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This work addresses the problem of energy consumption time series forecasting. In our approach, a set of time series containing energy consumption data is used to train a single, parameterised prediction model that can be used to predict future values for all the input time series. As a result, the proposed method is able to learn the common behaviour of all time series in the set (i.e., a fingerprint) and use this knowledge to perform the prediction task, and to explain this common behaviour as an algebraic formula. To that end, we use symbolic regression methods trained with both single- and multi-objective algorithms. Experimental results validate this approach to learn and model shared properties of different time series, which can then be used to obtain a generalised regression model encapsulating the global behaviour of different energy consumption time series.

High reactivity coke is beneficial for achieving low carbon emission blast furnace ironmaking. Therefore, the preparation of highly reactive ferro-coke has aroused widespread attention. However, the effects of the particle size of iron ore on the pyrolysis behaviour of a coal-iron ore briquette are still unclear. In this study, the effect of three particle sizes (0.50–1.00 mm, 0.25–0.50 mm and <0.74 mm) of iron ore on the thermal and kinetic behaviours of coal-iron ore briquettes were investigated by non-isothermal kinetic analysis. The results showed that the synergistic effect of iron ore and coal during coking mainly occurred during the later reaction stage (850–1100 °C) and smaller particle sizes of iron ore have a stronger synergistic effect. The addition of iron ore had little effect on T0 (the initial temperature) and Tp (the temperature at the maximum conversion rate) of briquette pyrolysis, however itgreatly affected the conversion rate and Tf (the final temperature) of the briquettes. T0 decreased with the decrease of iron ore particle sizes, while Tp and Tf showed opposite trends. After adding iron ore into the coal briquette, the reaction kinetics at all stages of the coal-iron ore briquettes changed. The weighted apparent activation energy of the caking coal (JM) briquette was 35.532 kJ/mol, which is lower than that of the coal-iron ore briquettes (38.703–55.627 kJ/mol). In addition, the weighted apparent activation energy gradually increased with decreasing iron ore particle sizes.

The electro-hydraulic servo pump control system (EHSPCS) is a volume control system that uses a permanent magnet synchronous motor (PMSM) with a fixed displacement pump to directly drive and control the hydraulic cylinder. The energy transmission law of the system is very complicated due to the transformation of electrical, mechanical and hydraulic energy as well as other energy fields, and qualitative analysis of the energy transfer efficiency is difficult. Energy transfer analysis of the EHSPCS under different working conditions and loads is proposed in this paper. First, the energy flow transfer mechanism was analyzed, and the mathematical and energy transfer models of the key components of the system were established to explore the energy characteristic state transition rule. Second, a power bond diagram model was built, its state equation and state matrix were deduced, and a system simulation model was built. Finally, combined with the EHSPCS experimental platform, simulation experiments were carried out on the dynamic position following and steady-state position holding conditions of the system, and the variation rules of the power of each energy characteristic state and the system energy transfer efficiency under different loads were obtained. The research results provide a foundation for the study of power matching and energy-saving mechanism of the EHSPCS.

Car-sharing services are developing at an ever-increasing pace. Taking into account the reduction of carbon dioxide emissions and pursuit of the sustainable development of transport, implementing electric cars in car-sharing fleets is being proposed. On the one hand, these types of vehicles are referred to as emission-free, but on the other hand, their environmental friendliness is questionable due to the emission of carbon dioxide during the production of energy to power them. Although many scientific papers are devoted to the issue of reducing emissions through car sharing, there is a research gap concerning the real production of carbon dioxide by car-sharing vehicles during car-sharing trips. To fill this research gap, the objective of the article was to analyze the actual level of carbon dioxide emissions from combustion and electric vehicles from car-sharing systems produced when renting rides. The test results showed that the electric car turned out to be significantly less emitting. The use of electric vehicles in car-sharing fleets can reduce carbon dioxide emissions from 14% to 65% compared to using cars with internal combustion engines. However, the key role during car-sharing trips is played by the driving style of the drivers, which has been omitted from the literature to date. This should be properly regulated by service providers and focus on the proper use of energy from electric vehicle batteries, especially at low temperatures. The article provides support for operators planning to modernize their fleet of vehicles and fills the research gap concerning car-sharing emissions.

The contaminant-insensitive sublimator (CIS) is a novel water sublimator in development, which uses two porous substrates to separate the sublimation point from the pressure-control point and provide long-life effective cooling for spacecraft. Many essential studies need to be carried out in the field. To overcome the reliability issues such as ice breakthrough caused by large temperature or pressure differences, the CIS development unit model, the mathematical models of heat and mass transfer and the evaluation coefficient have been established. Numerical investigations have been implemented aiming at the impacts of physical properties of porous substrate, physical properties of working fluid, orifice layouts and orifice-structure parameters on the characteristics of flow field and temperature field. The numerical investigation shows some valuable conclusion, such as the temperature uniformity coefficient at the bottom surface of the large pore substrate is 0.997669 and the pressure uniformity coefficient at the same surface is 0.85361267. These numerical results can provide structure and data reference for the CIS design of lunar probe or spacesuit.

As renewable energies become the main direction of global energy development in the future, Virtual Power Plant (VPP) becomes a regional multi-energy aggregation model for large-scale integration of distributed generation into the power grid. It also provides an important way for distributed energy resources (DER) to participate in electricity market transactions. Firstly, the basic concept of VPP is outlined, and various uncertainties within VPP are modeled. Secondly, using multi-agent technology and Stackelberg dynamic game theory, a double-layer nested dynamic game bidding model including VPP and its internal DERs is designed. The lower layer is a bidding game for VPP internal market including DER. VPP is the leader and each DER is a subagent that acts as a follower to maximize its profit. Each subagent uses the particle swarm algorithm (PSA) to determine the optimal offer coefficient, and VPP carries out internal market clearing with the minimum variance of unit profit according to the quoting results. Then, the subagents renew the game to update the bidding strategy based on the outcomes of the external and internal markets. The upper layer is the external market bidding game. The trading center (TC) is the leader and VPP is the agent and the follower. The game is played with the goal of maximum self-interest. The agent uses genetic algorithms to determine the optimal bid strategy, and the TC carries out market clearance with the goal of maximizing social benefits according to the quotation results. Each agent renews the game to update the bidding strategy based on the clearing result and the reporting of the subagents. The dynamic game is repeated until the optimal equilibrium solution is obtained. Finally, the effectiveness of the model is verified by taking the IEEE30-bus system as an example.

Deep water shallow natural gas hydrate (NGH) is a kind of clean energy and has entered the commercial exploitation stage. However, it produces a lot of seabed sediment in the process of large-scale mining, which not only easily causes undersea natural hazards, but also leads to pipeline equipment blockage and high energy consumption in the mining process. A downhole solid–liquid separator can effectively separate natural gas hydrate from sand and backfill sand in situ, which can effectively solve this problem. In this paper, the safety of a downhole solid–liquid separator desander under torsion conditions is determined by a test method. A numerical simulation method was used to simulate the tension and pressure of the downhole solid–liquid separator, and a modal simulation analysis and erosion analysis of the downhole solid–liquid separator were carried out. The experiments showed that the downhole solid–liquid separator could withstand 30 KN/m of torque, and a numerical simulation analysis showed that it could withstand 30 MPa of pressure and 50 KN of tension. The results show that the maximum stress is 116.56 MPa, and the maximum allowable stress is 235 MPa. The modal analysis showed that the downhole solid–liquid separator produces resonance at a frequency of about 93 Hz, resulting in large deformation, which should be avoided as far as possible. Through the erosion analysis, the life of the downhole solid–liquid separator was determined to be about 2.3 years. Numerical simulation and experimental results show that the designed downhole solid–liquid separator for natural gas hydrate can ensure safety.