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District heating systems operation can be improved by control strategies. One of the options is the introduction of predictive control model. Predictive models of heat load can be applied to improve district heating system performances. In this article, short-term multistep-ahead predictive models of heat load for consumers connected to district heating system were developed using SVMs (Support Vector Machines) with FFA (Firefly Algorithm). Firefly algorithm was used to optimize SVM parameters. Seven SVM-FFA predictive models for different time horizons were developed. Obtained results of the SVM-FFA models were compared with GP (genetic programming), ANNs (artificial neural networks), and SVMs models with grid search algorithm. The experimental results show that the developed SVM-FFA models can be used with certainty for further work on formulating novel model predictive strategies in district heating systems.

Abstract In this study a non-parametric method of data envelopment analysis (DEA) was applied to analyze the efficiency of farmers, discriminate efficient farmers from inefficient ones and to identify wasteful uses of energy in order to optimize the energy inputs for apple production in Tehran province, Iran. From this study the following results were obtained: from the total of 56 farmers, considered for the analysis, 34% and 54% were found to be technically and pure technically efficient, respectively. The technical, pure technical and scale efficiency scores of farmers were 0.7857, 0.8982 and 0.8666, respectively. Optimum energy requirement was found to be 37993.15 MJ ha −1 ; indicating that 11.29% of total energy input could be saved if the recommendations of this study are followed. From total energy saving, the contribution of electrical energy was the highest; it followed by chemicals energy inputs; implying that there was a great scope for saving energy inputs by improving the use pattern of these inputs. The results of economical analysis showed that the total costs of production could decreased from 8227.70 to 7570.01 $ ha −1 ; also the benefit to cost ratio and productivity improved from 1.24 to 1.34 and 2.52 to 2.74, respectively.

Abstract The aims of this study comprise energy optimization, economic analysis and life cycle assessment in converting paddy to white rice by data envelopment analysis (DEA) and multi-objective genetic algorithm (MOGA). For these purposes, 60 milling factories in Guilan province in Iran are assessed. Results indicate that the amount of energy input and output are 68178.31 MJ TIP−1 and 11894.64 MJ TIP−1, respectively, in converting paddy to white rice, in which natural gas consumption has a very high contribution to the total energy inputs. Life cycle assessment results show that background system for natural gas in milling factories and combustion of natural gas inside factories are environmental hotspots. Based on optimization results in converting paddy to white rice (mainly with lower natural gas consumption), reductions in energy consumption are 6 and 24%, reductions of global warming potential are 8 and 9%, and increase net profits are 24 and 41% by using DEA and MGOA, respectively. It can be said that MGOA is an appropriate optimization method to find the best mix in converting paddy to white rice inputs in order to attain energy, environmental and economic efficiencies.

Abstract The mechanism of repetitive extinction-ignition dynamics for lean premixed hydrogen–air mixture is studied in a microchannel with prescribed wall temperature. In this dynamics, the reacting flow is affected by the wall temperature and leads to ignition near walls. The flame expands in both downstream and upstream directions until flame bifurcation occurs. Part of the flame which propagates towards inflow consumes all the unburned mixture along its way. As the flame reaches cold inflow mixture, it extinguishes due to the heat loss. Another part of flame consumes the unburned mixture in downstream until the flame is extinguished. Afterward, unburned mixture fills the tube again until it is reignited. The repetitive extinction-ignition dynamics can be classified in five phases, namely, initiation phase, ignition phase, propagation phase, weak reaction phase, and flowing phase. Three peaks were detected for hydrogen–air mixture combustion which all appears in propagation and weak reaction phases. In the remaining phases two peaks were present. Details of flow field indicate that bifurcation of flame is due to creation of recirculation zones formed close to the walls at the beginning of ignition phase. The recirculation zones grow and merge, until a boundary zone is created in flow field with zero velocity.

Abstract Maintenance of distribution systems has become more important due to the need to increase energy availability, quality and safety, and also reduce operation cost. Accordingly, the maintenance strategy in distribution systems is one of the most important decision-making activities. One of the most important evaluations for deciding the adequate performance of power distribution system is the identification of the critical components. On the other hand, the budget for maintenance of components is limited, so the maintenance should only be performed on critical components. Identifying the critical components is used to achieve the objective of minimising the cost for maintenance actions. This paper presents a new weighted importance (WI) reliability index model and proposes an appropriate method in order to prioritise the elements of distribution system for reliability-centered maintenance (RCM) at two different levels. At the first level, the feeders of a sample distribution substation are prioritised for the RCM actions. The second level is more detailed than the first level. At the second level, the components of a sample feeder are prioritised for the RCM actions. The reliability of system can be increased to as much as required level while minimal maintenance to be done by the maintenance prioritisation of the system components and performing the maintenance actions on the critical components. Appropriate maintenance decision-making for the critical components of distribution system can lead to the improvement in the reliability of distribution system.

Abstract In this paper, two new CO 2 cascade refrigeration cycles are proposed and analyzed. In both these cycles the top cycle is an ejector-expansion transcritical cycle and the bottom cycle is a sub-critical CO 2 cycle. In one of these proposed cycles the waste heat from the gas cooler is utilized to drive a supercritical CO 2 power cycle making the plant a combination of three cycles. Using the first and second laws of thermodynamics, theoretical analyses on the performance characteristics of the cycles are carried out. Also a parametric study is conducted to optimize the performance of each cycle under various operating conditions. The proposed cycles exhibit a reasonable value of COP (coefficient of performance) with a much less value of compressor discharge temperature, compared to the conventional cycles.

Abstract This paper presents a new method for exergy auditing of steam boilers. The presented method is based on developing ASME ptc4.1. The ASME ptc4.1 presents a method to estimate energy loss terms and the first law efficiency. This work presents a similar method to estimate exergy loss terms and exergitic efficiency. The method determines the inappropriately-working components. The identification of the components enables the auditors to improve the system's performance. Using this method the different terms of irreversibility including exergy destruction in the boiler, exergy loss through the boiler's wall, exergy destruction in GAH, the loss related to the flue gas exhaust, loss due to the emission of not-burnt hydrocarbons and loss due to formation of CO can be calculated. In order to examine the performance of the method, a boiler of a power plant is chosen and by measuring the temperature and the flue gas analysis, the boiler's wall temperature and some other required parameters, the components of the irreversibility are calculated. Results indicated that the largest amount of the irreversibility is related to exergy destruction inside the boiler that is more than 38% of the total exergy input. Results also revealed that the exergy efficiency of the boiler is 53.70%.

Abstract In this paper, to improve the performance of the thermodynamic system and reduce greenhouse gas emissions and fuel utilization, a novel power generation system based on syngas-fueled solid oxide fuel cell, gas turbine, organic flash cycle, and a thermoelectric generator was devised. The performance of the proposed system was analyzed through energy, exergy, exergoeconomic, economic, and environmental viewpoints. Finally, the multi-objective particle swarm optimization algorithm and TOPSIS and LINMAP decision-making methods were employed to obtain the optimum performance. According to the obtained results at the base operation condition, the main performance metrics were FX, FX, FX, FX, FX. For fuel cost of 3 $/GJ and electricity cost of FX, the payback time was around FXyears with a total profit of FX at the end of the economic lifetime. The parametric study revealed that the SOFC with anode and cathode gas recycling exhibits a higher exergy efficiency and lower Levelized total emissions. For the energy-cost optimization scenario, the optimum energy efficiency selected by LINMAP methods was FX, and the minimum total specific cost selected by TOPSIS method was FX. For the exergy-cost optimization scenario, the optimum exergy efficiency selected by TOPSIS was FX.