EXERGETIC AND THERMOECONOMIC APPROACH FOR OPTIMAL PLANNING OF DISTRICT ENERGY SYSTEMS

A sustainable urban energy planning for achieving the EU 2020 and 2050 energy goals requires adopting a systemic approach based on reducing end-user energy requirements, recycling energy that otherwise would be wasted and replacing fossil fuels by renewable. District Heating and District Cooling play a key role in such a concept. From the sustainability viewpoint, district heating is an important option to supply heat to the users in urban areas. The energy convenience of such option depends on the annual energy request, the population density and the efficiency in heat production. Among the alternative technologies, geothermal heat pumps (both open loop and closed loop heat pumps) play a crucial role. In order for the DHN to remain an effective solution with respect to alternative technologies, the optimal configuration, design and operation must be investigated. This thesis aims to propose a methodology for the Multiobjective Optimizations of district heating networks, where the objective functions (the minimum specific primary energy consumption or the minimum economic cost) of a district heating network are investigated using a thermoeconomic based probabilistic procedure. A procedure, derived from Simulating Annealing optimization technique, to select which users in a urban area should be connected with a district heating network and which ones should be heated through an alternative technology is proposed. The goal of this procedure is to reach a globally optimal system from the energy and economic viewpoints. The procedure proposes district heating as the initial choice for all the users. The users are then progressively disconnected to the network, according with the primary energy required to supply them heat, and the alternative technology is considered for disconnected users. Here, ground water heat pump and condensing boilers are considered as the alternative technologies. The optimization technique developed in this PhD thesis develops the three levels of the optimization of energy systems: - Development of a Synthetic Method: The optimal synthesis is performed though a method which starts with a superstructure (where all the buildings (users) in the considered area for the expansion of DH network are supplied by district heating network) and then reduced to the optimal configuration (some of the users are disconnected from the DHN and supplied with an alternative technology such as geothermal heat pumps or condensing boilers). - Development of Optimal Design Method for the components and the properties at the nominal load selected in order to reach optimal performances: - as the users are disconnected from the district heating network, the mass flow rate flowing in the pipes is reduced resulting in different pipe diameters in comparison to the initial configuration. The optimal value velocity in the pipes is obtained as a function of the pipe diameters; - The cogeneration ratio (the ratio between the thermal power of the CHP appliances and the total thermal power installed in the power station ) has been considered as a parameter in the optimal design of the system. - Development of Optimal Operating properties: the operating properties under specific conditions has been changed, like the operating supply temperatures, but also the evolution of the network during its construction is considered. The application to an Italian town is considered as a test case. The main advantage of this procedure is that complex networks, like the DHN in Casale Monferrato characterized by 198 users, grouped in 21 macrozones, can be easily processed. The optimal configuration of the overall urban heating system is obtained. This configuration corresponds to the minimum primary energy request to supply heat to all the users (those connected to the network and those using an alternative heating system). After a brief introduction where the district heating technology is presented, the Thesis is divided in two parts: the first parts introduces the methodological approach proposed for the optimization of a District heating network, together with the description of the optimization model. The second part focuses on a specific application case, showing the preliminary operations required for the application of the model and the results obtained from the optimizations performed. The results have been interpreted trying to reach a more general conclusion which is not related only to the specific case stud

Performance potential of ORC architectures for waste heat recovery taking into account design and environmental constraints

The subcritical ORC (SCORC), sometimes with addition of a recuperator, is the de facto state of the art technology in the current market. However architectural changes and operational modifications have the potential to improve the base system. The ORC architectures investigated in this work are: the transcritical ORC (TCORC), the triangular cycle (TLC) and the partial evaporation ORC (PEORC). Assessing the potential of these cycles is a challenging topic and is brought down to two steps. First, the expected thermodynamic improvement is quantified by optimizing the second law efficiency. Secondly, the influences of technical constraints concerning volumetric expanders are investigated. In the first step, simple regression models are formulated based on an extensive set of boundary conditions. In addition a subset of environmentally friendly working fluids is separately analysed. In the second step, two cases are investigated with the help of a multi-objective optimization technique. The results of this optimization are compared with the first step. As such the effect of each design decision is quantified and analysed, making the results of this work especially interesting for manufacturers of ORC systems

IEA ECES Annex 31 Final Report - Energy Storage with Energy Efficient Buildings and Districts: Optimization and Automation

At present, the energy requirements in buildings are majorly met from non-renewable sources where the contribution of renewable sources is still in its initial stage. Meeting the peak energy demand by non-renewable energy sources is highly expensive for the utility companies and it critically influences the environment through GHG emissions. In addition, renewable energy sources are inherently intermittent in nature. Therefore, to make both renewable and nonrenewable energy sources more efficient in building/district applications, they should be integrated with energy storage systems. Nevertheless, determination of the optimal operation and integration of energy storage with buildings/districts are not straightforward. The real strength of integrating energy storage technologies with buildings/districts is stalled by the high computational demand (or even lack of) tools and optimization techniques. Annex 31 aims to resolve this gap by critically addressing the challenges in integrating energy storage systems in buildings/districts from the perspective of design, development of simplified modeling tools and optimization techniques

Selected Papers from SDEWES 2017: The 12th Conference on Sustainable Development of Energy, Water and Environment Systems

EU energy policy is more and more promoting a resilient, efficient and sustainable energy system. Several agreements have been signed in the last few months that set ambitious goals in terms of energy efficiency and emission reductions and to reduce the energy consumption in buildings. These actions are expected to fulfill the goals negotiated at the Paris Agreement in 2015. The successful development of this ambitious energy policy needs to be supported by scientific knowledge: a huge effort must be made in order to develop more efficient energy conversion technologies based both on renewables and fossil fuels. Similarly, researchers are also expected to work on the integration of conventional and novel systems, also taking into account the needs for the management of the novel energy systems in terms of energy storage and devices management. Therefore, a multi-disciplinary approach is required in order to achieve these goals. To ensure that the scientists belonging to the different disciplines are aware of the scientific progress in the other research areas, specific Conferences are periodically organized. One of the most popular conferences in this area is the Sustainable Development of Energy, Water and Environment Systems (SDEWES) Series Conference. The 12th Sustainable Development of Energy, Water and Environment Systems Conference was recently held in Dubrovnik, Croatia. The present Special Issue of Energies, specifically dedicated to the 12th SDEWES Conference, is focused on five main fields: energy policy and energy efficiency in smart energy systems, polygeneration and district heating, advanced combustion techniques and fuels, biomass and building efficiency

Thermodynamic and economic analysis of performance evaluation of all the thermal power plants : a review

Surging in energy demand makes it necessary to improve performance of plant equipment and optimize operation of thermal power plants. Inasmuch as thermal power plants depend on fossil fuels, their optimization can be challenging due to the environmental issues which must be considered. Nowadays, the vast majority of power plants are designed based on energetic performance obtained from first law of thermodynamic. In some cases, energy balance of a system is not appropriate tool to diagnose malfunctions of the system. Exergy analysis is a powerful method for determining the losses existing in a system. Since exergy analysis can evaluate quality of the energy, it enables designers to make intricate thermodynamic systems operates more efficiently. These days, power plant optimization based on economic criteria is a critical problem because of their complex structure. In this study, a comprehensive analysis including energy, exergy, economic (3-E) analyses, and their applications related to various thermal power plants are reviewed and scrutinized.The National Natural Science Foundation of China, Hubei Provincial Natural Science Foundation of China, Key Project of ESI Discipline Development of Wuhan University of Technology and the Scientific Research Foundation of Wuhan University of Technology.https://onlinelibrary.wiley.com/journal/20500505am2020Mechanical and Aeronautical Engineerin

Design and Algorithm-based optimisation of Axial ORC turbine and transient cycles incorporating novel machine Learning tools

The flue gas stacks of industrial steam boilers can be considered an untapped waste heat source, which is characterised as highly intermittent. Although Organic Rankine Cycles pose strong potential to reuse such low-grade heat, the component and system levels analysis of ORCs to efficiently utilise these highly intermittent heat sources in a techno-economic fashion is still an unanswered research question. Such a holistic approach ultimately expedites the commercial adoption of ORCs to utilise a broader range of waste heat sources achieving the highest possible techno-economic benefits. To answer this research question, emphasising scale ORCs that employ axial flow turbines owing to their scalability and superior isentropic efficiency, this thesis undertakes turbine and cycle configuration optimisation by integrating the Craig and Cox loss model to simulate a small-scale axial flow ORC turbine. The transient waste heat of an actual industrial steam boiler stack was employed as a heat source to investigate ten novel cycle configurations. The optimisation was undertaken using parametric, metaheuristic (nature-inspired) and mathematics-based optimisers. Artificial Neural Networks (ANNs) and genetic algorithms (GAs)-based on the loss model led to an optimised turbine configuration that improved turbine total-to-static efficiency and cycle efficiency by 5.2% and 0.24%, respectively. The recuperative cycle proved the optimal thermodynamic configuration, with a 26.5% increase in mean power generation. Furthermore, a multi-objective analysis revealed the recuperative cycle integrated with an air preheater as the optimum thermo-economic configuration, with a 48.9% improvement in the combined overall value of the multiple objectives, including the Specific Investment Cost and mean power, achieving the final payback within 1.72 years. The ideal configuration was observed as a strong function of the Levelized cost of fuel and electricity prices. Application of a mathematical technique based on the non-linear programming by quadratic Lagrangian algorithm was validated for single- and multi-objective cycle configuration optimisations, providing results comparable to the well-established metaheuristic-based genetic algorithm, with a computational efficiency of greater than one order of magnitude. The overall approach of the direct loss model, artificial neural network- and genetic algorithm-based turbine optimisation, parametric cycle pre-optimisation, mathematical technique-based component optimisation and payback evaluation can be considered a blueprint for the future evaluation and design of organic Rankine cycles utilising transient waste heat sources

Optimization of a multi-generation power, desalination, refrigeration and heating system

The optimization of a multi-generation system which represents the integrated dual-purpose desalination plant and a low-scale absorption refrigeration system is addressed. A nonlinear mathematical programming optimization model that integrates a natural gas combined-cycle, a multi-effect distillation desalination plant, a series flow double-effect water-lithium bromide absorption refrigeration system, and a water heater, is developed based on first-principle models. The model is implemented in General Algebraic Modelling System and a generalized gradient-based optimization algorithm is used. Given design specifications for electricity generation (around 37 MW), freshwater production (100 kg/s), refrigeration capacity (2 MW), and thermal load for heating (around 0.7 MW of hot water), the integrated system is optimized by minimizing two objective functions by single-objective optimization: total heat transfer area and total annual cost. As a result, minimum total heat transfer area values of 39148 m2, 36002 m2, and 35161 m2 are obtained when 4, 5, and 6 distillation effects were considered in the multi-effect distillation system, respectively. Also, a minimum annual cost of around 24 MM$/yr. is obtained for 5 distillation effects. The influence of the number of effects in the multi-effect distillation subsystem on the optimal solutions is analyzed. Cost-effective optimal solutions are developed for the studied multi-generation system.Fil: Pietrasanta, Ariana Milagros. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo y Diseño. Universidad Tecnológica Nacional. Facultad Regional Santa Fe. Instituto de Desarrollo y Diseño; ArgentinaFil: Mussati, Sergio Fabian. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo y Diseño. Universidad Tecnológica Nacional. Facultad Regional Santa Fe. Instituto de Desarrollo y Diseño; ArgentinaFil: Aguirre, Pio Antonio. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo y Diseño. Universidad Tecnológica Nacional. Facultad Regional Santa Fe. Instituto de Desarrollo y Diseño; ArgentinaFil: Morosuk, Tatiana. Technishe Universitat Berlin; AlemaniaFil: Mussati, Miguel Ceferino. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo y Diseño. Universidad Tecnológica Nacional. Facultad Regional Santa Fe. Instituto de Desarrollo y Diseño; Argentin

Energetic analysis and optimal design of a CHP plant in a frozen food processing factory through a dynamical simulation model

The proper design of cogeneration plants requires the choice of the technologies that best fits the ratio between heating and power loads. In this paper, a dynamical procedure of selecting and dimensioning a cogeneration plant, using deep and detailed energy, exergy and economic analysis of the entire production process of a frozen food production factory is proposed. The results highlight that a design method, based on a dynamic simulation, optimizes the energy efficiency of the food processing plant involved in the experimental test. Indeed, by considering the overall efficiency of the CHP + National grid system, the energy efficiency is 6% higher in the case of dynamic compared to a static design, resulting in better overall use of resources with a possible lower level of environmental impact. Moreover, the CHP plant designed with the proposed method generates electrical energy which appropriately matches that required by the process, with a surplus/deficit less than 4%, while the classic method never covers the amount required and results in a deficit greater than 20%. Finally, the annual savings of the solution derived from the dynamic method is 12% higher than that obtained with a traditional design technique. Considering the greater absolute cost of the cogeneration plant, this dynamic approach results in more profitable annual investment margins for the company

Performance evaluation of organic Rankine cycle architectures : application to waste heat valorisation

In our society, there is an ever increasing need for electricity. However, today most of the electricity is generated by burning fossil fuels in a thermal power plant. A proposed alternative is to make use of low temperature heat from renewable sources (geothermal and solar) or waste heat (excess heat that is dumped into the atmosphere) in an organic Rankine cycle (ORC) to generate electricity. The purpose of the presented work is to support further adoption of ORC technology. To achieve this, two main challenges need to be resolved. First, sound criteria should be devised to compare and size ORCs and secondly the performance of the ORC should be increased further. From literature it is clear that novel ORC architectures have the opportunity to increase the performance of the basic subcritical ORC. However these studies are not cross comparable. As such, a new screening approach is created which rigorously compares and quantifies the potential of three different ORC architectures. Secondly, the sizing and the financial appraisal of the ORC is tackled by introducing a multi-objective optimization which combines financial and thermodynamic criteria in the optimization objectives. Finally, experimentally validated part-load models of the ORC were developed. These part-load models are crucial to predict the actual power output of time varying heat sources like waste heat streams. In addition, the models permit to investigate the concept of retrofitting existing subcritical ORCs to work under the more optimal working regime of partial evaporation