scholarly journals Potential of Photovoltaic Panels on Building Envelopes for Decentralized District Energy Systems

2021 ◽  
Vol 9 ◽  
Author(s):  
Luise Middelhauve ◽  
Luc Girardin ◽  
Francesco Baldi ◽  
François Maréchal
Keyword(s):  
Energy Systems ◽  
Energy Generation ◽  
System Optimization ◽  
Mixed Integer ◽  
Optimization Approach ◽  
Round Trip ◽  
District Energy ◽  
Self Sufficiency ◽  
Wide Range ◽  
The Impact

The expected increase of the penetration of distributed renewable energy technologies into the electricity grid is expected to lead to major challenges. As a main stakeholder, authorities often lack the appropriate tools to frame and encourage the transition and monitor the impact of energy transition policies. This paper aims at combining relatively detailed modeling of the PV generation potential on the building’s envelope while retaining the energy system optimization approach. The problem is addressed as a multiobjective, mixed-integer linear programming problem. Compared to the existing literature in the field, the proposed approach combines advanced modeling of the energy generation potential from PV panels with detailed representation of the district energy systems, thus allowing an accurate representation of the interaction between the energy generation from PV and the rest of the system. The proposed approach was applied to a typical residential district in Switzerland. The results of the application of the proposed method show that the district can achieve carbon neutrality based on PV energy alone, but this requires covering all the available district’s rooftops and part of the district’s facades. Whereas facades are generally disregarded due to their lower generation potential, the results also allow concluding that facade PV can be economically convenient for a wide range of electricity prices, including those currently used by the Swiss grid operators. Achieving self-sufficiency at district scale is challenging: it can be achieved by covering approximately 42–100% of the available surface when the round-trip efficiency decreases from 100 to 50%. The results underline the importance of storage for achieving self-sufficiency: even with 100%, round-trip efficiency for the storage, very large capacities are required. However, energy demand reduction through renovation would allow reaching self-sufficiency with half of the PV and storage capacity required.

scholarly journals Impact of demand response on BIPV and district multi-energy systems design in Singapore and Switzerland

2021 ◽  
Vol 2042 (1) ◽  
pp. 012096
Author(s):  
Christoph Waibel ◽  
Shanshan Hsieh ◽  
Arno Schlüter
Keyword(s):  
Demand Response ◽  
Programming Model ◽  
Systems Design ◽  
Energy Systems ◽  
Mixed Integer ◽  
Peak Shaving ◽  
Climate Conditions ◽  
Building Integrated Photovoltaics ◽  
Energy Hub ◽  
The Impact

Abstract This paper demonstrates the impact of demand response (DR) on optimal multi-energy systems (MES) design with building integrated photovoltaics (BIPV) on roofs and façades. Building loads and solar potentials are assessed using bottom-up models; the MES design is determined using a Mixed-Integer Linear Programming model (energy hub). A mixed-use district of 170,000 m2 floor area including office, residential, retail, education, etc. is studied under current and future climate conditions in Switzerland and Singapore. Our findings are consistent with previous studies, which indicate that DR generally leads to smaller system capacities due to peak shaving. We further show that in both the Swiss and Singapore context, cost and emissions of the MES can be reduced significantly with DR. Applying DR, the optimal area for BIPV placement increases only marginally for Singapore (~1%), whereas for Switzerland, the area is even reduced by 2-8%, depending on the carbon target. In conclusion, depending on the context, DR can have a noticeable impact on optimal MES and BIPV capacities and should thus be considered in the design of future, energy efficient districts.

scholarly journals Backbone—An Adaptable Energy Systems Modelling Framework

Energies ◽  
2019 ◽  
Vol 12 (17) ◽  
pp. 3388 ◽  
Author(s):  
Niina Helistö ◽  
Juha Kiviluoma ◽  
Jussi Ikäheimo ◽  
Topi Rasku ◽  
Erkka Rinne ◽  
...  
Keyword(s):  
Power Plants ◽  
Large Scale ◽  
Unit Commitment ◽  
Energy Systems ◽  
Mixed Integer ◽  
Investment Planning ◽  
Planning And Scheduling ◽  
Modelling Framework ◽  
Wide Range ◽  
Systems Modelling

Backbone represents a highly adaptable energy systems modelling framework, which can be utilised to create models for studying the design and operation of energy systems, both from investment planning and scheduling perspectives. It includes a wide range of features and constraints, such as stochastic parameters, multiple reserve products, energy storage units, controlled and uncontrolled energy transfers, and, most significantly, multiple energy sectors. The formulation is based on mixed-integer programming and takes into account unit commitment decisions for power plants and other energy conversion facilities. Both high-level large-scale systems and fully detailed smaller-scale systems can be appropriately modelled. The framework has been implemented as the open-source Backbone modelling tool using General Algebraic Modeling System (GAMS). An application of the framework is demonstrated using a power system example, and Backbone is shown to produce results comparable to a commercial tool. However, the adaptability of Backbone further enables the creation and solution of energy systems models relatively easily for many different purposes and thus it improves on the available methodologies.

scholarly journals District Cooling Versus Individual Cooling in Urban Energy Systems: The Impact of District Energy Share in Cities on the Optimal Storage Sizing

Energies ◽  
2019 ◽  
Vol 12 (3) ◽  
pp. 407 ◽  
Author(s):  
Dominik Dominković ◽  
Goran Krajačić
Keyword(s):  
Energy Supply ◽  
Energy Systems ◽  
Energy System ◽  
Integrated Modelling ◽  
Economic Costs ◽  
Battery Storage ◽  
Spatial Constraints ◽  
District Energy ◽  
Urban Energy ◽  
The Impact

The energy transition of future urban energy systems is still the subject of an ongoing debate. District energy supply can play an important role in reducing the total socio-economic costs of energy systems and primary energy supply. Although lots of research was done on integrated modelling including district heating, there is a lack of research on integrated energy modelling including district cooling. This paper addressed the latter gap using linear continuous optimization model of the whole energy system, using Singapore for a case study. Results showed that optimal district cooling share was 30% of the total cooling energy demand for both developed scenarios, one that took into account spatial constraints for photovoltaics installation and the other one that did not. In the scenario that took into account existing spatial constraints for installations, optimal capacities of methane and thermal energy storage types were much larger than capacities of grid battery storage, battery storage in vehicles and hydrogen storage. Grid battery storage correlated with photovoltaics capacity installed in the energy system. Furthermore, it was shown that successful representation of long-term storage solutions in urban energy models reduced the total socio-economic costs of the energy system for 4.1%.

scholarly journals A novel approach for energy- and memory-efficient data loss prevention to support Internet of Things networks

2020 ◽  
Vol 16 (6) ◽  
pp. 155014772092982
Author(s):  
Pooya Hejazi ◽  
Gianluigi Ferrari
Keyword(s):  
Internet Of Things ◽  
Load Balancing ◽  
Data Storage ◽  
Optimization Problem ◽  
Mixed Integer ◽  
Optimization Approach ◽  
Distributed Data ◽  
Data Loss ◽  
Distributed Data Storage ◽  
Wide Range

Internet of Things integrates various technologies, including wireless sensor networks, edge computing, and cloud computing, to support a wide range of applications such as environmental monitoring and disaster surveillance. In these types of applications, IoT devices operate using limited resources in terms of battery, communication bandwidth, processing, and memory capacities. In this context, load balancing, fault tolerance, and energy and memory efficiency are among the most important issues related to data dissemination in IoT networks. In order to successfully cope with the abovementioned issues, two main approaches—data-centric storage and distributed data storage—have been proposed in the literature. Both approaches suffer from data loss due to memory and/or energy depletion in the storage nodes. Even though several techniques have been proposed so far to overcome the abovementioned problems, the proposed solutions typically focus on one issue at a time. In this article, we propose a cross-layer optimization approach to increase memory and energy efficiency as well as support load balancing. The optimization problem is a mixed-integer nonlinear programming problem, and we solve it using a genetic algorithm. Moreover, we integrate the data-centric storage features into distributed data storage mechanisms and present a novel heuristic approach, denoted as Collaborative Memory and Energy Management, to solve the underlying optimization problem. We also propose analytical and simulation frameworks for performance evaluation. Our results show that the proposed method outperforms the existing approaches in various IoT scenarios.

scholarly journals Impact of advanced electricity tariff structures on the optimal design, operation and profitability of a grid-connected PV system with energy storage

2019 ◽  
Vol 2 (S1) ◽  
Author(s):  
Lionel Bloch ◽  
Jordan Holweger ◽  
Christophe Ballif ◽  
Nicolas Wyrsch
Keyword(s):  
Distribution System ◽  
Energy Systems ◽  
Mixed Integer ◽  
Economic Viability ◽  
Programming Approach ◽  
Pv System ◽  
Battery System ◽  
Tariff Structures ◽  
The Impact ◽  
Privately Owned

Abstract The increasing penetration of residential photovoltaics (PV) comes with numerous challenges for distribution system operators. Technical difficulties arise when an excess of PV energy is injected into the grid, causing voltage rise or overloading of the lines. Economic challenges appear because PV owners and consumers are not participating equally in the grid costs. Indeed, PV owners benefit by self-consuming their PV production and by gaining additional revenues when they sell their PV surplus to the grid. Hence, they lower their grid costs. In this paper, we propose a mixed-integer-linear programming approach to solve the design and operation of a PV and battery system efficiently. We use this tool to benchmark five different tariff scenarios, which include real-time pricing, a capacity-based tariff, and a block rate tariff, and evaluate their effect on the design and operation of the system. Carefully tailored metrics show the impact of these tariff structures on the trade-off between the economic viability of privately owned energy systems and their grid usage intensity. Considering both aspects, we show that a block rate tariff is the most promising approach and that capacity-based tariffs rely on PV curtailment alone to curtail the generation peaks.

scholarly journals Sustainable Energy Systems: Optimization and Efficiency

2020 ◽  
Vol 10 (12) ◽  
pp. 4405 ◽  
Author(s):  
João Carlos de Oliveira Matias ◽  
Radu Godina ◽  
Edris Pouresmaeil
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Distributed Generation ◽  
Sustainable Energy ◽  
Energy Systems ◽  
World Population ◽  
Special Issue ◽  
Wide Range ◽  
Sustainable Energy Systems ◽  
The Impact

The world population is growing at a very high rate, which also entails a massive increase in energy consumption, and also, therefore, in its production, which is gradually and steadily increasing. Energy and the environment are essential to achieving sustainable development, and constitute a fundamental part of human activity. If we consider energy efficiency as the use of an appliance, process or installation for which we try to produce more energy, but with less energy consumption than the average for these appliances, processes or installations, then achieving a higher energy efficiency is imperative. Energy efficiency is a cornerstone policy on the road to stopping climate change and to achieving sustainable societies, along with the development of renewable energy and an environmentally friendly transport policy. In this Special Issue, 11 selected and peer-reviewed articles have been contributed, on a wide range of topics under the umbrella of sustainable energy systems. The published articles encompass distinct areas of interest. One area addresses distributed generation, which addresses such topics as the optimal planning of distributed generation, protection of blind areas in distribution networks, multi-objective optimization in distributed generation, energy management of virtual power plants in distributed generation, and the impact of demand-response programs on a home microgrid, as well as concentrating solar power into a highly renewable, penetrated power system. The second section of the Special Issue addresses a wide range of topics, from parametric studies of 2 MW gas engines or data centers, to combustion characteristics of a non-premixed oxy-flame, to new techniques of PV Tracking, to applications of nanofluids in the thermal performance enhancement of parabolic trough solar collectors.

scholarly journals Grid-Aware Layout of Photovoltaic Panels in Sustainable Building Energy Systems

2021 ◽  
Vol 8 ◽  
Author(s):  
Luise Middelhauve ◽  
Francesco Baldi ◽  
Paul Stadler ◽  
François Maréchal
Keyword(s):  
Energy Demand ◽  
Power Grid ◽  
Renewable Energy Sources ◽  
Energy Systems ◽  
Energy Generation ◽  
Building Energy ◽  
Solar Irradiation ◽  
Mixed Integer ◽  
Photovoltaic Panels ◽  
Building Energy Systems

In the context of increasing concern for anthropogenic CO2 emissions, the residential building sector still represents a major contributor to energy demand. The integration of renewable energy sources, and particularly of photovoltaic (PV) panels, is becoming an increasingly widespread solution for reducing the carbon footprint of building energy systems (BES). However, the volatility of the energy generation and its mismatch with the typical demand patterns are cause for concern, particularly from the viewpoint of the management of the power grid. This paper aims to show the influence of the orientation of photovoltaic panels in designing new BES and to provide support to the decision making process of optimal PV placing. The subject is addressed with a mixed integer linear optimization problem, with costs as objectives and the installation, tilt, and azimuth of PV panels as the main decision variables. Compared with existing BES optimization approaches reported in literature, the contribution of PV panels is modeled in more detail, including a more accurate solar irradiation model and the shading effect among panels. Compared with existing studies in PV modeling, the interaction between the PV panels and the remaining units of the BES, including the effects of optimal, scheduling is considered. The study is based on data from a residential district with 40 buildings in western Switzerland. The results confirm the relevant influence of PV panels’ azimuth and tilt on the performance of BES. Whereas south-orientation remains the most preferred choice, west-orientationed panels better match the demand when compared with east-orientationed panels. Apart from the benefits for individual buildings, an appropriate choice of orientation was shown to benefit the grid: rotating the panels 20° westwards can, together with an appropriate scheduling of the BES, reduce the peak power of the exchange with the power grid by 50% while increasing total cost by only 8.3%. Including the more detailed modeling of the PV energy generation demonstrated that assuming horizontal surfaces can lead to inaccuracies of up to 20% when calculating operating expenses and electricity generated, particularly for high levels of PV penetration.

scholarly journals Sizing and Management of an Energy System for a Metropolitan Station with Storage and Related District Energy Community

Energies ◽  
2021 ◽  
Vol 14 (18) ◽  
pp. 5997
Author(s):  
Mircea Stefan Simoiu ◽  
Ioana Fagarasan ◽  
Stephane Ploix ◽  
Vasile Calofir
Keyword(s):  
Energy Storage ◽  
Optimal Solution ◽  
Energy System ◽  
District Level ◽  
Mixed Integer ◽  
Programming Approach ◽  
Net Energy ◽  
Self Sufficiency ◽  
Photovoltaic Plant ◽  
The Impact

Future renewable energy communities will reshape the paradigm in which we design and control efficient power systems at the district level. In this manner, the focus will be fundamentally shifted towards sustainable related concepts such as self-consumption, self-sufficiency and net energy exchanged with the grid. In this context, the paper presents a novel approach for optimally designing and controlling the photovoltaic plant and energy storage systems for a metro station in order to increase collective self-consumption and self-sufficiency at the district level. The methodology considers a community of several households connected to a subway station and focuses on the interaction between energy sources and consumers. Furthermore, the optimal solution is determined by using a Mixed Integer Linear Programming Approach, and the impact of different configurations on the overall district benefit is investigated by using several simulation scenarios. The work presents a detailed case study to underline the benefits and flexibility offered by the energy storage system in comparison with a scenario involving only a photovoltaic plant.

scholarly journals Improving mesoscale wind speed forecasts using lidar-based observation nudging for airborne wind energy systems

2019 ◽  
Vol 4 (4) ◽  
pp. 563-580
Author(s):  
Markus Sommerfeld ◽  
Martin Dörenkämper ◽  
Gerald Steinfeld ◽  
Curran Crawford
Keyword(s):  
Wind Speed ◽  
Wind Energy ◽  
Energy Systems ◽  
Stability Conditions ◽  
Data Set ◽  
Advantages And Disadvantages ◽  
Wide Range ◽  
Lidar Measurements ◽  
Wind Energy Systems ◽  
The Impact

Abstract. Airborne wind energy systems (AWESs) aim to operate at altitudes above conventional wind turbines where reliable high-resolution wind data are scarce. Wind light detection and ranging (lidar) measurements and mesoscale models both have their advantages and disadvantages when assessing the wind resource at such heights. This study investigates whether assimilating measurements into the mesoscale Weather Research and Forecasting (WRF) model using observation nudging generates a more accurate, complete data set. The impact of continuous observation nudging at multiple altitudes on simulated wind conditions is compared to an unnudged reference run and to the lidar measurements themselves. We compare the impact on wind speed and direction for individual days, average diurnal variability and long-term statistics. Finally, wind speed data are used to estimate the optimal traction power and operating altitudes of AWES. Observation nudging improves the WRF accuracy at the measurement location. Close to the surface the impact of nudging is limited as effects of the air–surface interaction dominate but becomes more prominent at mid-altitudes and decreases towards high altitudes. The wind speed frequency distribution shows a multi-modality caused by changing atmospheric stability conditions. Therefore, wind speed profiles are categorized into various stability conditions. Based on a simplified AWES model, the most probable optimal altitude is between 200 and 600 m. This wide range of heights emphasizes the benefit of such systems to dynamically adjust their operating altitude.

Sign in / Sign up

Export Citation Format

Share Document