Smart Energy最新文献

Grounded in the idea of meeting the needs of generations across time, sustainable development bears a close relationship to the way in which humanity consumes energy. Nevertheless, the historic notion that energy demand growth reflects improved living standards, economic development and prosperity are challenged when sustainability constraints and the impact on climate change are considered. As a result, a growing body of scientific research is exploring how energy demand can contribute to the energy transition instead of placing it in peril, by means of greater efficiency, digitalization, connectivity and a holistic approach to planning and management. Over the years, the Conference on Sustainable Development of Energy, Water and Environment Systems (SDEWES) has acted as a forum for scientific discourse in this field, shedding light on nuanced discussions and challenging siloed thinking. This special issue contains a selection of four papers that are focused on smart energy demand, demand response and decarbonization, presented at the 2021 SDEWES Conference (16^th SDEWES Conference held in Dubrovnik, Croatia).

Among the numerous envisioned applications for hydrogen in the decarbonisation of the energy system, seasonal energy storage is usually regarded as one of the most likely options. Although long-term energy storage is usually considered at grid-scale level, given the increasing diffusion of distributed energy systems and the expected cost reduction in hydrogen related components, some companies are starting to offer residential systems, with PV modules and batteries, that rely on hydrogen for seasonal storage of electrical energy. Such hydrogen storage systems are generally composed by water electrolysers, hydrogen storage vessels and fuel cells.

The aim of this work is to investigate such systems and their possible applications for different geographical conditions in Italy. On-grid and off-grid systems are considered and compared to systems without hydrogen, in terms of self-consumption ratio, size of components and economic investment. Each different option has been assessed from a techno-economic point of view via MESS (Multi Energy Systems Simulator), an analytical programming tool for the analysis of local energy systems.

Results have identified the optimal sizing of the system's components and have shown how such systems are not, in general, economically competitive for a single dwelling, although they can in some cases ensure energy independence.

Decarbonizing industrial high-temperature (above 500 °C) heat demand is considered as one of the most challenging areas for decarbonization of energy due to (1) their strive for high-grade heat input, and (2) CO₂ emission as the by-product. Heat and electricity from solar sources (medium to high-temperature solar thermal and photovoltaics) are two potential solutions for reducing CO₂ emission in the industrial heating sector. This study investigates the potential of solar energy in the form of heat and/or electricity to make a significant contribution to reduce CO₂ emissions from industrial heating requirements. Analysis is performed to determine the optimal configuration of both systems along with a hybrid system in terms of both cost and emissions reductions which are compared with a natural gas-only (conventional) system. Annual hourly solar irradiation data for two locations with different climatic conditions (mild and hot climates) was generated and employed as the input to the optimization model to provide a high-resolution (hourly-based) comparison. The results showed that for the hot climate, the optimized compact parabolic trough system reduced CO₂ emissions by 45% compared to the base gas-only system with an increase in 75% for cost. A 45% reduction in emissions for the location with mild weather condition resulted accompanied with an 88% increase for costs. The photovoltaic solution resulted in higher cost than that of compact parabolic trough solution in the same level of emission due to the lower conversion efficiencies of the photovoltaic cells. Beside the environmental aspects, less dependance to gas transmission network and relying on local energy sources as well as less operation/maintenance costs are the benefits of the proposed configurations.

The present work refers to two current problems in the context of achieving Greenhouse gas (GHG) neutrality: first the curtailment of renewable, volatile power generation units and secondly the high share of the mobility domain in total GHG-emissions. Both problems can be countered by a decentralised, smart energy system that supplies electricity, gas and heat to a hybrid public transport bus fleet and is simultaneously coupled to the public gas grid, public electricity grid and the district heating grid (Multi-Grid-Coupling). The enabling energy conversion unit is a reversible solid oxide cell (rSOC), which is operated in combined heat and power (CHP) mode or in power-to-gas (P2G) mode. P2G is primarily a solution approach for the first-mentioned problem and can thus successively lead to the replacement of fossil energy sources. Furthermore, by integrating industrial waste gases – as a necessary CO₂ source for the P2G process – an additional benefit is gained from the CO₂ that is emitted anyhow. The hybrid bus fleet constitutes an ecological alternative concept in public transport and therefore addresses the second-mentioned problem. The system, developed under the current state of the art technologies and the current ecological and economic conditions for Europe and Germany, can be operated profitably from the perspective of the system operator. This applies to the economically and ecologically optimised operating schedule of the controllable system elements such as the electrical, thermal and compressed gas storages, rSOC, compressor and the energy exchange with the public grids. To derive the optimal operating schedule of the cross-sectoral system, a mixed-integer linear programming (MILP) model is implemented and simulated under the current legal situation.

Transportation is undergoing an electric revolution and the marine sector is missing many of the advances made in other industries. The critical roadblock is the virtual actor of safety. To date, there is no viable replacement for the range, comfort, and safety provided by a tank of diesel.

The question this research asks is could fully integrating transport, storage, and eliminating critical excess energy within the closed loop of the sailing vessel increase comfort, safety, range, and speed? This paper leverages the smart energy systems approach and is based on existing technology, including the propeller. However, it applies a new approach to driveline design and operation as a basis to model energy performance.

In our model, wind is the primary energy source converted into electric energy via hydro-generation; the point of departure from existing systems is the ability to fully manage critical excess energy in an integrated smart energy system. Energy management is carried out by a new performance algorithm called Charge Made Good (CMG), that allows the vessel to predict the battery state at the journey’s end and maintain this prediction during periods of intermittent energy production from forecast variance. The model shows that fossil fuels used for safety and range in direct-drive and electric-hybrid systems can be eliminated, with an improved level of amenity aboard and an improved safety factor using the smart energy systems approach. It is the first academic research to address the safety and comfort of zero-emissions recreational craft rather than technical but unusable/uneconomic solutions.

The aim of this paper is to explore potential least-cost decarbonisation solutions for an off-grid and offshore fish farm power supply system under long term uncertainty. The Hinnøya island in Norway is used as a use case. Three distinctive off-grid and grid-based alternative power supply solutions were proposed and studied as a replacement to the existing diesel power solution in a three-stage stochastic model and under two critical long-term uncertainties: (1) access to strong grid and (2) storage battery cost. The TIMES modelling framework is applied. The stochastic model results reveal that grid integrated storage is an optimal near-term investment for a storage battery cost of 295 €/kWh and less by 2025. In scenarios with no access to strong grid, grid integrated storage continues to be a least-cost solution in the long-term as well, whereas in those scenarios with strong grid access, new investment in storage is not required after 2030. Contrary to the stochastic model runs, the equivalent deterministic model runs showed that a hybrid wind and diesel solution is an optimal near-term investment. From 2030, however, a similar technology pattern in both stochastic and deterministic model runs are observed. Nevertheless, the results are very sensitive to the assumed storage battery costs. Higher storage costs (as high as 704 €/kWh by 2025) would make the hybrid wind and diesel solution an optimal solution instead of the grid integrated storage solution in near-term investment in both stochastic and deterministic model runs.

Large energy companies and energy startups are increasingly focusing their resources to build new businesses concerning smart energy systems (SES). The development and integration of related innovative technologies for green transformation with traditional business models are often hampered, however, by the challenge of parallel management of exploitation of current business areas, and the exploration of new business areas with breakthrough innovation. While knowledge management could be key in this balancing strategy and shifting the organization to a more sustainable future, little is known about the challenges in the context of the energy sector. Applying a comparative case study method at a large energy company and a small energy startup, path dependency is reflected in KMS design in both cases, which could result in a slower shift to new technologies in case of the incumbent, and slower exploitation of the technological innovation in case of the startup. If a partnership is not an option for simulating structural ambidexterity, energy companies could speed up green transformation individually with smart knowledge management systems (SKMS) that support the development of contextual ambidexterity and SES.

This research aims to design a model to forecast and simulate aggregated world energy demand at distant horizons in time. This is done by estimating statistically a simplified interrelated model for the three variables considered, total primary Energy, world population and GDP. The approach intends to offer a complementary perspective to current practice, based on simulating energy demand conditional on GDP and population. The model is based on long historical series spanning the years (1900;2017) available from renowned researchers and institutions in their respective fields. The estimated models allow a forecast of future energy demand and a risk/sensitivity analysis. Alternative solutions and simulation methods are carried out to assess the robustness of the results derived. These forecasts are compared to the results of key relevant roadmaps put forward in the literature - in the range (330;408) EJ/yr for final energy consumption -, the general conclusion being that the aforementioned roadmaps assume sizeable efficiency savings, relying mainly on electrification and renewable energies deployment, that depart significantly from historical trends embodied in the model estimated - 900 EJ/yr on average, and 600 EJ/yr under favourable assumptions. These results jeopardise the unbounded GDP-growth paradigm, suggesting a replacement by alternative welfare measures as suggested by the UN human development index, the prosperity approach, and related standards.

Major concern in utilising renewable energy sources, such as solar or wind, is their intermittent nature. Therefore, whether they can be reliable energy sources to provide uninterrupted energy demand when reaching a high share of renewable energy in the system depends on the whole energy supply network. Higher flexibility of RES-based systems can be reached through the development of smart energy concepts.

The system dynamics model coupled with a geographical information system platform has been used to analyse space and time dimensions of RES potential using geo-referenced information. This approach allows analysing the whole energy system by determining the best-suited development scenario for each region separately, based on their resource, economic, and technological capabilities. Furthermore, the system dynamics model is complemented with different policies to evaluate their impact on renewable and local energy resource development and economic potential. The results show that the potential for large-scale onshore wind farm capacities with suitable land conditions could be around 5.5 GW, but the forecasted necessary wind power capacity to reach climate neutrality in 2050 is 1.55 GW. Therefore, onshore wind turbines should be promoted to move toward a smart and renewable power system in Latvia.

In Germany's future energy system wind and solar power directly cover all electricity demand for more than half of the year. Typical inclined south facing PV modules produce a strong peak around noon on sunny days. In east-west facing vertical PV modules energy yield peaks are shifted towards morning and afternoon hours. Such systems can be applied in agri photovoltaic power plants with similar energy yield per installed capacity to conventional photovoltaic systems. While installed power per area is by a factor 4 to 5 smaller, dual land use with agriculture allows for a technical potential in the terawatt hours per year range, which is comparable to half of entire German primary energy demand. In a simulation model based on the programme EnergyPLAN for Germany 2030 with 80% CO₂ reduction related to 1990 the effect of different PV power plant orientations is investigated. In the model an optimum share of around 80% vertical PV systems is found without any electricity storages and 70% with electricity storage possibilities. It could be shown that vertical PV systems enable lower storage capacities or lower utilization of gas power plants. Without any storage options a reduction of the overall carbon dioxide emissions by up to 10.2 Mt/a is possible.