Smart Energy最新文献

With the sudden threat of gas supply interruption through the Ukraine-Russian war, the importance of improving buildings' energy efficiency has become even more relevant. Mainly during 2022 and 2023, there was an intensive process to launch a recast Energy Performance of Buildings Directive, to assure favourable policy framework conditions. In this context, the current paper addresses the following question: How does the consideration of staged renovation change the view of cost-optimal building standards and related building renovation assessments? For that, this paper analyses the staged building renovation and the time perspective when they are performed related to cost-optimal building standards. The workflow relies on the following methods: (1) cost-optimal methodology and global costs calculation and (2) mixed-integer optimisation to derive optimum timing of staged renovation under household budget constraints. The analysis consists of a country comparison (Spain, Germany and Sweden) and an evaluation of different energy efficiency measures. The main conclusion is that in staged renovations, the cost-optimal variant was in many cases the climate-optimal one when using the metric cumulative CO₂ emission. Although the metric “cumulative CO2 emissions” is not suggested by the EPBD yet, this metric represents the depth and time perspective of renovation activities. Therefore, in order to speed up building stock decarbonisation cost-optimal methods alone are not sufficient to increase buildings' energy efficiency and climate neutrality in a fast way. In addition to that, considering households’ budget as optimisation variable can be an effective to assess the time when renovation activities are performed.

As the world moves to clean, renewable energy, questions arise as to how best to produce and use hydrogen. Here, we propose using hydrogen produced only by electrolysis with clean, renewable electricity (green hydrogen). We then test the impact of producing such hydrogen intermittently versus continuously for steel and ammonia manufacturing and long-distance transport via fuel cells on the cost of matching electricity, heat, cold, and hydrogen demand with supply and storage on grids worldwide. An estimated 79, 32, and 91 Tg-H₂/y of green hydrogen are needed in 2050 among 145 countries, for steel, ammonia, and long-distance transport, respectively. Producing and compressing such hydrogen for these processes may consume ∼12.1% of the energy needed for end-use sectors in these countries after they transition to 100% wind-water-solar (WWS) in all such sectors. This is less than the energy needed for fossil fuels to power the same processes. Due to the variability of WWS electricity, producing green hydrogen intermittently, rather than continuously, thus with electrolyzer use factors significantly below unity (0.2–0.65), may reduce overall energy costs with 100% WWS. This result is subject to model uncertainties but appears robust. In sum, grid operators should incorporate intermittent green hydrogen production and use in planning.

The ambitious legislation driven by climate change, makes it necessary to focus more strongly on previously untapped greenhouse gas saving potentials, such as the mobile supply of renewable electrical energy which can create geographical flexibility. Consumers are supplied with electrical energy by the mobile energy system, whereby the energy can potentially come from the photovoltaic modules (PV), the diesel generator (DG), the fuel cell (FC) or the battery (EES) contained in the overall system. Exemplary customers of the service can be, e.g., road construction sites, festivals or other temporary events or also local distribution grid balancing applications. Given exogenous PV production and load profiles, this study determines the cost-optimal sizing of the system components (FC, DG, and EES) while deriving the optimal operating strategy for the overall system using mixed integer linear programming (MILP). In addition to investment and fuel costs, emission costs are integrated, which primarily occur in the context of DG operation. The model is implemented in Python in the optimisation environment Pyomo and solved by the Gurobi solver. The simulation is based on three scenarios for different combinations of PV production and load profiles as well as various hydrogen and emission price scenarios. It turns out, that the optimal sizes of the FC and the DG are between 0.5 and 2 kW for 60% and 0% demand coverage through PV respectively. For the battery, an optimal size between 1 and 4.8 kWh can be derived analogously.

Hydrogen is experiencing an unprecedented global hype. Hydrogen is globally discussed as a possible future energy carrier and regarded as the urgently needed building block for the much needed carbon-neutral energy transition of hard-to-abate sectors to mitigate the effects of global warming. This article provides synthesised, measurable sustainability criteria for analysing green hydrogen production proposals and strategies. Drawn from expert interviews and an extensive literature review this article proposes that a sustainable hydrogen production should consider six impact categories; Energy transition, Environment, Basic needs, Socio-economy, Electricity supply, and Project planning. The categories are broken down into sixteen measurable sustainability criteria, which are determined with related indicators. The article concludes that low economic costs can never be the only decisive criterion for the hydrogen production; social aspects must be integrated along the entire value chain. The compliance with the criteria may avoid social and ecological injustices in the planning of green hydrogen projects and increases inter alia the social welfare of the affected population.

Developing affordable and scalable energy storage solutions are essential to decarbonizing power systems. The conversion of renewable electricity into chemical energy carriers such as ammonia has attracted extensive attention from academia and industry. Many Power-to-Ammonia (PtA) plants have been conceptualized and developed worldwide in recent years. The PtA plant is an integration of multiple electrochemical processes, each with a distinct set of operational constraints and cost structure. One of the problems in the operation of PtA plants is the optimal scheduling of the hydrogen buffer in PtA plants considering the operational characteristics of electrochemical processes and the volatility and uncertainty of electricity prices. In this paper, a two-stage Markov-Decision-Process (MDP) approach is proposed. The computational challenges brought by the infinite optimization horizon and non-concavity of cost functions are resolved. The first stage solution is based on the periodic MDP approach, which captures the periodic structure of electricity prices. The second stage solution gives optimal real-time decisions based on a rolling-horizon MDP approach. Numerical results show that the accurate representations of the cost functions and the optimization horizon using the proposed method are necessary, while the linearization of cost functions and the truncation of the optimization horizon lead to notable deviations from the optimality.

Energy system modelling may support policymakers in their energy planning efforts. Energy system modellers usually identify the optimal system configuration based on an economic objective function, or in multi-objective optimization, a combination of multiple objectives such as greenhouse gas emissions and total system cost. However, there could be political, socio-economic, or environmental reasons justifying a policymaker's selection of a solution that is slightly more costly or greenhouse gas polluting than the uniquely optimal solution. Solely focusing on the uniquely optimal solution disregards potentially diverse alternatives, which based on different evaluation metrics could even be preferable. In response to this challenge, the evaluation of near-optimal solutions is gaining attention in the energy system modelling field as an extension of traditional multi-objective optimization studies and as a way to bridge the gap between simulation and optimization approaches. In this study, we explore near-optimal solutions, outline the diversity of near-optimal solutions, and evaluate the relevance of these solutions in the context of energy planning. The proposed methodology is applied to the Italian case to determine its potential as a tool to support policymakers in evaluating energy system scenarios from a selection of optimal and near-optimal solutions.

A smart demand response control system aiming towards real-time operational optimisation of district heating (DH) network temperature levels, both in the return and supply pipes, has been developed in the TEMPO project. The return temperature is mainly dependent on the demand side. The controller optimises its value through control of the customers’ heat load. The network supply temperature, however, is directly controllable on the production side. The capabilities of supply temperature control are twofold. On the one hand, lowering the network supply temperature as close as possible to the limits determined by customer thermal demands. On the other hand, activating the intrinsic thermal capacity of the piping to temporarily store heat and thereby shifting the heat load in time. This provides additional energy flexibility potential on top of building demand response.

In this study, the two features of the smart control system have been tested in a part of the DH network of Brescia (Italy). A cloud-based platform is used to collect real-time data from various sources and to communicate control signals calculated by the smart controller. The article presents the results of the tests and an evaluation of the controller performance. The analysis indicates that daily flow-weighted average return temperature reductions of almost 1 K on average can be achieved, and up to 15 K instantaneously. Using supply temperature control, the daily peak load energy supply could be reduced by 262 kWh (34%) on average, by shifting the heat load.

The study develops energy scenarios for Greater Kampala Metropolitan Area (GKMA). GKMA is Uganda's capital metropolis with no focused energy policy framework. The study uses TIMES-VEDA to assess sustainable low-carbon development using BAU, Kabejja, Carbon-Tax, and Lutta scenarios. The study examines commercial, industrial, transportation, residential, agricultural, and electricity generation activities that support economic development. BAU is the baseline case with limited commitment to a low-carbon future. Kabejja, Carbon-Tax, and Lutta are the alternative scenarios with distinct carbon abatement policies. The bottom-up analysis suggests that should policy trends continue as BAU, consumption, and CO₂ emissions upsurge significantly. However, consumption and carbon emissions lessen as the energy management system tends to a near-zero carbon abatement strategy. Lutta is the best pathway for a sustainable future, provided the metropolis adopts the low-carbon electrification of the GKMA energy policy, with the setting up of an electrified Kampala metro becoming the central focus for future policy shifts over the planning horizon.

During recent years, electrofuels (fuels from electricity, water, and carbon) have gained increased interest as substitute for fossil fuels in all energy and chemical sectors. The feasibility of electrofuels has been assessed from a range of aspects but no study has assessed the land area needed if scaling up the production based on renewables. The amount of land on Earth is limited and the competition for land, in a long-term perspective, imposes a risk of, e.g., increased food prices and biodiversity losses. The aim of this paper is to assess how much land area it would require if all fossil fuels were substituted by electrofuels (‘All electrofuel’-scenario) and compare this with the area needed if all fossil fuels were substituted by bioenergy (‘All biomass’-scenario) or by electricity (‘All electric’-scenario). Each scenario represents extreme cases towards fully renewable energy systems to outline the theoretical area needed. Main conclusions are (1) the electricity demand, if substituting all fossil fuels with electrofuels, is huge (1540 EJ) but technically obtainable, demanding 1.1% of the Earth's surface, for solar panels, in the most optimistic case, and (2) the sustainable technical potential for biomass cannot alone substitute all fossil fuels, unless radical energy demand reductions.

Sector coupling improves energy system efficiency by maximising potential synergies among energy sectors. This paper aims to assess the sector coupling of electricity, transport, and cooling on the Java and Bali islands, Indonesia. Future energy systems in 2040, focussing on decarbonised electricity sector with high electric vehicles deployment and district cooling penetration, were simulated using EnergyPLAN. A bottom-up calculation approach was applied to determine demand in the transport sector. In the cooling sector, geospatial analysis was employed to quantify cooling demand and locate potential district cooling networks in Jakarta. Six scenarios were explored based on their energy demand and supply characteristics. Modelling results show that the sector coupling of three sectors could reduce primary energy supply (PES), CO₂ emissions and annual costs. The most suitable scenario has about 8% lower PES, 14% lower CO₂ emissions and 2% less annual costs compared to the business-as-usual scenario. Results also show that transport electrification could only effectively and significantly decrease CO₂ emissions if its electricity demand is produced from renewables. Transport electrification with large scale integration of renewables could also lower the annual costs by decreasing fossil fuel costs in the transport and electricity sectors.