limits and potentials of mixed integer linear programming methods for optimization of polygeneration energy systems

Abstract The simultaneous production of different energy vectors from hybrid polygeneration plants is a promising way to increase energy efficiency and facilitate the development of distributed energy systems. The inherent complexity of polygeneration energy systems makes their economic, environmental and energy performance highly dependent on system synthesis, equipment selection and capacity, and operational strategy. Mixed Integer Linear Programming (MILP) is the state of the art approach to tackle the optimization problem of polygeneration systems. The guarantee of finding global optimality in linear problems and the effectiveness of available commercial solvers make MILP very attractive and widely used in optimization problems of polygeneration systems. Nevertheless, several drawbacks affect the MILP formulation, such as: the impossibility of taking into account nonlinear effects; the necessity of considering all the time periods at once; the risk of high-dimensionality of the problem. To tackle these limitations, several techniques have been developed, such as: piecewise linearization methods; rolling horizon approaches; dimensionality reduction by means of energy demands clustering algorithms. In this paper, limits and potentials of MILP methods for the optimization problem of polygeneration energy systems are reviewed and discussed

A methodology for designing flexible multi-generation systems

An FMG (flexible multi-generation system) consists of integrated and flexibly operated facilities that provide multiple links between the various layers of the energy system. FMGs may facilitate integration and balancing of fluctuating renewable energy sources in the energy system in a cost- and energy efficient way, thereby playing an important part in smart energy systems. The development of efficient FMGs requires systematic optimization approaches. This study presents a novel, generic methodology for designing FMGs that facilitates quick and reliable pre-feasibility analyses. The methodology is based on consideration of the following points: Selection, location and dimensioning of processes; systematic heat and mass integration; flexible operation optimization with respect to both short-term market fluctuations and long-term energy system development; global sensitivity and uncertainty analysis; biomass supply chains; variable part-load performance; and multi-objective optimization considering economic and environmental performance. Tested in a case study, the methodology is proved effective in screening the solution space for efficient FMG designs, in assessing the importance of parameter uncertainties and in estimating the likely performance variability for promising designs. The results of the case study emphasize the importance of considering systematic process integration when developing smart energy systems. (C) 2016 Elsevier Ltd. All rights reserved

Thermoeconomic and environmental optimization of polygeneration systems for small-scale residential buildingsintegrating thermal and electric energy storage, renewable energy and legal restrictions.

El sector residencial, responsable del 27% del consumo energético mundial y 17% de emisiones de gases de efecto invernadero aproximadamente, desempeña un papel clave para combatir el cambio climático. Por esto, el uso de sistemas de poligeneración resulta una alternativa apropiada para cubrir las demandas energéticas de los edificios, ya que permiten un uso eficiente de los recursos naturales con un bajo impacto ambiental. En este sentido, esta tesis ha desarrollado un modelo de programación lineal entera mixta (MILP) para investigar estos sistemas de forma sistemática, integrando tecnologías renovables, como la solar y eólica, con almacenamiento de energía térmica y eléctrica, considerando equipos comerciales, teniendo en cuenta aspectos económicos y ambientales en el diseño. La investigación comienza por la forma de abordar el proceso de optimización, partiendo por la elección del método para seleccionar días representativos. Comparando diferentes métodos, se demuestra que su idoneidad depende en gran medida de la variabilidad de las series temporales involucradas en el sistema analizado. Además, se ha desarrollado un nuevo método que mejora los resultados del proceso de optimización. Por otro lado, se ha estudiado la viabilidad del uso de edificios residenciales como microrred. El estudio muestra que resultan rentables con respecto a los sistemas energéticos convencionales actuales, pero es necesario la aplicación de incentivos o permitir la venta de electricidad a un precio razonable para que sean competitivos. Adicionalmente, se han estudiado e identificado sinergias entre los componentes del sistema energético gracias al desarrollo de un modelo termoeconómico, que muestran la importancia de abordar el diseño de los sistemas energéticos considerando conjuntamente tecnologías térmicas y eléctricas, destacando la bomba de calor y los acumuladores de energía como tecnologías claves para lograr soluciones más económicas y sostenibles. Finalmente, se han aplicado las últimas regulaciones españolas de autoconsumo para evaluar su impacto económico y ambiental en el diseño de sistemas energéticos. Además, a través de la aplicación de la optimización multiobjetivo, se analizó si la reciente regulación de autoconsumo se ajusta a las metas europeas e internacionales para combatir el cambio climático. Asimismo, se estudia cómo podría abordarse la regulación para promover el desarrollo de sistemas energéticos sostenibles para el sector residencial. Los resultados sugieren actuar sobre la regulación de autoconsumo para reducir el impacto ambiental de forma efectiva. En general, esta tesis proporciona metodologías e ideas útiles para el diseño de sistemas energéticos sostenibles capaces de cubrir las demandas de energía de los edificios residenciales.The residential sector, responsible of about 27% of the global energy consumption and 17% of the greenhouse gas emissions, plays a key role in the action to combat climate change. In this sense, polygeneration systems could be considered a suitable alternative to attend the energy demands of residential buildings since they enable an efficient use of natural resources with a low environmental impact. This thesis developed a Mixed Integer Linear Programming (MILP) model to research these kind of systems in a systematic way to integrate renewable energy such as solar and wind energy with thermal and electric energy storage, considering commercial equipment for small-medium scale residential buildings, taking into account both economic and environmental aspects for the optimal design of such systems. The research starts from the suitable way to address the optimization process focused on the selection of the method to select representative days. Through the comparison of different methods, it was demonstrated that its right selection strongly depends on the variability of the time series involved in the analysed system. Besides, a new method was developed in order to improve the results of the optimization process. The developed MILP model was applied to study the feasibility of residential buildings as a microgrid. This innovative approach was found profitable with respect to the current conventional energy systems but it is necessary the application of feed-in tariff schemes or allowing the sale of electricity at reasonable price in order to make them competitive. Further, a thermoeconomic analysis was carried out to evaluate synergies between the components of the energy system. It was shown the importance of considering both thermal and electrical parts in the design of energy systems, highlighting the role of heat pumps and energy storage as key technologies, to achieve more cost-effective and sustainable solutions. Finally, the recent Spanish self-consumption regulations were applied to evaluate its impact on the design of energy systems. Moreover, through the application of multiobjective optimization and the analysis of different trade-off solutions was evaluated if this regulation aligned with European and international goals to combat climate change, and how it could be addressed in order to promote the design of affordable sustainable energy supply systems for the residential buildings. The obtained results suggest to act on the self-consumption regulation in order to achieve more significant reduction of greenhouse gas emissions. Overall, this thesis provided methodologies and useful insights for the design of sustainable energy systems for residential buildings.<br /

liquid air energy storage as a polygeneration system to solve the unit commitment and economic dispatch problems in micro grids applications

Abstract Storage technologies play a crucial role in polygeneration plants that attempt to integrate power, thermal and cooling energy systems in order to maximize process efficiency and reduce operating cost. With the increasing penetration of renewable energy into the plant, storage technologies help to dampen the intermittency problem in their energy supply whilst at the same time perform peak shaving to reduce primary energy consumption, thus mitigating pollutant emission. Among the various storage technologies, Liquid Air Energy Storage (LAES) have gathered research interest due to its capability of simultaneously producing electrical and cooling power. Furthermore, unlike Electrochemical Energy Storage (EES) technologies, the LAES lifetime is not heavily dependent on its duty cycle, thus allowing for a calendar life twice or thrice that of EES. In this paper, the economic dispatch of an Eco-building in Singapore has been evaluated using a mixed-integer quadratic programming solver by comparing the adoption of EES and LAES within a capacity range of 300kWh-2000kWh. At the higher end of the capacity range, the LAES configuration results in a higher Net Present Value after 20 years and a shorter time period to obtain the Return of Investment compared to that of EES. At the lower capacity range, both technologies give similar financial returns. Analysis of the results show LAES to be a promising technology to compete with EES in the context of a polygeneration plant and further technology integration is discussed

Tackling thermal integration in the synthesis of polygeneration systems for buildings

A novel methodology is proposed for the synthesis of polygeneration systems in tertiary sector buildings with detailed thermal integration. The methodology involves a systematic approach that combines Pinch Analysis, mathematical programming, and the definition of a superstructure with thermal flexibility whereby mass flows can exchange heat in various temperature intervals. With the detailed characterization of the thermal energy flows associated with the thermal energy technologies and services to be supplied to the building, the optimization procedure provides a more realistic system configuration, ensures that thermodynamic principles are satisfied, and allows for synergies and potential benefits to emerge. The methodology is first introduced through a simple example of a gas engine-based energy system, highlighting the necessity of a detailed characterization of the hot and cold flows regarding their quantity and quality levels. Then, the approach is applied to the case study of a Brazilian university hospital that requires electricity, steam, hot water, and chilled water. The optimization is formulated as a multi-period mixed integer linear programming model that minimizes the total annual cost of installing and operating the system using local-based data. The results show the technical and economic interest of deploying cogeneration gas engines to cover electricity and thermal energy services. Besides, a strong synergy is observed between the cogeneration gas engine and the single-effect absorption chiller. Thus, it is demonstrated how a preliminary analysis of thermal integration opportunities must be an integral part of the optimal synthesis of energy supply systems

planning tool for polygeneration design in microgrids

Abstract This work suggests a methodology to assist the designer during the planning phase of microgrids and eco-districts. A mixed integer linear programming model is designed to mathematically describe the different energy systems and the physical relations among them. Given the different electrical/thermal demand profiles, the micro grid's topology and a set of boundary conditions, the model can identify the optimum mix of (poly-)generation units and energy storage systems, as well as the necessary district heating/cooling infrastructure. Both economic and energetic cost functions are defined to explore the problem from different perspectives. The described tool is applied to study an actual district of the NTU campus in Singapore, comprising 5 multi-purpose buildings and a district cooling network supplied by centralized electrical chillers. The planning tool was run to assess the optimal configuration that minimizes the overall cost (initial investment and OM the outcome results presented a layout and a mix of energy systems different from the present one. In particular, the optimal configuration results to be a district cooling system served by a mix of electrical chiller plant, trigeneration distributed energy system and sensible cold thermal energy storage

Optimization of a small-scale polygeneration system for a household in Turkey

With environmental concerns, alternative solutions for generating electricity while decreasing the consumption of fossil fuels have gained a great importance. Polygeneration is one of these solutions which is also capable to increase the technical performance of electricity generation. Polygeneration systems are available in large scale, medium scale and small scale. This study focuses on small scale polygeneration systems specifically for residential applications. Type and size of the components and the system’s operational strategy plays a significant role in polygeneration system design as these factors affect the system cost and also environmental impacts. This study aims to propose a guide for component selection, sizing and addressing a suitable operational strategy for a predefined system configuration. Decision making criteria is defined for component selection by a comprehensive literature review. Internal combustion engines, Stirling engines, micro gas turbines and fuel cells are investigated within these criteria. This provides the user an insight on component selection. When combined with factors such as market conditions, location and especially household demand profile, a selection can easily be made by the customer. For component sizing and operational strategy, a model has been implemented in Matlab. A baseline case model with a predefined system configuration and operational strategy was defined. The baseline case system includes a prime mover, a back-up auxiliary boiler, a vapor compression refrigeration chiller, a thermal energy storage and solar thermal collectors for the domestic hot water demand. The operational strategy is defined as thermal load following. For the case study, this model was altered for different cases with alterations on the operational strategy and the system configuration in order to identify the optimal solution for the user where the total annual cost is minimized while satisfying all kinds of end-use demands of a single-family household in Ankara, Turkey. The results also give insights on the effect of having solar thermal collectors and a thermal energy storage coupled with a CHP unit on the overall system

An integrated simulation tool proposed for modeling and optimization of CHP units

Master's thesis in Petroleum engineeringIn this project, a novel framework for CHP optimization is proposed. The objective of the study was to develop an automatic optimization tool based on the integration of IPSEpro simulation software and MATLAB programming environment. The data exchange between these components was organized via COM interface. An experimentally validated model of the commercial AET100 CHP unit was utilized. The CHP was considered as a part of a grid. Therefore electricity trading possibility was taken into account. The system was extended to polygeneration by implementing a solar panel as an additional power source. The objective was to minimize the cost function, which consists of operational and capital investments costs, under a set of constraints. For solving the problem, the Genetic Algorithm was applied. As an addition to the study, two other algorithms (Particle Swarm Optimization and Differential Evolution) were also tested. The applying a tool to real data was not considered in the project. However, an optimization was done for test data to show the performance of a developed framework. The test optimization was done for the 24-hours period in July and December, with different electricity and gas price profiles and various ambient conditions. The obtained results were analyzed in details. It was shown that the proposed optimization tool provides appropriate results. It is flexible and has a good potential to be further extended and developed

Polygeneration system optimization for building energy system retrofit: A case of study for TR5 building of UPC-Terrassa

The building sector represents around one-third of the energy related to the EU CO2 eq emissions, which makes it a crucial sector for achieving the EU’s energy and environmental goals. Thus, the EU has established a legislative framework to foster, among others, the modernisation of the existing building stock through a better energy system integration. In this sense, bearing in mind the needs of energy system retrofit of the public buildings in Spain, this paper carried out a thorough analysis of different trade-off solutions obtained from the multiobjective optimization of a polygeneration system for the TR5 building of the Polytechnic University of Catalunya. The results highlight the selection of PV panels, cogeneration modules and life Li-Ion batteries, among others, to achieve cost-effective and sustainable energy systems. By covering the available area, 2000 , the PV panels attend about 23% of the electricity required for the building. On the other hand, considering the current geopolitical tensions, it presents a potential configuration that allows to cut off the natural gas consumption reducing about 6% the current cost. The study was carried out by using a Mixed Integer Linear Programming model maximizing the Net Present Value of the project considering the environmental impact

Design of affordable sustainable energy supply systems for residential buildings: A case study

The residential sector plays an important role to mitigate climate change due to its high energy consumption. Polygeneration systems are a suitable alternative enabling efficient use of natural resources with low environmental impact. However, their deployment depends, among other factors, on the economic cost and the legal restrictions. This work analyses the potential reduction of greenhouse gases emissions, expressed in CO2 -equivalent emissions (CO2eq), in residential buildings installing polygeneration systems and considering the current Spanish self-consumption regulation. This is achieved through a multiobjective optimization, applying a Mixed Integer Linear Programming model, considering economic, environmental and legal aspects. Obtained results provide interesting replicable lessons, and show the interest of collective installations, in which remarkable CO2eq emissions reductions, above 65% with respect to conventional systems, can be achieved at an affordable cost. Technologies such as photovoltaic, reversible heat pumps, biomass and thermal energy storage are competitive when properly integrated. Furthermore, the sale of renewable electricity to the grid under a net-billing scheme, with suitable electricity sale prices, is an appropriate approach, aligned with the European climate and energy policy. Nevertheless, the current Spanish self-consumption regulation is mostly appropriate for small-medium size residential buildings