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This study proposes a distributed load restoration method to effectively model and solve the load restoration problem of integrated power distribution and natural gas systems (IDGSs) after faults for resilient operation. The IDGS load restoration problem is devised as a mixed-integer second-order cone programming (MISOCP) model to minimize the total load loss cost of IDGS. This model considers distribution network reconfiguration and the coupling effect between the power distribution system (PDS) and natural gas system (NGS). Moreover, a bidirectional gas flow model is used to offer more flexibility for load restoration when the NGS is faulty. By considering the independent management and information privacy of each energy subsystem, the proposed model is solved using an alternating direction method of multipliers (ADMM) algorithm in a distributed manner. Furthermore, an adaptive-ADMM algorithm is used for convergence acceleration. Finally, numerical studies are conducted to validate the proposed methods effectiveness.

This paper proposes a distributed energy management for active distribution network (ADN) considering aggregated office buildings. It aims to dispatch the flexible resources of office buildings to actively participate in the optimization of the ADN. Firstly, by considering the comfortable indoor temperature range and travel habits of workers, an optimal operation model for the office building with integrated heating ventilation and air conditioning (HVAC) systems and electric vehicle (EV) charging piles is constructed. Secondly, based on the piecewise linearization and second-order cone relaxation (SOCR), an ADN optimization model with aggregated office buildings is formulated and converted into a mixed-integer second-order cone programming (MISOCP) model. Then, considering the private information protection, the alternating direction method of multipliers (ADMM) is used to solve the ADN optimization model to realize the distributed energy management of the ADN with aggregated office buildings. Finally, the scheduling results of the ADN optimization model under different comfortable indoor temperatures and control methods of EVs are analyzed in the winter heating scenario. Numerical results show that the proposed method can increase the penetration of distributed photovoltaic (PV) generation and decrease losses of the distribution network while ensuring the temperature and travel demands of workers in office buildings. The information privacy of each district can also be protected with the proposed method.

In this paper, a regret-based risk-averse stochastic production task and energy management (PTEM) model for industrial microgrid is proposed, which is applied to a battery manufacturing plant (BMP) microgrid. We incorporate production task scheduling with production constraints in the energy management of industrial microgrid. The general PTEM of industrial microgrids is analyzed and the production processes and energy requirements of a BMP multi-energy microgrid prosumer are presented, in which thermostatically controlled loads (TCLs) in buildings are considered. Then, the regret-based risk-averse PTEM model is formulated as a mixed-integer linear programming (MILP) problem based on stochastic programming considering uncertainties of day-ahead electricity market price and photovoltaic (PV) power output. Conditional value-at-risk (CVaR) is introduced for risk control and utilized for minimizing the expected regret. Numerical studies are carried out to validate the proposed model by comparing with risk-neutral approach and deterministic model based on real market prices from PJM electricity market. The results show that the proposed PTEM approach is effectively risk-averse. In addition, the impacts of total target production task and risk-control parameter on expected cost and regret are analyzed.

Bean curd dreg (BCD) is a by-product of bean products, which can be used as a great ingredient for composting, but it combined with cow manure and corn stalk composting was rarely reported. In this study, the effect of BCD on the maturity and the micro-ecological environment was investigated under a lab-scale composting experiment and found that BCD was conducive to improve the maturity of compost during the BCD application. The excitation-emission matrix (EEM) showed that the final humus content in BCD treatments was richer than that in CK treatment. High-throughput sequencing results showed that BCD-applied better ameliorated the bacteria community structure with higher Actinomycetes abundance and lower denitrifying bacteria abundance in the late stage of composting. PICRUSt results showed that BCD-added decreased the abundance of microbial metabolic genes in the high temperature period (> 70 °C), but the metabolic abundance increased rapidly as the temperature cooled down. Compared with CK, the metabolic abundance decreased significantly on day 24, which was consistent with the conclusion of composting maturity. Redundancy analysis (RDA) results indicated that there were significant discrepancies in the microbial community structure of samples at different composting periods and the change of the dominant population in the BCD-treated compost samples were more outstanding than that in the CK treatment. Hence, BCD is a very good composting modifier that compensates for the disadvantages of composting and enhances the fertility of the compost product.

Power-to-gas (P2G) and gas-fired generation units (GFGUs) enable the bidirectional energy flow of integrated energy systems (IESs). The static security of IES should be analysed considering the interdependence between energy systems. In this study, the static security of IES is analysed, and a novel static security control strategy to improve the security of IES after N−1 contingency is proposed considering P2G. First, electricity–gas IES model is presented, and the multi-energy flow of IES is solved by the Newton–Raphson method. Then, N − 1 static security analysis is carried out for the electricity system and natural gas system. Based on the obtained Jacobian matrix during the energy flow calculation process after N − 1 contingency, variable sensitivity matrixes of voltage, gas pressure, branch power flow and pipeline flow to control variables are derived. Furthermore, a static security control strategy for IES based on the sensitivity matrices is developed to regulate operation statuses of P2G and GFGU and compressor outlet pressure to mitigate the violation of security constraints. The performance of the proposed analysis method and control strategy is evaluated by IES 4-12 and IES 118-48 test systems. The results demonstrate that the proposed control strategy can mitigate security risks of IES after N − 1 contingencies.

Coordinated operation of integrated electricity and district heating system (IEDHS) has great potential to enhance the flexibility of the power system to cope with the wind power curtailment. This study proposes an interval optimal scheduling algorithm for IEDHSs, considering the dynamic characteristics of the heating network. The model of the district heating system with dynamic characteristics including transmission delay and heat losses, is established in detail, and the uncertainties of both wind power and electricity and heating loads are described with interval numbers. Then an interval optimal scheduling model of the IEDHS is formulated to minimise the IEDHS operation cost. The impacts of the transmission delay and heat losses of the heating network on the scheduling of the IEDHS are analysed. Case studies are performed on the PJM 5-bus electricity system with a 6-node district heating system and IEEE 39-bus electricity system with a 12-node district heating system to evaluate the effectiveness of the proposed model. The results demonstrate that the dynamic characteristics of the heating network can integrate more wind power and enlarge the width of the cost interval.

Aiming to achieve the flexible operation of distribution network (ADN), an energy management strategy of ADN with integrated distributed wind power and smart buildings is proposed in this study. First, based on the thermal storage characteristics of buildings, the resistor–capacitor model is used to develop an energy consumption prediction model of smart buildings. Second, the smart buildings are modelled as flexible resources of ADN. A multi-objective ADN model is further formulated based on analytic hierarchy process (AHP) by comprehensively considering constraints of power grid and smart buildings. Then, the unified model of ADN is transformed by second-order conic relaxation to guarantee the global optimal solution. Finally, the scheduling results for the unified model of ADN under different control methods for heating ventilation and air-conditioning (HVAC) systems are compared in the winter heating scenario. In addition, the impact of the demand response capability for smart buildings on the economic and secure operation of the ADN is further analysed. Numerical studies demonstrate that the proposed method can increase the penetration of local wind power, reduce peak-valley load difference and network loss of the grid while ensuring the comfort temperature of customers, and further achieve the flexible operation of ADN.

The application of boron in fuel-rich solid propellant is limited by its long combustion time, ignition delay and low combustion efficiency. To overcome these problems, B/Nitrocellulose (NC)/Fe particles were fabricated by electrospraying. The reactivity and combustion behavior of B/NC/Fe particles were characterized by TG/DSC, oxygen bomb calorimeter and laser ignition. Compared with pure boron, lower oxidation temperature was observed in the thermal analysis of prepared particles. Meanwhile, the prepared particles released more heat and ignite more readily during the combustion. Furthermore, B/NC/Fe particles were added into Hydroxyl-terminated polybutadiene (HTPB)/Ammonium perchlorate (AP) propellants as additives to test their combustion performance. The burning rate of propellants in air and closed bomb were both improved by 8.20% and 117%, respectively. Overall, B/NC/Fe particles not only show the superior reaction performance, but also contribute to the tunable burning rate of propellants.

This paper proposes an adjustable robust power dispatch (ARPD) model under low-carbon economy to accommodate the uncertainty of wind power with combined wind-storage system (CWSS) and carbon capture power plants (CCPPs). First, battery energy storage (BES), which is considered as adjustable under worst-case scenarios, is introduced to wind power plants to form a combined wind storage system structure to improve operation flexibility. Then, a dispatching model of CCPPs is presented and analysed. The operating characteristics of CCPPs make it possible to control net power outputs and carbon emissions independently and flexibly. The integration of BES and carbon capture and storage (CCS) improves the operation flexibility of both wind power plants and conventional power plants. The objective function of the proposed model under interval-uncertain wind power is to minimize the total cost under the worst wind power output case and the context of low-carbon economy. The proposed model is implemented on the modified PJM 5-bus system with one wind farm and the IEEE-118 bus system with five wind farms. Numerical results demonstrate that the proposed model is effective at reducing carbon emissions and wind power curtailment, and verify that as the number of CCPPs increases, the overall costs come down.

To provide a theoretical basis for improving the thermal safety of spent acid, its decomposition behaviour was studied. A mixed solution of n-propyl nitrate (NPN) and nitric acid was analysed using isoperibolic experiments and differential scanning calorimetry. An accurate kinetic model based on the analysis was proposed to describe the decomposition of the spent acid by applying an isoconversional method and nonlinear regression to the DSC data. We found that the thermal decomposition in the mixed solution involved two competing reactions: the decomposition of NPN in the nitric acid solution and the decomposition of nitric acid. The decomposition of the mixed solution followed a 0.9082th Prout–Tompkins equation with autocatalysis, with a differential kinetic mechanism function of f(α) = (1 − α)0.9082·α0.1291. Lastly, the thermal safety evaluation and thermodynamic parameters were studied. The self-accelerating decomposition temperature and the critical temperature of thermal runway were 338.70 K and 346.76 K, respectively, in an approximately closed system, and 347.25 K and 355.73 K, respectively, in an open system. These results show that the spent acid was more hazardous than the NPN and nitric acid solution. In addition, the thermal stability of the mixed solution in an open system was higher than that of the mixed solution in an approximately closed system.

In order to understand better thermal safety of the nitrolysis solution from the nitration of hexamethylenetetramine, its decomposition behavior was studied. The nitrolysis solution prepared was analyzed using isoperibolic experiments, differential scanning calorimetry (DSC), differential thermal analysis-thermogravimetry, and fourier transform infrared spectroscopy. An accurate kinetic model was proposed to describe the decomposition in the nitrolysis solution by applying an ordinary differential equation fitting method to isothermal DSC data and non-isothermal DTA data. We found that the thermal decomposition in the mixed solution is attributed to pyrolysis of organic nitrates in acid solution. The process is coupled with rapid reaction rate, great heat release, and huge amounts of reddish-brown gas produced. The decomposition in the nitrolysis solution follows a 1.162th Prout-Tompkins equation with autocatalysis, with a differential kinetic mechanism function of f(α) = (1 − α)1.162·α0.4189. The thermal safety evaluation and safety parameters were finally studied based on four criteria and isoperibolic experiment data. The thermal safety margin is less than 164.57 K and the bursting point of pyrolysis is 338.43 K at 5 min of delay time. These results show that the nitrolysis solution is hazardous and the thermal sensitivity is higher than that of 2-ethylhexyl nitrate and hexogen.

In traditional integrated electricity and district heating systems, the inflexible operation of combined heat and power units leads to a large amount of wind power curtailments during winter. The thermal inertia of aggregated buildings can provide additional operational flexibility to promote wind power accommodation. In this study, a day-ahead scheduling model for integrated electricity and district heating system considering the thermal inertia of buildings is proposed. In this work, the operation model of the district heating network under constant mass flow and variable temperature operation strategy is presented, and the aggregated model of buildings based on the detailed thermal model of buildings is established. Then, the scheduling framework is analysed and the day-ahead scheduling model is formulated as quadratic programming problem to minimise the operation cost of integrated electricity and district heating system. The validity of the proposed model is verified by the case studies performed on a 6-bus power system with a 6-node heating system and IEEE 39-bus electricity system with a 16-node heating system. The results demonstrate that the thermal inertia of buildings can provide additional operational flexibility and effectively help reduce wind power curtailment and operation costs.

During the actual operation of micro grid, the power fluctuation of tie line caused by the Load power fluctuation of renewable energy or load prediction deviation needs to be controlled in real time to ensure the economy of micro grid operation. This paper aims at a power system model based on the framework of "distribution network - industrial park micro grid - enterprise load user", and studies a power control method of micro grid tie line based on user reward scheme. Firstly, the objective economic function of the micro-grid in the park is established, and then the optimal reward scheme for internal load users of the micro-grid in the park is derived according to two typical load response models. The power fluctuation can be stabilized by encouraging load users to respond to demand, thus the internal load users can benefit while reducing their own economic losses and the day-ahead scheduling results of tie lines can be effectively tracked. Taking a production industrial park as an example, the effectiveness of the proposed optimization model and algorithm is verified by an example analysis.

Reducing the hygroscopicity and thermal decomposition temperature of ammonium perchlorate is of great significance for its application in solid rocket propellants. In this work, an in situ chemical precipitation reaction of stearic acid with copper acetate or cobalt acetate was adopted to prepare hydrophobic coatings of AP. The prepared samples were characterized by scanning electron microscopy, infrared spectroscopy, X-ray diffraction, contact angle measurement, differential thermal analysis and thermogravimetric analysis. The results show that a compact and uniform hydrophobic layer of copper stearate (CuSt2) or cobalt stearate (CoSt2) is successfully coated on the surface of AP particles. Compared with the raw AP, the contact angles of AP/CuSt2 and AP/CoSt2 with a coating content of 10 wt% are increased by 136.2° and 133.6°, respectively. Meanwhile, their moisture contents after being placed at 79 wt% relative humidity for 66 h are only 7.42% and 7.68% of the raw AP case. In addition, the high-temperature decomposition peak temperatures of AP/CuSt2 and AP/CoSt2 at the optimum coating content (6 wt%) are lowered by 113.3 °C and 75.8 °C, respectively, revealing that the hydrophobic coatings have high catalytic activity in the decomposition of AP. This research provides a promising strategy for reducing the hygroscopicity and simultaneously improving the thermal performance of AP, and this is also a reference for the modification of other materials.

Energetic thin films have been widely used in the field of microscale energy-demanding systems. In this work, a novel energetic metal–organic frameworks [Cd5(Mtta)9]n film is fabricated on the copper substrate through an in situ synthesis method for the first time. A 5-methyl tetrazole/copper complex is deposited to modify the copper substrate through an electrochemical-assisted strategy. The [Cd5(Mtta)9]n film is then integrated on the surface of modified copper substrate by an in situ reaction of acetonitrile with sodium azide and cadmium nitrate. The morphological, structural and compositional information of the [Cd5(Mtta)9]n film is characterized by field emission scanning electron microscopy, X-ray diffraction and infrared spectrum. The thermostabilities of the [Cd5(Mtta)9]n film are studied by differential scanning calorimetry and thermogravimetry. In addition, the preliminary laser ignition test is conducted by using pulsed Nd:YAG laser. The results show that the as-prepared [Cd5(Mtta)9]n film possesses a rod-like topography. The flame height and ignition duration of [Cd5(Mtta)9]n film reach 9.0 mm and 220 µs, respectively, revealing that [Cd5(Mtta)9]n film is an excellent ignition material. This research opens up a new avenue for the preparation of novel energetic films, which provides potential applications on microelectromechanical systems to achieve functional nanoenergetics-on-a-chip.

Aiming to utilize the flexibility of smart buildings for flexible operation of active distribution network, a combined modeling and optimal scheduling method for the active distribution network with integrated smart buildings is proposed in this paper. Based on the heat storage characteristics of a building, the energy consumption prediction model of the building considering different heating zones with different orientations is developed using the Resistor-Capacitor thermal network model. Then, different optimal control methods of the heating, ventilation and air-conditioning system in the building are developed. The energy consumption management of the heating, ventilation and air-conditioning system is achieved by adjusting the room temperature within the suitable temperature comfort range. In order to further consider the impact of the integration of smart buildings on the economic and security operation of the active distribution network, the optimal scheduling method of the active distribution network with integrated smart buildings is developed considering the load factor of the aggregation of the smart buildings. Finally, the optimal scheduling results of the aggregation of the smart buildings under different heating, ventilation and air-conditioning control methods in the winter heating scenario are analyzed. In addition, based on the branch flow model, the optimal power flow model of active distribution network with on-load tap changer is constructed by piecewise linearization and second-order cone relaxation to achieve flexible and optimal operation of the active distribution network. Thus, the impacts of the optimal schedules of the aggregation of smart buildings on the economic and security operation of the active distribution network are further evaluated. Numerical studies demonstrate that the proposed optimal scheduling method can make full use of the demand response potential of the smart buildings and further contribute to the operating costs reduction of the smart buildings. Meanwhile, the optimization of the active distribution network with the load factor of the aggregation of buildings can reduce the power loss and increase the minimum voltage magnitude of the active distribution network utilizing the flexibility of the smart buildings.

The integration of large-scale wind power brings challenges to the operation of integrated energy systems (IES). In this paper, a day-ahead scheduling model for IES with wind power and multi-type energy storage is proposed in a scenario-based stochastic programming framework. The structure of the IES consists of electricity, natural gas, and heating networks which are all included in the model. Operational constraints for IES incorporating multi-type energy storage devices are also considered. The constraints of the electricity network, natural gas network and heating network are formulated, and nonlinear constraints are linearized. The calculation method for the correlation of wind speed between wind farms based on historical data is proposed. Uncertainties of correlated wind power were represented by creating multiple representative scenarios with different probabilities, and this was done using the Latin hypercube sampling (LHS) method. The stochastic scheduling model is formulated as a mixed integer linear programming (MILP) problem with the objective function of minimizing the total expected operation cost. Numerical results on a modified PJM 5-bus electricity system with a seven-node natural gas system and a six-node heating system validate the proposed model. The results demonstrate that multi-type energy storage devices can help reduce wind power curtailments and improve the operational flexibility of IES.

Green energy is driving the evolutions of energy industry and carbon emission is becoming an important concern. Considering the increasing couplings among various energy sectors, this paper investigates multi-period optimal energy flow and energy pricing in carbon-emission embedded integrated energy systems, including electricity, natural gas, and district heating networks. Firstly, an optimal scheduling model of integrated energy systems was proposed in this paper. The models of DC power flow, natural gas pipeline flow and heating network energy flow are presented and linearized for the optimization problem. Natural gas-fired generators and combined heat and power (CHP) units are modeled as coupling components of electricity-gas and electricity-heating networks. Then, based on the optimal scheduling model, the locational marginal prices (LMP) for electricity, natural gas and heating network are determined. Moreover, the carbon emission caused by energy production has been taken into account in the optimal scheduling and energy pricing process. Finally, case studies on a combined network consisting of IEEE 39-bus system, Belgium 20-node natural gas system and 6-node heating system demonstrate the effectiveness of the proposed model and the impacts of carbon emission on system scheduling and LMP.

Intermolecular energetic materials (IEMs) have become the focus of attention due to their excellent performance in combustion, ignition, energy release and sensitivity. In this paper, two IEMs were successfully designed and prepared by the self-assembly of 5-aminotetrazole (5-ATZ) and transition metal ions on the surface of ammonium perchlorate (AP) particles. The scanning electron microscope, infrared spectroscopy, powder X-ray diffraction, thermogravimetric analyses, and differential thermal analyses were employed to characterize the prepared samples. The results show that the surface of AP particles is completely covered by a uniform and dense M(5-ATZ)4Cl2 (M = Cu, Co) self-assembled layer. Thermal analyses show that the high-temperature decomposition peak temperatures of AP/Cu(5-ATZ)4Cl2 (10 wt%) and AP/Co(5-ATZ)4Cl2 (10 wt%) are decreased by 93.3 °C and 127.1 °C compared to the case of pure AP, while the heat releases of them are increased by 539 J∙g−1 and 580 J∙g−1. In addition, the burning rates of AP/Cu(5-ATZ)4Cl2/Al (10 wt%) and AP/Co(5-ATZ)4Cl2/Al (10 wt%) are increased by 6.8 mm∙s−1 and 7.8 mm∙s−1 compared with the case of AP/Al. Moreover, the hygroscopicity tests show that the prepared samples do not agglomerate aftter being placed in the atmosphere with a relative humidity of 79% for 66 h. This research shows considerable application prospects in improving the combustion and energy performance of solid propellants, it is also a reference for the design and preparation of other novel IEMs.

Ammonium perchlorate is an important oxidizer in solid rocket propellants, underwater explosives and pyrotechnics. The crystal quality of ammonium perchlorate has an important impact on its application in these fields. In this work, a dropwise cooling crystallization method was proposed to crystallize ammonium perchlorate in gas–liquid two-phase suspension systems. Compared with the typical cooling crystallization method, dropwise cooling crystallization is favorable to control supersaturation and then control the shape and size of ammonium perchlorate crystals. The prepared samples were characterized by scanning electron microscopy, optical microscopy, laser particle distribution measurement, thermogravimetric analysis and powder X-ray diffraction. It is clearly shown that the as-prepared ammonium perchlorate crystals exhibit a high-index faced polyhedron morphology with a uniform shape and a narrow particle size distribution, the size of which can be controlled within the range of 13.64 μm to 50.33 μm. In addition, the gas-phase medium plays a good role in mixing, and it is found that higher gas-phase medium flow rates and higher feed rates of concentrated ammonium perchlorate solution result in a smaller average size of ammonium perchlorate crystals. Moreover, the crystallization method proposed in this study also has a good effect on the crystallization of sodium nitrate and ammonium chloride. This research provides a reference for the crystallization of other crystalline materials in crystal engineering.

The integration of high-penetration distributed generators (DGs) with smart inverters and the emerging power electronics technology of soft open points provide increased controllability and flexibility to the operation of active distribution networks. Existing works on distributed energy storage planning have not fully considered the coordinated operation of these new power electronic devices with distributed energy storage systems, leading to less economic investment decisions. This paper proposes an optimal planning model of distributed energy storage systems in active distribution networks incorporating soft open points and reactive power capability of DGs. The reactive power capability of DG inverters and on load tap changers are considered in the Volt/VAR control. Moreover, soft open points are modeled to provide flexible active and reactive power control on the associated feeders. Hourly network reconfiguration is conducted to optimize the power flow by changing the network topology. A mixed-integer second-order cone programming model is formulated to optimally determine the locations and energy/power capacities of distributed energy storage systems. Finally, the effectiveness of the proposed model is validated on a modified IEEE 33-node distribution network. Considering soft open points, DG reactive power capability, and network reconfiguration, the results demonstrate the optimal distributed energy storage systems planning obtained by the proposed model achieves better economic solution.

Global warming caused by excessive CO2 emissions has make it urgent to develop low-carbon economy. The carbon capture system is effective to reduce the carbon footprint of coal-fired power plants. Meanwhile, using more renewable energies such as wind power will require less generations from traditional power plants and hence limit the overall carbon emission. However, the wind power is intermittent by nature and hence may fluctuate and present a stochastic feature. In order to effectively reduce the overall carbon emission, a stochastic day-ahead scheduling optimization model with wind power integration incorporating carbon capture power plant (CCPP) and coupon-based demand response (CDR) is proposed in this work. Firstly, the formulation of CDR and the operating mechanism of CCPPs are clarified. Then the flexible operation mechanism aiming at reducing wind power curtailment and CO2 emissions is analyzed. The random forecasting errors of the day-ahead hourly wind power output and loads are considered. Monte Carlo method is applied to simulate stochastic scenarios and a scenario reduction method is applied to ease the computational burden. Simulation results with on the PJM 5-bus system and the IEEE 118-bus system demonstrate the effectiveness of the proposed method in carbon emission reduction and wind curtailments decrease.

Aiming to further achieve the flexible operation of the active distribution network by utilizing heating, ventilation and air-conditioning systems and electric vehicles of office buildings, a hierarchical scheduling method of active distribution network considering flexible loads in office buildings is proposed in this paper. In stage I, based on the heat storage property of office buildings and the behavioral property of office workers, an energy optimal scheduling model of the office building incorporating heating, ventilation and air-conditioning systems and electric vehicles is established. In stage II, an optimal scheduling method of the active distribution network considering on-load tap changer and flexible loads (i.e., heating, ventilation and air-conditioning systems and electric vehicles) in office buildings is developed by using the second-order conic relaxation and piecewise linearization. Finally, the scheduling results for the heating, ventilation and air-conditioning systems and electric vehicles in office buildings under different cases are compared in a winter scenario, and the security and economy of the active distribution network considering flexible loads in office buildings are further analyzed. Numerical studies demonstrate that the proposed method can contribute to the office building cost reduction and the load factor increment while guaranteeing the heating and the transportation demands of office workers. It can further improve the security and economic operation of the distribution network.