Effect of power interchange operation of multiple household gas engine cogeneration systems on energy-saving

The effect of power interchange operation of multiple household gas engine cogeneration systems (H-GCGS) on the energy-saving is investigated using an optimization approach based on the mixed-integer linear programming. In this power interchange operation, electricity generated by H-GCGS is shared among households in a housing complex without transmitting to a commercial electric power system so that the operating time of these systems may increase. This paper numerically analyzes optimal operational strategies for 20 households and three types of household energy supply configurations: the power interchange operation of the H-GCGSs (IC), stand-alone operation of each H-GCGSs (SA), and conventional energy supply system without the H-GCGSs. A numerical result clarifies the effectiveness of the power interchange operation from the energy-saving viewpoint and a dominant parameter for evaluating the energy-saving effect.     

Performance and emissions of a supercharged dual-fuel engine fueled by hydrogen-rich coke oven gas

This study investigated the engine performance and emissions of a supercharged dual-fuel engine fueled by hydrogen-rich coke oven gas and ignited by a pilot amount of diesel fuel. The engine was tested for use as a cogeneration engine, so power output while maintaining a reasonable thermal efficiency was important. Experiments were carried out at a constant pilot injection pressure and pilot quantity for different fuel-air equivalence ratios and at various injection timings without and with exhaust gas recirculation (EGR). The experimental strategy was to optimize the injection timing to maximize engine power at different fuel-air equivalence ratios without knocking and within the limit of the maximum cylinder pressure. The engine was tested first without EGR condition up to the maximum possible fuel-air equivalence ratio of 0.65. A maximum indicated mean effective pressure (IMEP) of 1425 kPa and a thermal efficiency of 39% were obtained. However, the nitrogen oxides (NOx) emissions were high. A simulated EGR up to 50% was then performed to obtain lower NOx emissions. The maximum reduction of NOx was 60% or more maintaining the similar levels of IMEP and thermal efficiency. Two-stage combustion was obtained; this is an indicator of maximum power output conditions and a precursor of knocking combustion.     

Feasibility of CHP-plants with thermal stores in the German spot market

The European Energy Exchange (EEX) day ahead spot market for electricity in Germany shows significant variations in prices between peak and off-peak hours. Being able to shift electricity production from off-peak hours to peak hours improves the profit from CHP-plant operation significantly. Installing a big thermal store at a CHP-plant makes it possible to shift production of electricity and heat to hours where electricity prices are highest especially on days with low heat demand. Consequently, these conditions will have to influence the design of new CHP-plants. In this paper, the optimal size of a CHP-plant with thermal store under German spot market conditions is analyzed. As an example the possibility to install small size CHP-plant instead of only boilers at a Stadtwerke delivering 30,000 MW h-heat for district heating per year is examined using the software energyPRO. It is shown that, given the economic and technical assumptions made, a CHP-plant of 4 MW-el with a thermal store participating in the spot market will be the most feasible plant to build. A sensitivity analysis shows to which extent the optimal solution will vary by changing the key economic assumptions.     

Energetic–exergetic-economic analyses of a cogeneration thermic power plant in Turkey

In present study the exergy and economical analysis of a cogeneration plant system in Turkey (Esenyurt Thermic Power Plant) was performed based on the measured data during the operation time of the system. First and second laws of thermodynamics are adapted to the measured data. Furthermore, fuel-utilization efficiency, rate of power heat and rate of process heat are determined. The system is considered as a steady-state open thermodynamic system.     

A theoretical study on a novel combined power and ejector refrigeration cycle

A new combined power and refrigeration cycle is proposed for the cogeneration, which combines the Rankine cycle and the ejector refrigeration cycle by adding an extraction turbine between heat recovery vapor generator (HRVG) and ejector. This combined cycle could produce both power output and refrigeration output simultaneously, and could be driven by the flue gas from gas turbine or engine, solar energy, geothermal energy and industrial waste heats. Parametric analysis and exergy analysis are conducted to examine the effects of thermodynamic parameters on the performance and exergy destruction in each component for the combined cycle. The results show that the condenser temperature, the evaporator temperature, the turbine inlet pressure, the turbine extraction pressure and extraction ratio have significant effects on the turbine power output, refrigeration output, exergy efficiency and exergy destruction in each component in the combined cycle. It is also shown that the biggest exergy destruction occurs in the heat recovery vapor generator, followed by the ejector and turbine.     

Bagasse saving and water recovery in cogeneration system using superheated steam dryer

The cogeneration system in sugar factory uses bagasse with high moisture content as the fuel for the boiler, which results in low boiler efficiency. The system also produces superheated steam, which is extracted from the turbine, and mixed with cooling water to produce saturated steam required by the evaporation system. The potential use superheated steam to reduce bagasse moisture content is ignored in the standard practice of the sugar factory. In this article, an investigation is made into the improvement of the cogeneration system by using superheated steam dryer to reduce the moisture content of bagasse. Mathematical models are developed for the typical system without superheated steam dryer and the improved system with superheated steam dryer. They are then used to compare the performances of both systems. It is found that, under the condition that the required steam flow rate for the evaporation process and the power output are the same, the improved system requires less bagasse consumption, and has larger energy utilization factor. In addition, water that would be lost with flue gases in the typical system is recovered in the improved system.     

Assessment of thermal performance improvement of GT-MHR by waste heat utilization in power generation and hydrogen production

The Gas Turbine Modular Helium Reactor (GT-MHR) uses two compression stages to compress the helium and a pre-cooler and an intercooler to reduce the compressors inlet temperature, that dissipate around 308.36 MW_th at the design operational conditions. This dissipated thermal energy can be used as an energy source to produce hydrogen. An energy analysis is conducted for a proposed system that includes GT-MHR combined with Organic Rankine Cycle (GT-MHR/ORC) and a Proton Exchange Membrane (PEM) electrolyzer (GT-MHR/ORC-PEM) for hydrogen production. The optimum operating parameters values of the new cycle are obtained using the Engineering Equation Solver (EES) software. Thermal efficiency has been improved from 48.6% for the simple GT-MHR cycle to 49.8% for the new combined (GT-MHR/ORC-PEM) cycle including hydrogen production at a rate of 0.0644 kg/s at the same operating conditions. However, the thermal efficiency for the combined GT-MHR/ORC was higher and reaches 50.68%. Moreover, a parametric study is carried out over a wide range of some operating conditions such as turbine inlet temperature, Compressor pressure ratio and compressor inlet temperature to investigate their effect on the new cycle performance. Results revealed that increasing the low-pressure compressor inlet temperature increases the amount of hydrogen produced while decreasing thermal efficiencies for the three cycles. Furthermore, increasing compressor pressure ratio reduces the mass flow rate of hydrogen produced util it reaches a minimum value then it starts to increase slightly, on the contrary, an opposite relationship is observed between thermal efficiencies and compressor pressure ratio. Moreover, at low compressor pressure ratio, the rate of hydrogen produced increases with increasing turbine inlet temperature; however, it decreases by increasing the turbine inlet temperature at high compressor pressure ratio. Nevertheless, a direct correlation is noticed between thermal efficiencies and turbine inlet temperature.     

Artificial neural networks and physical modeling for determination of baseline consumption of CHP plants

An effective modeling technique is proposed for determining baseline energy consumption in the industry. A CHP plant is considered in the study that was subjected to a retrofit, which consisted of the implementation of some energy-saving measures. This study aims to recreate the post-retrofit energy consumption and production of the system in case it would be operating in its past configuration (before retrofit) i.e., the current consumption and production in the event that no energy-saving measures had been implemented. Two different modeling methodologies are applied to the CHP plant: thermodynamic modeling and artificial neural networks (ANN). Satisfactory results are obtained with both modeling techniques. Acceptable accuracy levels of prediction are detected, confirming good capability of the models for predicting plant behavior and their suitability for baseline energy consumption determining purposes. High level of robustness is observed for ANN against uncertainty affecting measured values of variables used as input in the models. The study demonstrates ANN great potential for assessing baseline consumption in energy-intensive industry. Application of ANN technique would also help to overcome the limited availability of on-shelf thermodynamic software for modeling all specific typologies of existing industrial processes.     

Methodology for generating thermal and electric load profiles for designing a cogeneration system

Cogeneration will be always an important concept for energy conversion in the future, since it proposes to optimize the use of the energy resources. In the transformation of conventional systems for operation in the cogeneration mode, there exists the necessity to estimate the electric and thermal load profiles hour by hour, so that the cogeneration system can be optimally designed and thus displace the electric energy that would be used by the conventional systems. This work develops a methodology for estimating the electric and thermal load profiles, hour by hour for each month of the year, from the few normally available data. For the electric profile, annual consumption data of electric energy measured at PUC-Rio, every 15 min in the period of 1 year, has been used to validate this methodology. For the thermal profile, a methodology was developed; it discusses how the input thermal energy can be estimated from values of ambient temperature, internal thermal loads and solar radiation incident on the buildings. As an example of this methodology, a thermal load calculation is detailed for a business building and the results compared to those obtained from an existing methodology. The results obtained with these models, allow more accurate predictions for estimating the electric energy with a generator, over a month period, when its capacity is smaller than the building peak demand. A model was also developed to calculate the contribution of the air conditioning electric energy consumption to the total electric energy load.     

Combined heat and power economic emission dispatch using nondominated sorting genetic algorithm-II

This paper presents nondominated sorting genetic algorithm-II for solving combined heat and power economic emission dispatch problem. The problem is formulated as a nonlinear constrained multi-objective optimization problem. Nondominated sorting genetic algorithm-II is proposed to handle economic emission dispatch as a true multi-objective optimization problem with competing and noncommensurable objectives. The proposed algorithm is illustrated for two test systems and the test results are compared with those obtained from strength pareto evolutionary algorithm 2.