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Abstract Ammonia-based chemisorption cycle driven by low grade heat exhibits vast potential for power generation because there exists huge pressure difference between the two salt-adsorbent-filled reactors. However, the intrinsic feature of ammonia as a wet fluid and the difficult match between chemisorption cycle and expansion device impede the development of such a power generation system and also increase the difficulty of practical implementation. To explore maximum benefits of this technology, the present work has proposed and studied a new resorption power generation cycle that applies multiple expansion. The application of multiple expansion integrated with reheating processes aims to overcome the limitation of the ammonia being wet fluid and fully harness the huge pressure difference that chemisorption can offer for power generation, leading to the improvement of energy efficiency. The performance of the proposed multiple expansion resorption power generation cycle using three typical resorption salt pairs, including sodium bromide – manganese chloride, strontium chloride – manganese chloride and sodium bromide – strontium chloride, have been investigated not just based on theoretical thermodynamics but also with the consideration of practical factors to obtain better understanding and more insights for a real system design. The multiple expansion resorption power generation using sodium bromide – manganese chloride and sodium bromide – strontium chloride pairs can achieve 100–600 kJ/kg (ammonia) work output when heat source temperature is from 30 °C to 150 °C; the multiple expansion using strontium chloride – manganese chloride pair has higher average work output per one expansion stage than that using the other two pairs. The cyclic energy efficiency can be achieved as 0.06–0.15 when implementing 2–4 expansions in a more practical scenario where the equilibrium pressure drop is set to 2 bar and the heat source temperature is in the range of 80–150 °C. Such efficiencies are circa 27–62% of Carnot efficiency under the same thermal conditions.

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.

Attempts to model any present or future power grid face a huge challenge because a power grid is a complex system, with feedback and multi-agent behaviors, integrated by generation, distribution, storage and consumption systems, using various control and automation computing systems to manage electricity flows. Our approach to modeling is to build upon an established model of the low voltage electricity network which is tested and proven, by extending it to a generalized energy model. But, in order to address the crucial issues of energy efficiency, additional processes like energy conversion and storage, and further energy carriers, such as gas, heat, etc., besides the traditional electrical one, must be considered. Therefore a more powerful model, provided with enhanced nodes or conversion points, able to deal with multidimensional flows, is being required. This article addresses the issue of modeling a local multi-carrier energy network. This problem can be considered as an extension of modeling a low voltage distribution network located at some urban or rural geographic area. But instead of using an external power flow analysis package to do the power flow calculations, as used in electric networks, in this work we integrate a multiagent algorithm to perform the task, in a concurrent way to the other simulation tasks, and not only for the electric fluid but also for a number of additional energy carriers. As the model is mainly focused in system operation, generation and load models are not developed. The financial support from EPSRC for Liz Varga on project entitled "Transforming Utilities’ Conversion Points" (no. EP/J005649/1) is gratefully acknowledged.

In the present work, an experimental study on a lab-scale adsorption refrigerator, based on activated carbon/ethanol working pair is reported. An extensive testing campaign has been carried out at the CNR ITAE laboratory, with multiple aims. First, the performance has been evaluated in terms of both COP and Specific Cooling Power (SCP), under different boundary conditions, including both air conditioning and refrigeration applications. Attractive SCPs, up to 180 W/kg and 70 W/kg for air conditioning and refrigeration, respectively, were measured. Under the same conditions, COP between 0.17 and 0.08 were obtained. In addition, different management strategies, namely, heat recovery between adsorbers and re-allocation of phase durations, were evaluated to identify their influence on the system. Both strategies confirmed the possibility of increasing COP and SCP up to 40% and 25%, respectively. Moreover, a design analysis based on the experimental results has been carried out, to suggest possible improvements of the system. The obtained results demonstrated the possibility of employing a non-toxic refrigerant like ethanol reaching performance comparable with other harmful refrigerants like ammonia and methanol.

The effect of pilot injection timing and pilot injection mass on combustion and emission characteristics under medium exhaust gas recirculation (EGR (25%)) condition were experimentally investigated in high-speed diesel engine. Diesel fuel (B0), two blends of butanol and diesel fuel denoted as B20 (20% butanol and 80% diesel in volume), and B30 (30% butanol and 70% diesel in volume) were tested. The results show that, for all fuels, when advancing the pilot injection timing, the peak value of heat release rate decreases for pre-injection fuel, but increases slightly for the main-injection fuel. Moreover, the in-cylinder pressure peak value reduces with the rise of maximum pressure rise rate (MPRR), while NOx and soot emissions reduce. Increasing the pilot injection fuel mass, the peak value of heat release rate for pre-injected fuel increases, but for the main-injection, the peak descends, and the in-cylinder pressure peak value and NOx emissions increase, while soot emission decreases at first and then increases. Blending n-butanol in diesel improves soot emissions. When pilot injection is adopted, the increase of n-butanol ratio causes the MPRR increasing and the crank angle location for 50% cumulative heat release (CA50) advancing, as well as NOx and soot emissions decreasing. The simulation of the combustion of n-butanol–diesel fuel blends, which was based on the n-heptane–n-butanol–PAH–toluene mixing mechanism, demonstrated that the addition of n-butanol consumed OH free radicals was able to delay the ignition time.

Abstract This paper aims at providing a performance analysis of a grid connected photovoltaic power plant in Sardinia by investigating on the effective performance ratio of PV installations, with a critical analysis of the whole energetic transformation chain, starting from the incident solar energy, to the DC energy output from the modules and AC energy output from the inverter and transformer. The parameters that can influence the energy production are analyzed in order to find out the critical points in the optimization of the PV system design process. One year measurement and performance analysis of two real-life grid connected PV power plants are presented in the paper, providing up-to-date measurement data, useful to compare the effective energy production of PV plants positioned in different areas of the world. Monthly variability of the performance ratio and its correlation with ambient temperature is also discussed in the paper.

Abstract Demand response and real-time pricing of electricity are key factors in a smart grid as they can increase economic efficiency and technical performances of power grids. This paper focuses on incorporating price-responsive customers in day-ahead scheduling of smart distribution networks under a dynamic pricing environment. A novel method is proposed and formulated as a tractable mixed integer linear programming optimization problem whose objective is to find hourly sale prices offered to customers, transactions (purchase/sale) with the wholesale market, commitment of distribution generation units, dispatch of battery energy storage systems and planning of interruptible loads in a way that the profit of the distribution network operator is maximized while customers’ benefit is guaranteed. To hedge distribution network operator against financial risk arising from uncertainty of wholesale market prices, a risk management model based on a bi-level information-gap decision theory is proposed. The proposed bi-level problem is solved by recasting it into its equivalent single-level robust optimization problem using Karush–Kuhn–Tucker optimality conditions. Performance of the proposed model is verified by applying it to a modified version of the IEEE 33-bus distribution test network. Numerical results demonstrate the effectiveness and efficiency of the proposed method.

Solid oxide cell systems (SOCs) are increasingly being considered for electrical energy storage and as a means to boost the use of renewable energy and improve the grid flexibility by power-to-gas electrochemical conversion. The control of several variables (e.g., local temperature gradients and reactant utilization) is crucial when the stacks are used in dynamic operation with intermittent electrical power sources. In the present work, two 1D models of SOC stacks are established and used to investigate their dynamic behavior and to select and tune a suitable control strategy. Subsequently, safe operating ranges were determined to meet the thermal constraints of the stack by analysing not only the fuel cell (SOFC) and electrolyzer (SOEC) individual modes but also the switching between the two modes when the stack operates reversibly. The dynamic analysis shows that the control loops of our multi-input (reactant molar flow rates), multi-output (reactant utilization and maximum local temperature gradients) control system are strongly decoupled. Therefore, a proportional integral control strategy can be used to prevent dangerous stack operating conditions in dynamic operation. Finally, the controllers were tuned, and their transfer functions were reported. Convective heat transfer via air flow allows controlling the temperature of the solid structure of the cell/stack component, thus avoiding issues related to temperature variation during transient operation. Moreover, the reactant utilization controllers can avoid component fracture or degradation owing to fuel starvation under dynamic operation. The process can be approximated by two first order transfer functions. It can help in the design of more complex control systems in the future if necessary, with embedded process models, such as model predictive control. Results in the simulation environment are preparatory to the programming phase of an actual controller in real-world applications.