Thermoeconomic and environmental synthesis and optimization of polygeneration systems supported with renewable energies and thermal energy storage applied to the residential-commercial sector

<br /

Advanced Model Predictive Control Solutions for Performance Enhancement of Food Service Appliances

This work is done in collaboration with Prof. Felice Andrea Pellegrino and Prof. Gianfranco Fenu of the University of Trieste, my colleague Ph.D. Francesco Forte and my place of work in the AD\&T Laboratory at Electrolux Professional Group. The purpose of this research is the design of a control system with the aim of improving the performance of professional appliances dedicated to the food processing in order to meet the objectives of energy saving and culinary quality. Furthermore, it is necessary to design real-time control software that is able to predict the behavior of the device, estimate non-measurable physical quantities, respect the constraints on energy consumption imposed a priori, reduce the effect of delay response with the aim of having smarter and more robust solutions. Therefore, we apply the model predictive control (MPC) strategy in an industrial setting, specifically for controlling the temperature of Oven Professional Appliances. The workflow includes identifying and validating a model of the cell temperature and incorporating disturbance models. MPC is implemented using a state-space formulation. The proposed method shows significant energy saving and error tracking reduction with respect to the current oven control; its effectiveness has been demonstrated through several tests carried out on a professional oven.This work is done in collaboration with Prof. Felice Andrea Pellegrino and Prof. Gianfranco Fenu of the University of Trieste, my colleague Ph.D. Francesco Forte and my place of work in the AD\&T Laboratory at Electrolux Professional Group. The purpose of this research is the design of a control system with the aim of improving the performance of professional appliances dedicated to the food processing in order to meet the objectives of energy saving and culinary quality. Furthermore, it is necessary to design real-time control software that is able to predict the behavior of the device, estimate non-measurable physical quantities, respect the constraints on energy consumption imposed a priori, reduce the effect of delay response with the aim of having smarter and more robust solutions. Therefore, we apply the model predictive control (MPC) strategy in an industrial setting, specifically for controlling the temperature of Oven Professional Appliances. The workflow includes identifying and validating a model of the cell temperature and incorporating disturbance models. MPC is implemented using a state-space formulation. The proposed method shows significant energy saving and error tracking reduction with respect to the current oven control; its effectiveness has been demonstrated through several tests carried out on a professional oven

Systematic approaches for synthesis, design and operation of biomass-based energy systems

A biomass-based energy system (BES) is a utility facility which produces cooling, heat and power simultaneously from biomass. By having a BES installed on-site, industrial processes can reduce energy costs by locally producing heat, cooling and power for process and work place requirements. However, several barriers have hindered development of BESs in the energy industry. These barriers include doubts over its operational uncertainties (e.g., seasonal biomass supply, equipment reliability, etc.), the misconception that generating energy from biomass is only a marginal business and the lack of successful cooperative partnerships within the industry. According to literature, such barriers are due to the lack of frameworks that address design aspects and demonstrate the economic viability of a BES. This thesis presents systematic approaches and frameworks to design a BES. These approaches emphasise on integrating synthesis, design and operation decision making for a BES during its preliminary design phase. Firstly, a systematic approach is presented to synthesise a BES considering seasonal variations in biomass supply and energy demand. In this approach, a multi-period optimisation model is formulated to perform technology and design capacity selection by considering seasonal variations in biomass supply and energy demand profiles. This approach is then extended to systematically allocate equipment redundancy within the BES in order to maintain a reliable supply of energy. In this approach, k-out-of-m system modelling and the principles of chance-constrained programming are integrated in a multi-period optimisation model to simultaneously screen technologies based on their respective equipment reliability, capital and operating costs. The model also determines equipment capacities, along with the total number of operating (and stand-by) equipment based on various anticipated scenarios in a computationally efficient manner. Following this, a systematic approach is developed to simultaneously screen, size and allocate redundancy within a BES considering its operational strategies (e.g., following electrical load or following thermal load). Subsequently, a systematic framework on Design Operability Analysis (DOA) is developed to analyse BES designs in instances of failure. This framework provides a stepwise procedure to evaluate proposed BES designs under scenarios of disruption and analyse their true feasible operating range. Knowledge of the feasible operating range enables designers to determine and validate if a BES design is capable of meeting its intended operations. Following this, a systematic Design Retrofit Analysis (DRA) framework is presented to debottleneck and retrofit existing BES designs in cases where energy demands are expected to vary in the future. The presented framework re-evaluates an existing BES design under disruption scenarios and determines its real-time feasible operating range. The real-time feasible operating range will allow designers to determine whether debottlenecking is required. If debottlenecking is required, the framework provides systematic debottlenecking and retrofit guidelines for BES designs. The design of a BES is then extended further to consider its interaction in an eco-industrial park (EIP). Since heat, cooling and power are essentially required in most industrial processes, a BES can be more economically attractive if synthesised for an EIP. As such, an optimisation-based negotiation framework is developed to analyse the potential cost savings allocation between participating plants in an EIP coalition. This framework combines the principles of rational allocation of benefits with the consideration of stability and robustness of an EIP coalition to changes in cost assumptions. Lastly, possible extensions and future opportunities for this research work are highlighted at the end of this thesis

The role of the energy performance modelling with a view to low energy buildings

Climate change requires courageous choices, the European Union has accepted this challenge. One of the 2050 European low-carbon targets is energy savings in the building sector which is responsible for around 40% of energy consumption and 36% of CO2 emissions in the EU. The role of Building Performance Simulation (BPS) is central in that it allows to improve the design, optimization, construction, operation and maintenance of new and existing buildings. In order to achieve the correct estimate of energy consumption of buildings, different models have been developed in the last decades. They can be grouped into three categories: black box models, gray box models and white box models. They are differentiated by the degree of detail with which they describe the physical phenomena that govern the calculation of energy performance instead of using statistical algorithms for the estimation of the same or some characteristics of the building. However, the most detailed models are still only a representation of reality and therefore with margins of error due to assumptions and approximations of calculation. These aspects could be critical in the estimation of energy performance of nearly Zero Energy Buildings (nZEBs) where low performance values could become comparable with errors in estimating energy performances themselves. nZEBs are currently not diffuse in the EU building stock, however are those on which Europe is pointing as a key to building renewal. This thesis aims to investigate the role of energy performance modelling of buildings with low energy consumption. For this reason, research fields of BPS are identified in which the energy performance modelling has been used. They are: climatic data versus energy performance, energy performance rating and ranking of buildings, definition of minimum building requirements and exploring of technologies and valuation methods of energy efficiency measures. For having a wider vision on which model can be used, with what simplifications and what expectations, a research was carried out for each application field. Numerical models are applied both to single buildings and to building stocks, but first ones are the main focus of the investigation. Concerning the first application field, in order to estimate the energy performance (EP) of buildings which have a very low amount of energy covered to a very significant extent by energy from renewable sources accurate and reliable climatic data are necessary. The analysis of EP estimated with different calculation methods shows that the sources of climate data currently available lead to results which can be very different from each other. An improved Typical Meteorological Year construction procedure is proposed to higher the reliability and representativeness of climatic data. Two data mining methods for selecting energy efficiency measures on an urban scale are tested and validated by saved energy of dynamic models. With reference to application field of definition of minimum building requirements the thesis analyses the process to define them. Moreover, it studies how the energy performance modelling influence the definition of minimum building requirements (about the fabric or the HVAC system) and as a fixed requirement could have an imbalance effect between different services. An improved procedure is shown to define the notional reference building and an analysis is led on a heating generator to show how the modelling of technology can affect minimum requirements. Finally concerning EP in valuation methods, case studies with Cost-Optimal Analysis (COA) and Multi-Criteria Analysis (MCA) are performed. The first one gives the possibility to compare results obtained with two calculation methods, the second one permits to investigate the role of energy performance in MCA

Multi-Scale Variability Analysis of Wheat Straw-Based Ethanol Biorefineries Identifies Bioprocess Designs Robust Against Process Input Variations

Bioprocesses based on (ligno-)cellulosic biomass are highly prone to batch-to-batch variations. Varying raw material compositions and enzyme activities hamper the prediction of process yields, economic feasibility and environmental impacts. Commonly, these performance indicators are averaged over several experiments to select suitable process designs. The variabilities in performance indicators resulting from variable process inputs are often neglected, causing a risk for faulty performance predictions and poor process design choices during scale-up. In this paper, a multi-scale variability analysis framework is presented that quantifies the effects of process input variations on performance indicators. Using the framework, a kinetic model describing simultaneous saccharification and ethanol fermentation was integrated with a flowsheet process model, techno-economic analysis and life cycle assessment in order to evaluate a wheat straw-based ethanol biorefinery. Hydrolytic activities reported in the literature for the enzyme cocktail Cellic\uae CTec2, ranging from 62 to 266 FPU\ub7mL−1, were used as inputs to the multi-scale model to compare the variability in performance indicators under batch and multi-feed operation for simultaneous saccharification and fermentation. Bioprocess simulations were stopped at ethanol productivities ≤0.1 g\ub7L−1\ub7h−1. The resulting spreads in process times, hydrolysis yields, and fermentation yields were incorporated into flowsheet, techno-economic and life cycle scales. At median enzymatic activities the payback time was 7%, equal to 0.6 years, shorter under multi-feed conditions. All other performance indicators showed insignificant differences. However, batch operation is simpler to control and well-established in industry. Thus, an analysis at median conditions might favor batch conditions despite the disadvantage in payback time. Contrary to median conditions, analyzing the input variability favored multi-feed operation due to a lower variability in all performance indicators. Variabilities in performance indicators were at least 50% lower under multi-feed operation. Counteracting the variability in enzymatic activities by adjusting the amount of added enzyme instead resulted in higher uncertainties in environmental impacts. The results show that the robustness of performance indicators against input variations must be considered during process development. Based on the multi-scale variability analysis process designs can be selected which deliver more precise performance indicators at multiple system levels

Does uncertainty matter ? A stochastic dynamic analysis of bankable emission permit trading for global climate change policy

Emission permit trading is a centerpiece of the Kyoto Protocol which allows participating nations to trade and bank greenhouse gas permits under the Framework Convention on Climate Change. When market conditions evolve stochastically, emission trading produces a dynamic problem, in which anticipation about the future economic environment affects current banking decisions. In this paper, the author explores the effect of increased uncertainty over future output prices and input costs on the temporal distribution of emissions. In a dynamic programming setting, a permit price is a convex function of stochastic prices of electricity and fuel. Increased uncertainty about future market conditions increases the expected permit price and causes a risk-neutral firm to reduce ex ante emissions so as to smooth out marginal abatement costs over time. The convexity results from the asymmetric impact of changes in counterfactual emissions on the change of marginal abatement costs. Empirical analysis corroborates the theoretical prediction. The author finds that a 1 percent increase in electricity price volatility measured by the annualized standard deviation of percentage price change is associated with an average decrease in the annual emission rate by 0.88 percent. Numerical simulation suggests that high uncertainty could induce substantially early abatements, as well as large compliance costs, therefore imposing a tradeoff between environmental benefits and economic efficiency. The author discusses policy implications for designing an effective and efficient global carbon market.Energy Production and Transportation,Markets and Market Access,Environmental Economics&Policies,Carbon Policy and Trading,Environment and Energy Efficiency

Systematic approaches for synthesis, design and operation of biomass-based energy systems

A biomass-based energy system (BES) is a utility facility which produces cooling, heat and power simultaneously from biomass. By having a BES installed on-site, industrial processes can reduce energy costs by locally producing heat, cooling and power for process and work place requirements. However, several barriers have hindered development of BESs in the energy industry. These barriers include doubts over its operational uncertainties (e.g., seasonal biomass supply, equipment reliability, etc.), the misconception that generating energy from biomass is only a marginal business and the lack of successful cooperative partnerships within the industry. According to literature, such barriers are due to the lack of frameworks that address design aspects and demonstrate the economic viability of a BES. This thesis presents systematic approaches and frameworks to design a BES. These approaches emphasise on integrating synthesis, design and operation decision making for a BES during its preliminary design phase. Firstly, a systematic approach is presented to synthesise a BES considering seasonal variations in biomass supply and energy demand. In this approach, a multi-period optimisation model is formulated to perform technology and design capacity selection by considering seasonal variations in biomass supply and energy demand profiles. This approach is then extended to systematically allocate equipment redundancy within the BES in order to maintain a reliable supply of energy. In this approach, k-out-of-m system modelling and the principles of chance-constrained programming are integrated in a multi-period optimisation model to simultaneously screen technologies based on their respective equipment reliability, capital and operating costs. The model also determines equipment capacities, along with the total number of operating (and stand-by) equipment based on various anticipated scenarios in a computationally efficient manner. Following this, a systematic approach is developed to simultaneously screen, size and allocate redundancy within a BES considering its operational strategies (e.g., following electrical load or following thermal load). Subsequently, a systematic framework on Design Operability Analysis (DOA) is developed to analyse BES designs in instances of failure. This framework provides a stepwise procedure to evaluate proposed BES designs under scenarios of disruption and analyse their true feasible operating range. Knowledge of the feasible operating range enables designers to determine and validate if a BES design is capable of meeting its intended operations. Following this, a systematic Design Retrofit Analysis (DRA) framework is presented to debottleneck and retrofit existing BES designs in cases where energy demands are expected to vary in the future. The presented framework re-evaluates an existing BES design under disruption scenarios and determines its real-time feasible operating range. The real-time feasible operating range will allow designers to determine whether debottlenecking is required. If debottlenecking is required, the framework provides systematic debottlenecking and retrofit guidelines for BES designs. The design of a BES is then extended further to consider its interaction in an eco-industrial park (EIP). Since heat, cooling and power are essentially required in most industrial processes, a BES can be more economically attractive if synthesised for an EIP. As such, an optimisation-based negotiation framework is developed to analyse the potential cost savings allocation between participating plants in an EIP coalition. This framework combines the principles of rational allocation of benefits with the consideration of stability and robustness of an EIP coalition to changes in cost assumptions. Lastly, possible extensions and future opportunities for this research work are highlighted at the end of this thesis

Situation Awareness for Smart Distribution Systems

In recent years, the global climate has become variable due to intensification of the greenhouse effect, and natural disasters are frequently occurring, which poses challenges to the situation awareness of intelligent distribution networks. Aside from the continuous grid connection of distributed generation, energy storage and new energy generation not only reduces the power supply pressure of distribution network to a certain extent but also brings new consumption pressure and load impact. Situation awareness is a technology based on the overall dynamic insight of environment and covering perception, understanding, and prediction. Such means have been widely used in security, intelligence, justice, intelligent transportation, and other fields and gradually become the research direction of digitization and informatization in the future. We hope this Special Issue represents a useful contribution. We present 10 interesting papers that cover a wide range of topics all focused on problems and solutions related to situation awareness for smart distribution systems. We sincerely hope the papers included in this Special Issue will inspire more researchers to further develop situation awareness for smart distribution systems. We strongly believe that there is a need for more work to be carried out, and we hope this issue provides a useful open-access platform for the dissemination of new ideas

Adaptive load frequency control of electrical power systems

The thesis describes Load Frequency Control techniques which may be used for real-time on-line control of large electrical power systems. Traditionally the frequency control of power systems has been carried out using standard fixed parameter control schemes, which give control over the immediate steady- state error and the long term accumulated frequency error, but do not account for the fact that system conditions can alter due to the change in consumer load and generating patterns. The thesis presents a method of controlling the system frequency using adaptive control techniques, which ensure that optimal control action is calculated based on the present system conditions. It enables the system operating point to be monitored so that optimal control may continue to be calculated as the system operating point alters. The proposed method of frequency control can be extended to meet the problems of system interconnection and the control of inter-area power flows. The thesis describes the work carried out at Durham on a fixed parameter control scheme which led to the development of an adaptive control scheme. The controller was validated against a real-time power system simulator with full Energy Management software. Results are also presented from work carried out at the Central Electricity Research Laboratories under the C.A.S.E award scheme. This led to the development of a power system simulator, which along with the controller was validated on-line with the Dispatch Project used by the Central Electricity Generating Board