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The paper aims to design and prove the concept of micro-industry using trigeneration fuelled by biomass, for sustainable development in rural NW India.

This is being tested at village Malunga, near Jodhpur in Rajasthan. The system components comprise burning of waste biomass for steam generation and its use for power generation, cooling system for fruit ripening and the use of steam for producing distilled water. Site was selected taking into account the local economic and social needs, biomass resources available from agricultural activities, and the presence of a NGO which is competent to facilitate running of the enterprise. The trigeneration system was designed to integrate off-the-shelf equipment for power generation using boilers of approximate total capacity 1 tonne of fuel per hour, and a back-pressure steam turbo-generator (200 kW). Cooling is provided by a vapour absorption machine (VAM).

The financial analysis indicates a payback time of less than two years. Nevertheless, this is sensitive to market fluctuations and availabilities of raw materials.

Although comparable trigeneration systems already exist in large food processing industries and in space heating and cooling applications, they have not previously been used for rural micro-industry. The small-scale (1-2 m3/h output) multiple effect distillation (3 effect plus condenser) unit has not previously been deployed at field level.

This paper aims to analyze energy and exergy analysis of solar-based intercooled and reheated gas turbine (GT) trigeneration cycle using parabolic trough solar collectors (PTC) with the use of MATLAB 2018.

In the first section of this paper, the solar-based GT is validated with the reference paper. According to the reference paper, the solar field is comprising 30 modules in series and 35 modules in parallel series, where a total of 1,050 modules of PTC are taken into consideration. In the second part of this paper, the hybridization of the solar, GT trigeneration cycle is analyzed and optimized. In the last section of this paper, the hybridization of solar, intercooled and reheated GT trigeneration systems is examined and compared.

The results examined the first section, the power produced by the cycle will be 37.34 MW at 0.5270 kg/s mass flow rate of the natural gas consumption and the efficiencies of energy and exergy will be 38.34% and 39.76%, respectively. The results examined in the second section, the power produced by the cycle will be 38.4 MW at 0.5270 kg/s mass flow rate of the natural gas consumption and accordingly the efficiency of energy and exergy is found to be 40.011% and 41.763%. Where in the last section, the power produced by the cycle will be 41.43 MW at 0.5270 kg/s mass flow rate of the natural gas consumption and the energy and exergy efficiencies will be 39.76% and 40.924%, respectively.

The author confirms that this study is original and has neither been published elsewhere nor it is currently under consideration for publication elsewhere.

The objective of this study is to highlight the questions arising in the design of district heating and cooling systems (DHCSs) in a distributed generation context and to present a model to help find cost‐effective solutions.

Literature on energy systems optimisation is reviewed and a mixed integer programming model for decentralized DHCSs design is developed and applied to two real case studies.

Distributed cooling generation partly coupled with distributed cogeneration and DH is the preferred solution in the examined areas. The optimal configurations, with special reference to network sizing and layout, significantly depend on heating demand profiles and energy prices.

Interdependencies between energy units sizing and network layout definition should be considered. Obtaining more robust and reliable network configurations should be the objective of future modelling efforts.

Despite the growth of distributed energy conversion, designers often rely on centralized concepts in order to reap economies of scale. The presented model helps in discovering less usual solutions representing the most profitable option.

Combining and comparing central and distributed production of heat and cooling under consideration of network costs.

The purpose of this paper is to assess renewable energy‐based cooling technologies using multi‐criteria methodology.

Analytic hierarchy process (AHP) methodology is applied to obtain the ranking of renewable energy options for cooling technology using five different criteria. In total, seven technologies were analyzed, based on the opinions obtained from experts and the extensive literature survey made and the ranking was obtained using AHP method.

The present findings revealed that the ranking for the renewable energy‐based cooling technologies were in the following order: biomass combustion, biogas, trigeneration, SPV, biomass gasifier, solar thermal storage, and hybrid technology. Only 5 per cent variation in global priority exists among top three options. This variation is considered insignificant due to rapidly varying factors such as technological advancements, government promotional schemes, fuel availability, etc. and hence these three options may be ranked equally.

The research output is helpful in identifying the technology, with promising potential for promoting technology on a wider scale. Additional attributes and sensitivity analysis can be included for further research.

The paper usefully describes the AHP methodology utilized in the present study and the ranking made for the evaluation of renewable energy‐based cooling systems. The outcome of the present study would benefit policymakers, researchers and entrepreneurs when choosing the appropriate cooling technology.

The way and manner in which energy is produced is known to have a significant impact on emissions. For this reason, the UK government has sought to enhance the efficiency of energy production/conversion by focusing on a number of energy production approaches, including Combined Heat and Power (CHP). The purpose of this paper is to describe a practical approach for assessing the feasibility of CHP.

The authors provide an overview of Combined Heat and Power (CHP); describe a new and easy‐to‐implement feasibility and optimisation model to aid in the installation of CHP; and discuss the practical feasibility issues of CHP through an analysis of existing case studies using the proposed model. The modelling utilises regression models which are created using historical data obtained from public sources.

Compared against alternatives, the model is shown to be particularly useful, as its functionality is embedded in resource‐intensive prime mover specifications obtained from seven real industrial cases.

The need for such a practical and easy‐to‐use model is driven by the existence of numerous models, which are mainly complex and not necessarily “user‐friendly”. The proposed model is set to provide a practical and user‐friendly model for CHP appraisal that is easy to understand and assess in terms of prime movers such as capital cost, payback, annual financial and CO₂ savings.

This study is aimed to develop a novel intuitionistic fuzzy P-graph with Gaussian membership function to help decision-makers deal with complex process network systems.

Two fuzzy P-graph case studies of the cogeneration system were selected, and relevant data were collected, including the structure and flow sequence of the system, and the rate of material and product transitions between the operating units. Gaussian function membership was set according to the restriction of fuzzy upper and lower bounds. Then the α-cut was used to obtain different upper and lower bound restrictions of each membership degree. After finding the optimal and suboptimal solutions for different membership degrees, the results of non-membership and hesitation were calculated.

The proposed method will help the decision maker consider the risk and provide more feasible solutions to choose the optimal and suboptimal solutions based on their own or through experience. The proposed model in this study has more flexibility in operation and decision making.

This study is the first to propose a novel intuitive fuzzy P-graph and demonstrates the effectiveness and flexibility of the method by two case studies of the cogeneration system. However, the addition of hesitation can increase the error tolerance of the system. Even for the solutions with a high degree of membership, optimal and suboptimal solutions still exist for the decision maker to select. Since decision makers expect the higher achievement of the target requirements; thus, it is important to have more feasible solutions with a high degree of membership.

This paper seeks to set out opportunities for the development of a UK‐focused feasibility and sizing model utilising linear programming.

Optimisation of the model is conducted using integer linear programming developed using Excel Solver.

When compared with comparable alternatives, the model is shown to be particularly useful as its functionality is embedded in resource intensive prime mover specifications obtained from seven real industrial cases.

The study acknowledges the limitation of utilising sizing data primarily obtained from secondary sources to develop the model.

The practical usefulness of this model is that it has been built using “real”, as opposed to simulated‐data. When compared with comparable alternatives, the model is shown to be articularly useful as its functionality is embedded in resource intensive prime mover specifications obtained from seven real industrial cases.

This study aims to investigate the aviation, energetic, exergetic, environmental, sustainability and exergoeconomic performances of a micro turbojet engine used in unmanned aerial vehicles at four different modes.

The engine data were collected from engine test cell. The engine performance calculations were performed for four different operation modes.

According to the results, maximum energy and exergy efficiency were acquired as 19.19% and 18.079% at Mode 4. Total cost rate was calculated as 6.757 $/h at Mode-1, which varied to 10.131 $/h at Mode-4. Exergy cost of engine power was observed as 0.249 $/MJ at Mode-1, which decreased to 0.088 $/MJ at Mode-4 after a careful exergoeconomic analysis.

The novelty of this work is the capability to serve as a guide for similar systems with a detailed approach in the thermodynamic, thermoeconomic and environmental assessments by prioritizing efficiency, fuel consumption and cost formation. This investigation intends to establish a design of the opportunities and benefits that the thermodynamic approach provides to turbojet engine systems.

This study aims to solve optimal pricing and power bidding strategy problem for integrated combined heat and power (CHP) system by using a modified heuristic optimization algorithm.

In electricity markets, generation companies compete according to their bidding parameters; therefore, optimal pricing and bidding strategy are solved. Recently, CHP units are significantly operated by generation companies to meet power and heat, simultaneously.

For validation, it is shown that profit is improved by 0.04%–48.02% for single and 0.02%–31.30% for double-sided auctions. As heat price curve is extracted, the simulation results show that when CHP system is integrated with other units results in profit increase and emission decrease by 3.04%–3.18% and 2.23%–4.13%, respectively. Also, CHP units significantly affect bidding parameters.

The novelties are pricing and bidding strategy of integrated CHP system is solved; local heat selling is considered in pricing and bidding strategy problem and heat price curve is extracted; the effects of CHP utilization on bidding parameters are investigated; a modified heuristic and deterministic optimization algorithm is presented.

This paper attempts to establish the general formula for computing the inverse of grey matrix, and the results are applied to solve grey linear programming. The inverse of a grey matrix and grey linear programming plays an important role in establishing a grey computational system.

Starting from the fact that missing information often appears in complex systems, and therefore that true values of elements are uncertain when the authors construct a matrix, as well as calculate its inverse. However, the authors can get their ranges, which are called the number-covered sets, by using grey computational rules. How to get the matrix-covered set of inverse grey matrix became a typical approach. In this paper, grey linear programming was explained in detail, for the point of grey meaning and the methodology to calculate the inverse grey matrix can successfully solve grey linear programming.

The results show that the ranges of grey value of inverse grey matrix and grey linear programming can be obtained by using the computational rules.

Because the matrix and the linear programming have been widely used in many fields such as system controlling, economic analysis and social management, and the missing information is a general phenomenon for complex systems, grey matrix and grey linear programming may have great potential application in real world. The methodology realizes the feasibility to control the complex system under uncertain situations.

The paper successfully obtained the ranges of uncertain inverse matrix and linear programming by using grey system theory, when the elements of matrix and the coefficients of linear programming are intervals and the results enrich the contents of grey mathematics.