Multi-stage optimal design of energy systems for urban districts

Urban districts develop in a dynamic manner over multi-year horizons with new buildings being added and changes being made to existing buildings (e.g. retrofits). Nevertheless, optimization models used to design urban district energy systems (DES) commonly consider a single, “typical” year for the design. This practice, however, does not allow for energy design decisions to be made in multiple phases in order to reflect a district’s development phases. This paper addresses this issue and presents a novel optimization model that allows the multi-stage optimal design of urban DES. The model identifies the cost-optimal technology investment decisions across a horizon that spans multiple years, while also calculating the energy system’s optimal operating patterns in order to meet the district’s energy demands. The evolution of the district’s energy demands and aspects like the evolution of technology costs and energy carrier prices are considered in the model. The model is applied to a new urban district in Zurich, Switzerland, for which 5 development stages are considered with new buildings of various types constructed in each phase. A multi-stage DES design plan is developed for the period 2021-2050, which includes large energy technology investments for each new development phase, but also smaller ones in the intermediate years between 2021 and 2050. The model specifies the amount of energy generated by each technology installed in each year, as well as the contribution of renewable energy in covering the district’s energy demands

A GIS based methodology to support multi-criteria decision making for the retrofitting process of residential buildings

This paper presents a workflow to support the decision making for building retrofit and building systems update at urban scale. The workflow includes i) a method to extract information from a geographical information system including information on building characteristics, building systems and building typology, ii) a method to evaluate the current and future energy demand of buildings using a dynamic building simulation tool, and iii) an updated version of the energy hub approach to evaluate best performing options in terms of energy systems update. The developed method is applied to the city of Zurich to evaluate the optimal energy system update for all existing buildings within the city. Modelling results include best performing options in terms of CO2 emissions, renewable energy share, or energy efficiency while minimizing resulting costs for possible system and retrofitting solutions

THE INVESTIGATION OF INSULIN ROLE AT THE ACTIVITY OF AROMATASE IN VIVO

FOURTY WOMEN, WHOSE AGE RANGED FROM 18 TO 37 YEARS, WERE STUDIED. THESE WOMENWERE DIVIDED IN FOUR GROUPS. THE FIRST GROUP COMPRISED PATIENTS WITH PCOS, INSULIN RESISTANCE AND ABNORMAL BMI. THE SECOND GROUP COMPRISED PATIENTS WITH PCOS, NO INSULIN RESISTAN CE AND NORMAL BMI. THE THIRD GROUP CONSISTED OF WOMENWITH ABNORMAL BMI, WHILE THE FOURTH GROUP OF WOMEN WITH NORMAL BMI LABORATORYEVALUATION INCLUDED MEASUREMENT OF SERUM LEVELS OF GLYCOSE, INSULIN, TESTOSTERONE, ANDROSTENEDIONE, DEYDROEPIANDROSTERONE SU LFATE, ESTRADIOL AND ESTRONEBEFORE AND 180 MINUTES AFTER AN ORALGLYCOSE TOLERANCE TEST. OUR RESULTS APPEAR TO INDICATED THAT SHORT-TERM INDUCED HYPERINSULINEMIA DOES NOT INCREASE SERUM ANDROGEN LEVELS FROM THE OVARIES WITH A DIRECT WAY. MOREOVER, SORT-TER MHYPERINSULINEMIA, DOES NOT SEEM TO INFLUENCE ANDROGEN CATABOLISM TO ESTROGENS,THAT IS AROMATASE EFFICACY IN VIVO.ΜΕΛΕΤΗΘΗΚΑΝ 40 ΕΠΙΛΕΓΜΕΝΕΣ ΓΥΝΑΙΚΕΣ ΗΛΙΚΙΑΣ 18-37 ΕΤΩΝ ΟΙ ΟΠΟΙΕΣ ΚΑΤΑΤΑΧΘΗΚΑΝΣΕ ΤΕΣΣΕΡΙΣ ΟΜΑΔΕΣ. Η ΠΡΩΤΗ ΟΜΑΔΑ ΑΠΟΤΕΛΟΥΝΤΑΝ ΑΠΟ ΑΣΘΕΝΕΙΣ ΜΕ PCOS ΑΝΤΙΣΤΑΣΗ ΣΤΗΝ ΙΝΣΟΥΛΙΝΗ ΚΑΙ ΠΑΘΟΛΟΓΙΚΟ ΒΜΙ. Η ΔΕΥΤΕΡΗ ΟΜΑΔΑ ΑΠΟ ΑΣΘΕΝΕΙΣ ΜΕ PCOS ΧΩΡΙΣΑΝΤΙΣΤΑΣΗ ΣΤΗΝ ΙΝΣΟΥΛΙ ΝΗ ΚΑΙ ΦΥΣΙΟΛΟΓΙΚΟ ΒΜΙ. Η ΤΡΙΤΗ ΟΜΑΔΑ ΑΠΟ ΥΓΙΕΙΣ ΓΥΝΑΙΚΕΣ ΜΕ ΠΑΘΟΛΟΓΙΚΟ ΒΜΙ ΚΑΙ Η ΤΕΤΑΡΤΗ ΟΜΑΔΑ ΑΠΟ ΥΓΙΕΙΣ ΓΥΝΑΙΚΕΣ ΜΕ ΦΥΣΙΟΛΟΓΙΚΟ ΒΜΙ. ΠΡΟΣΔΙΟΡΙΣΤΗΚΑΝ ΤΑ ΕΠΙΠΕΔΑ ΓΛΥΚΟΖΗΣ, ΙΝΣΟΥΛΙΝΗΣ, ΤΕΣΤΟΣΤΕΡΟΝΗΣ, ΑΝΔΡΟΣΤΕΝΔΙΟΝΗΣ, ΘΕΙΙΚΗΣ ΔΕΥΔΡΟ ΕΠΙΑΝΔΡΟΣΤΕΡΟΝΗΣ, ΟΙΣΤΡΑ ΔΙΟΛΗΣ ΚΑΙ ΟΙΣΤΡΟΝΗΣ ΠΡΙΝ ΚΑΙ ΥΣΤΕΡΑ ΑΠΟ ΦΟΡΤΗΣΗ ΜΕ 75GZ ΔΕΞΤΡΟΖΗΣ ΑΠΟ ΤΟ ΣΤΟΜΑ. ΤΑ ΕΥΡΗΜΑΤΑ ΜΑΣ ΕΝΙΣΧΥΟΥΝ ΤΗΝ ΑΠΟΨΗ ΟΤΙ Η ΒΡΑΧΥΧΡΟΝΙΑ ΥΠΕΡΙΝΣΟΥΛΙΝΑΙΜΙΑ ΔΕΝ ΠΡΟΚΑΛΕΙ ΑΥΞΗΣΗ ΤΩΝ ΕΠΙΠΕΔΩΝ ΤΩΝ ΑΝΔΡΟΓΟΝΩΝ ΑΠΟ ΤΙΣ ΟΩΘΗΚΕΣ ΜΕ ΑΜΕΣΟ ΤΡΟΠΟ. ΕΠΙΠΛΕΟΝ, Η ΒΡΑΧΥΧΡΟΝΙΑ ΥΠΟΕΡΙΝΣΟΥΛΙΝΑΙΜΙΑ, ΔΕΝ ΕΠΗΡΕΑΖΕΙ ΤΟΝ ΚΑΤΑΒΟΛΙΣΜΟ ΤΩΝ ΑΝΔΡΟΓΟΝΩΝ ΣΕ ΟΙΣΤΡΟΓΟΝΑ, ΔΗΛΑΔΗ ΤΗ ΔΡΑΣΤΙΚΟΤΗΤΑ ΤΗΣ ΑΡΩΜΑΤΑΣΗΣ ΙN VIVO

MANGO: A novel optimization model for the long-term, multi-stage planning of decentralized multi-energy systems

This study presents MANGO (Multi-stAge eNerGy Optimization), a novel optimization model that incorporates a multi-year planning horizon, along with flexible, multi-stage investment strategies for the effective, long-term design of decentralized multi-energy systems (D-MES). By considering the dynamic surrounding energy and techno-economic landscape that evolves over time, MANGO harnesses the strategic value of investment flexibility and can optimally phase D-MES investments in order to benefit, for instance, from projected future reduced technology costs and technical improvements. To achieve this, the model considers the most relevant dynamic aspects, such as year-to-year variations in energy demands, changing energy carrier and technology prices, technical improvements and equipment degradation. MANGO is also capable of optimizing the design of complex configurations composed of multiple, interconnected D-MES installed at different locations. Finally, the model’s formulation also addresses end-of-horizon effects that can distort solutions in multi-stage energy system models. Besides presenting the key aspects and the mathematical formulation of MANGO, this study also uses the model to develop a six-stage energy design plan, along a 30-year project horizon, for an urban district composed of 3 sites in Zurich, Switzerland. One candidate D-MES is considered per site and different scenarios are examined regarding building retrofitting and D-MES interconnections. Results overall show that retrofitting leads to lower emission levels, but significantly higher costs. On the other hand, D-MES interconnections improve both the economic and the environmental system performance. Finally, regarding optimal D-MES configurations, a variety of technologies is used, with combinations of air-source heat pumps and natural gas boilers leading to better economic performance and combinations of ground-source heat pumps and biomass boilers to more environmentally-friendly designs. Overall, MANGO facilitates D-MES decision-making at the strategic level by delivering flexible multi-stage investment strategies, at the economic level by providing detailed information about the systems’ economic performance during each project year and, finally, at the technical level by specifying the optimal technical configurations of each D-MES and their optimal operating schedules. With its long-term perspective, MANGO can offer insights that closely match the dynamic class of real-world energy system design projects led by energy developers.ISSN:0306-2619ISSN:1872-911

Review of model-based electricity system transition scenarios: An analysis for Switzerland, Germany, France, and Italy

Policymakers currently face the challenge of supporting a suitable technology mix to decarbonize electricity systems. Due to multiple and interdependent technologies and sectors, as well as opposing objectives such as minimizing cost and reducing emissions, energy system models are used to develop optimal transition pathways towards decarbonized electricity systems. Research in this domain has increased in recent years and multiple studies have used energy system modeling (ESM) to shed light on possible transition pathways for national electricity systems. However, in many cases, the large number of model-based studies makes it difficult for policymakers to navigate study results and condense diverging pathways into a coherent picture. We conduct an in-depth review of ESM publications covering Switzerland, Germany, France, and Italy, and analyze the main trends regarding electricity generation mixes, key supply and storage technology trends, and the role of demand developments. Our findings show that diverging solutions are proposed regarding technology mixes in 2030 and 2050, not all of which meet current climate targets. Additionally, our analysis suggests that natural gas, solar, and wind will continue to be key actors in the electricity system transition, whereas the role of storage remains opaque and calls for clearer policy support. We conclude that due to diverging targets and the current energy landscape in each country considered, different options appear as prominent transition pathways, meaning that individual sets of policies are necessary for each case. Nonetheless, international collaborations will be essential to ensure a swift electricity system transition by 2050.ISSN:1364-032

Designing electrically self-sufficient distributed energy systems under energy demand and solar radiation uncertainty

This paper examines the design of autonomous Distributed Energy Systems (DES) under energy demand and solar radiation uncertainty. A two-stage stochastic program is developed that seeks cost-optimal DES designs considering probabilistic scenarios for the uncertain parameters to represent possible operating conditions. Then, energy autonomy constraints are imposed to each individual scenario, ensuring the autonomy robustness of the DES. The model is applied to a Swiss office building and results reveal that the most cost-effective DES solutions achieve an electrical autonomy of 20% relying on renewable PV electricity generation. Higher autonomy levels require additional electricity from a CHP engine, while a 100% autonomous system is achievable but requires significant amounts of thermal and electrical storage. Finally, comparing the stochastic DES designs against deterministic ones reveal significant differences, illustrating the importance of uncertainty considerations in the design of autonomous DES.ISSN:1876-610