • An unsteady numerical model for thermodynamic analysis. • Passive cooling capacity of 0.64 kWh/m2.day and fresh air supply of 2705.2 kg/day. • Radiant cooling capacity of 0.99 kWh/m2·day and radiant cooling ratio of 47 %. • Daily CO 2 reduction of 23.8 kg and economic saving of 55.0 CNY in a typical office building. [ABSTRACT FROM AUTHOR]