Waste Heat Recovery Systems: Numerical and Experimental Analysis of organic Rankine Cycle Solutions

This thesis aims to present the ORC technology, its advantages and related problems. In particular, it provides an analysis of ORC waste heat recovery system in different and innovative scenarios, focusing on cases from the biggest to the lowest scale. Both industrial and residential ORC applications are considered. In both applications, the installation of a subcritical and recuperated ORC system is examined. Moreover, heat recovery is considered in absence of an intermediate heat transfer circuit. This solution allow to improve the recovery efficiency, but requiring safety precautions. Possible integrations of ORC systems with renewable sources are also presented and investigated to improve the non-programmable source exploitation. In particular, the offshore oil and gas sector has been selected as a promising industrial large-scale ORC application. From the design of ORC systems coupled with Gas Turbines (GTs) as topper systems, the dynamic behavior of the GT+ORC innovative combined cycles has been analyzed by developing a dynamic model of all the considered components. The dynamic behavior is caused by integration with a wind farm. The electric and thermal aspects have been examined to identify the advantages related to the waste heat recovery system installation. Moreover, an experimental test rig has been realized to test the performance of a micro-scale ORC prototype. The prototype recovers heat from a low temperature water stream, available for instance in industrial or residential waste heat. In the test bench, various sensors have been installed, an acquisitions system developed in Labview environment to completely analyze the ORC behavior. Data collected in real time and corresponding to the system dynamic behavior have been used to evaluate the system performance based on selected indexes. Moreover, various operational steady-state conditions are identified and operation maps are realized for a completely characterization of the system and to detect the optimal operating conditions.

Prestazioni energetico-ambientali di sistemi cogenerativi avanzati e analisi di casi applicativi

Lo scopo di questa tesi è quello di analizzare dapprima l’impatto ambientale di tali impianti e poi analizzare il contributo effettivo che oggi la tecnologia innovativa dei cicli Rankine organici può dare nella valorizzazione elettrica del calore di scarto di processi industriali, focalizzando l’obiettivo principalmente sulle turbine a gas ed eseguendo un caso di studio in un settore ancora poco esplorato da questa tecnologia, quello Oil&Gas. Dopo aver effettuato il censimento degli impianti a fonti fossili e rinnovabili, cogenerativi e non, presenti in Emilia-Romagna, è stato sviluppato un software chiamato MiniBref che permette di simulare il funzionamento di una qualsiasi centrale termoelettrica grazie alla possibilità di combinare la tecnologia dell’impianto con il tipo di combustibile consentendo la valutazione delle emissioni inquinanti ed i potenziali di inquinamento. Successivamente verranno illustrati gli ORC, partendo dalle caratteristiche impiantistiche e termodinamiche fino ad arrivare alla scelta del fluido organico, fondamentale per le performance del ciclo. Dopo aver effettuato una ricognizione dello stato dell’arte delle applicazioni industriali degli ORC nel recupero termico, verranno eseguite simulazioni numeriche per ricostruire gli ORC ed avere una panoramica il più completa ed attendibile delle prestazioni effettive di questi sistemi. In ultimo verranno illustrati i risultati di un caso di studio che vede l’adozione di recupero mediante ciclo organico in un’installazione esistente del settore Oil&Gas. Si effettuerà uno studio delle prestazione dell’impianto al variare delle pressioni massime e minime del ciclo ed al variare del fluido impiegato al fine di mostrare come questi parametri influenzino non solo le performance ma anche le caratteristiche impiantistiche da adottare. A conclusione del lavoro si riporteranno i risultati relativi all’analisi condotte considerando l’impianto ai carichi parziali ed in assetto cogenerativo.

Exact and heuristic algorithms for the integrated planning of multi-energy systems

The aim of this thesis is to present exact and heuristic algorithms for the integrated planning of multi-energy systems. The idea is to disaggregate the energy system, starting first with its core the Central Energy System, and then to proceed towards the Decentral part. Therefore, a mathematical model for the generation expansion operations to optimize the performance of a Central Energy System system is first proposed. To ensure that the proposed generation operations are compatible with the network, some extensions of the existing network are considered as well. All these decisions are evaluated both from an economic viewpoint and from an environmental perspective, as specific constraints related to greenhouse gases emissions are imposed in the formulation. Then, the thesis presents an optimization model for solar organic Rankine cycle in the context of transactive energy trading. In this study, the impact that this technology can have on the peer-to-peer trading application in renewable based community microgrids is inspected. Here the consumer becomes a prosumer and engages actively in virtual trading with other prosumers at the distribution system level. Moreover, there is an investigation of how different technological parameters of the solar Organic Rankine Cycle may affect the final solution. Finally, the thesis introduces a tactical optimization model for the maintenance operations’ scheduling phase of a Combined Heat and Power plant. Specifically, two types of cleaning operations are considered, i.e., online cleaning and offline cleaning. Furthermore, a piecewise linear representation of the electric efficiency variation curve is included. Given the challenge of solving the tactical management model, a heuristic algorithm is proposed. The heuristic works by solving the daily operational production scheduling problem, based on the final consumer’s demand and on the electricity prices. The aggregate information from the operational problem is used to derive maintenance decisions at a tactical level.