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In the current situation with the unprecedented deployment of clean technologies for electricity generation, it is natural to expect that storage will play an important role in electricity networks. This paper provides a qualitative methodology to select the appropriate technology or mix of technologies for different applications. The multiple comparisons according to different characteristics distinguish this paper from others about energy storage systems. Firstly, the different technologies available for energy storage, as discussed in the literature, are described and compared. The characteristics of the technologies are explained, including their current availability. In order to gain a better perspective, availability is cross-compared with maturity level. Moreover, information such as ratings, energy density, durability and costs is provided in table and graphic format for a straightforward comparison. Additionally, the different electric grid applications of energy storage technologies are described and categorised. For each of the categories, we describe the available technologies, both mature and potential. Finally, methods for connecting storage technologies are discussed.

Massive adoptions of combined heat and power (CHP) units necessitate the coordinated operation of power system and district heating system (DHS). Exploiting the reconfigurable property of district heating networks (DHNs) provides a cost-effective solution to enhance the flexibility of the power system by redistributing heat loads in DHS. In this paper, a unit commitment considering combined electricity and reconfigurable heating network (UC-CERHN) is proposed to coordinate the day-ahead scheduling of power system and DHS. The DHS is formulated as a nonlinear and mixed-integer model with considering the reconfigurable DHN. Also, an auxiliary energy flow variable is introduced in the formed DHS model to make the commitment problem tractable, where the computational burdens are significantly reduced. Extensive case studies are presented to validate the effectiveness of the approximated model and illustrate the potential benefits of the proposed method with respect to congestion management and wind power accommodation. (Corresponding author:Hongbin Sun)

Robust mitigation options will play significant role in achieving the target of limiting global change to below 1.5 °C above pre-industrial levels by 2100. To support cooperation for mitigation development, we establish a real options-based model to evaluate the rational decisions of exercising the abandon option for carbon capture and storage-enhanced oil recovery (CCS-EOR) projects under oil market and geological uncertainties. Three possible cooperative mechanisms (fixed carbon dioxide (CO2) price, oil-indexed CO2 price, and joint venture contracts) among CO2-EOR stakeholders are evaluated. The results show that the conflicts in profit maximization targets for different stakeholders in cooperative mitigation are to a great extent unable to be avoided. A joint venture business model is preferred in cooperative mitigation as it can effectively weaken such conflicts. And it is more reasonable to provide incentives to the downstream of the CO2-EOR chain than compensating the adoption cost of carbon capture technologies in the upstream. From a global perspective, the inefficient cooperation can be a main barrier that hinders the development of deep-cutting options. Global mitigation strategies should not only focus on promoting technology progress but also the design of innovative business models to balance the benefits among stakeholders. A joint venture business model is recommended in both the developed and developing countries for seizing the early mitigation opportunities.

Abstract The potential of using high metals containing coal gangue and lignite to prepare high-activity coal char-based catalysts is investigated for effective biomass tar decomposition. Loose structure and rough surface are formed for these char-based catalysts with heterogeneous distribution of a large number of inorganic particles. In the biomass tar decomposition, the performance of the coal char-based catalysts is significantly influenced by the content of the metals in the raw materials and coal gangue char (GC) with the ash content as high as 50.80% exhibits the highest activity in this work. A high biomass tar conversion efficiency of 93.5% is achieved at 800 °C along with a significant increase in the fuel gas product. During the five-time consecutive tests, the catalytic performance of GC increases a little at the second or third times reuse and remains relatively stable, showing the remarkable stability of the catalyst in biomass tar decomposition applications.

Abstract This article introduces an effective stochastic operation framework for optimal energy management of the shipboard power systems including large, nonlinear and dynamic loads. The proposed framework divides the ship power system into several agents, which coordinate with each other based on their demands/supplies until. The alternating direction method of multipliers (ADMM) is deployed as the multi-agent framework to solve the reformulated distributed energy management problem in the ship. Two types of turbo-generators are considered in the proposed system model, including single-shaft and twin-shaft models, to increase the part-load efficiency in certain times when facing variable speed operation. The proposed distributed framework is equipped with a recursive mechanism, which helps the ship system for running optimal load scheduling when facing insufficient power generation. In order to model the uncertainty effects associated with the forecast error in the interval-ahead load demand, a stochastic framework based on unscented transform is devised which can work in the nonlinear and correlated environments of shipboard power systems. Due to the nonlinear cost function in each agent, a powerful optimization algorithm based on modified θ-firefly algorithm (Mθ-FOA) is proposed. This is a phasor algorithm, which helps for escaping from premature convergence and getting trapped in local optima. The appropriate performance of the proposed stochastic model is examined on the real dataset of a ship power system. The simulation results show the high robustness, guarantied consensus, economic operation and feasible solution when power generation shortage based on load shedding in the system.

Abstract Liquid fuels are likely to remain the main energy source in long-range transportation and aviation for several decades. To reduce our dependence on fossil fuels, liquid biofuels can be blended to fossil fuels – or used purely. In this paper, coconut methyl ester, standard diesel fuel (EN590:2017), and their blends were investigated in 25 V/V% steps. A novel turbulent combustion chamber was developed to facilitate combustion in a large volume that leads to ultra-low emissions. The combustion power of the swirl burner was 13.3 kW, and the air-to-fuel equivalence ratio was 1.25. Two parameters, combustion air preheating temperature and atomizing air pressure were adjusted in the range of 150–350 °C and 0.3–0.9 bar, respectively. Both straight and lifted flames were observed. The closed, atmospheric combustion chamber resulted in CO emission below 10 ppm in the majority of the cases. NO emission varied between 60 and 183 ppm at straight flame cases and decreased below 20 ppm when the flame was lifted since the combustion occurred in a large volume. This operation mode fulfills the 2015/2193/EU directive for gas combustion by 25%, which is twice as strict as liquid fuel combustion regulations. The 90% NO emission reduction was also concluded when compared to a lean premixed prevaporized burner under similar conditions. This favorable operation mode was named as Mixture Temperature-Controlled (MTC) Combustion. The chemiluminescent emission of lifted flames was also low, however, the OH* emission of straight flames was clearly observable and followed the trends of NO emission. The MTC mode may lead to significantly decreased pollutant emission of steady-operating devices like boilers, furnaces, and both aviation and industrial gas turbines, meaning an outstanding contribution to more environmentally friendly technologies.

A Wireless Sensor Network (WSN) is comprised of a number of sensor nodes (SNs) that are randomly placed in an open, harsh environment for many applications. Due to the resource-constrained nature of SNs and hostile deployment environments, energy efficiency and security are considered two key factors in designing WSN routing protocols. This paper proposes an Energy Efficient Secure Multipath (EESM) routing protocol to securely construct efficient routes and transmit data packets between SNs and the base station (BS). EESM achieves energy efficiency through minimal task allocation among SNs whereas all computation-intensive tasks such as network information collection, routing table generation, and network maintenance are performed by the BS. The proposed protocol incorporates lightweight security mechanisms including a one-way hash chain, message authentication code, encryption, and clique-based coordinator selection and monitoring schemes to defend against numerous security attacks. Simulation results show that EESM can successfully detect and protect the network against various security attacks such as replay attacks, sybil attacks, sinkhole attacks, spoofing attacks, compromised node attacks, and so on. In terms of energy efficiency, the proposed protocol achieves an up to 37% increase in network lifetime and a 6% increase in throughput over Secure and Energy Efficient Multipath (SEEM) routing, Secure and Reliable Multipath Routing (SRMR), and Reliable and Multipath Encounter Routing (RMER) protocols. The paper implements the protocol in a real environment using Arduino motes to analyze security overheads and network setup time.

Lithium-ion batteries are fast becoming the battery of choice in applications such as electric/hybrid electric vehicles (EV/HEV) and renewable energy systems. This increasing usage demands an improved reliability of the battery systems, which in turn heavily relies on the control and optimization algorithms. Of particular importance is ensuring that each lithium-ion cell within a battery pack remains strictly within an acceptable charge range to avoid untimely degradation of the battery pack. Unfortunately, current battery models make the design of charge equalization circuitry difficult due to their limitations. The aim of this paper is to develop a component-wise control-oriented physics-based battery pack model to facilitate implementation of advanced model-based control and optimization algorithms. In the first stage some existing results are used to obtain a simplified electrochemical ODE model of an individual lithium-ion cell. Then, the cell model is used as the building block of the complete battery pack model. Different charge/discharge scenarios are presented to illustrate the potential of the modeling approach in facilitating the implementation of advanced control and optimization algorithms in improved power equalization and hence prolonging the battery pack lifetime.