Search

With the development in the field of energy and the growing demand for sustainable energy, gas–electric integrated energy systems are attracting attention as an emerging energy supply method. At the same time, with the deep application of information technology, the cyber–physical interactions of gas–electric integrated energy systems are increasingly enhanced. To this end, first, the reliability assessment indices of a gas–electric integrated energy system, which comprehensively considers the interactions between cyber–physical and different energy sources, are established in this paper to quantitatively assess the reliability level of the system under different fault and failure conditions. Second, to solve the reliability optimization problem, a comprehensive reliability enhancement optimization model is constructed in this paper, which targets the sum of the total penalties of the failure rate and average repair time modification. The impact of the cyber systems on the gas–electric integrated energy systems is transformed into a modification of the failure rate and the average repair time, and the model is solved by an adaptive Gaussian particle swarm optimization algorithm. Finally, the applicability and superiority of the adaptive Gaussian particle swarm optimization algorithm to the reliability optimization of the gas–electricity integrated energy system are verified by conducting simulation tests on the gas–electricity integrated energy system coupled with an 8-node distribution system and the 11-node natural gas system in Belgium. Furthermore, the effects of cyber systems and cyber-attacks on system reliability optimization are also analyzed to verify the effectiveness of the proposed method and the rationality of the newly defined reliability indices. [ABSTRACT FROM AUTHOR]

Thermal processes represent a significant fraction of industrial energy consumptions, and they rely mainly on fossil fuels. Thanks to technological innovation, highly efficient devices such as high-temperature heat pumps are becoming a promising solution for the electrification of industrial heat. These technologies allow for recovering waste heat sources and upgrading them at temperatures up to 200 °C. Moreover, the coupling of these devices with thermal storage units can unlock the flexibility potential deriving from the industrial sector electrification by means of Demand-Side Management strategies. The aim of this paper is to quantify the impact on the energy system due to the integration of industrial high-temperature heat pumps and thermal storage units by means of a detailed demand–supply model. To do that, the industrial heat demand is investigated through a set of thermal process archetypes. High-temperature heat pumps and thermal storage units for industrial use are included in the open-source unit commitment and optimal dispatch model Dispa-SET used for the representation of the energy system. The case study analyzed is Belgium, and the analysis is performed for different renewable penetration scenarios in 2040 and 2050. The results demonstrate the importance of a proper sizing of the heat pump and thermal storage capacity. Furthermore, it is obtained that the electrification of the thermal demand of industrial processes improves the environmental impact (84% reduction in CO2 emissions), but the positive effect of the energy flexibility provided by the heat pumps is appreciated only in the presence of a very high penetration of renewable energy sources. [ABSTRACT FROM AUTHOR]

In this paper, a Belgian tax reform plan is elaborated to respond to the EU proposal that requires member states to restructure passenger car taxation systems, preferentially based on the CO2 emissions of the car. A tax orientation on CO2 emissions alone might however favour diesel vehicles, characterised by a higher fuel efficiency, whereas they release more polluting emissions (PM and NOx) than comparable gasoline vehicles. This paper introduces a methodology, the Ecoscore, as a potential tax assessment basis. The Ecoscore is based on a well-to-wheel framework and enables a comparison of the environmental burden caused by vehicles with different drive trains and using different fuels. A new proposal for a fixed vehicle taxation system, based on the Ecoscore, is launched. In addition, its impact on the life cycle cost of conventional as well as alternative fuelled cars is measured in order to examine its steering effect towards a cleaner vehicle choice. The overall result is that current tax distortions can be corrected by restructuring the vehicle registration tax and annual circulation tax, based on the Ecoscore. To stimulate behavioural changes, such a fiscal policy should however be paired with additional policies that act on the other important aspects that determine the car purchase decision. [ABSTRACT FROM AUTHOR]

In this paper, the energy benefits of switchable insulation systems (SIS) are assessed when applied as shades for windows as well as dynamic insulation for exterior walls of residential buildings located in European countries including Belgium and Spain. A series of analyses is performed for detached houses and apartments representing common Belgian residential buildings to determine the energy performance of SIS when deployed to windows and exterior walls and operated using simplified rule-based controls. The analysis results indicate that SIS-integrated windows can achieve significant energy savings for both dwelling types in Belgium, including the elimination of any mechanical cooling and a reduction of up to 44% of heating energy end-use. Moreover, the results show that SIS can offer even more energy efficiency and thermal comfort benefits when deployed to both windows and exterior walls for residential buildings. These energy efficiency benefits are higher, especially for reducing heating needs, for the milder climates of Belgium and Spain. However, it should be noted that the energy performance of SIS could be affected substantially by windows' orientation and occupants' behavior. [ABSTRACT FROM AUTHOR]

This paper evaluates the potential energy savings when switchable insulation systems (SIS) are applied to walls of residential buildings located in Belgium and other locations in Europe. The study considers two low-energy prototypical dwellings (an apartment and a detached house) that are representative of post-2010 constructions and renovations in Belgium. Using an 3R2C-based analysis tool, the performance of both dwellings is evaluated with static and dynamic wall insulation systems. First, the switchable insulating system is described along with its associated simple 2-step rule-based control strategy. Then the modeling strategy and simulation analysis tools are presented. In Belgium, it was found that SIS-integrated walls allow energy savings up to 3.7% for space heating and up to 98% for cooling. Moreover, it was found that to further reduce the energy consumption of SIS-integrated buildings in various European climates, thermal mass placement needs to be considered. By optimizing the placement and the parameters of the various wall layers, it is possible to increase the space heating savings by up to a factor of 4 and those of cooling by up to a factor of 2.5. [ABSTRACT FROM AUTHOR]

Renewable Energy Communities consist in an emerging decentralized market mechanism which allows local energy exchanges between end-users, bypassing the traditional wholesale/retail market structure. In that configuration, local consumers and prosumers gather in communities and can either cooperate or compete towards a common objective, such as the minimization of the electricity costs and/or the minimization of greenhouse gas emissions for instance. This paper proposes data analytics modules which aim at helping the community members to schedule the usage of their resources (generation and consumption) in order to minimize their electricity bill. A day-ahead local wind power forecasting algorithm, which relies on state-of-the-art Machine Learning techniques currently used in worldwide forecasting contests, is in that way proposed. We develop furthermore an original method to improve the performance of neural network forecasting models in presence of abnormal wind power data. A technique for computing representative profiles of the community members electricity consumption is also presented. The proposed techniques are tested and deployed operationally on a pilot Renewable Energy Community established on an Medium Voltage network in Belgium, involving 2.25 M W of wind and 18 Small and Medium Enterprises who had the possibility to freely access the results of the developed data modules by connecting to a dedicated web platform. We first show that our method for dealing with abnormal wind power data improves the forecasting accuracy by 10% in terms of Root Mean Square Error. The impact of the developed data modules on the consumption behaviour of the community members is then quantified, by analyzing the evolution of their monthly self-consumption and self-sufficiency during the pilot. No significant changes in the members behaviour, in relation with the information provided by the models, were observed in the recorded data. The pilot was however perturbed by the COVID-19 crisis which had a significant impact on the economic activity of the involved companies. We conclude by providing recommendations for the future set up of similar communities. [ABSTRACT FROM AUTHOR]

The renewable energy transition has introduced new electricity tariff structures. With the increased penetration of photovoltaic and wind power systems, users are being charged more for their peak demand. Consequently, peak shaving has gained attention in recent years. In this paper, we investigated the potential of peak shaving through battery storage. The analyzed system comprises a battery, a load and the grid but no renewable energy sources. The study is based on 40 load profiles of low-voltage users, located in Belgium, for the period 1 January 2014, 00:00–31 December 2016, 23:45, at 15 min resolution, with peak demand pricing. For each user, we studied the peak load reduction achievable by batteries of varying energy capacities (kWh), ranging from 0.1 to 10 times the mean power (kW). The results show that for 75% of the users, the peak reduction stays below 44% when the battery capacity is 10 times the mean power. Furthermore, for 75% of the users the battery remains idle for at least 80% of the time; consequently, the battery could possibly provide other services as well if the peak occurrence is sufficiently predictable. From an economic perspective, peak shaving looks interesting for capacity invoiced end users in Belgium, under the current battery capex and electricity prices (without Time-of-Use (ToU) dependency). [ABSTRACT FROM AUTHOR]

In the quest to increase the share of renewable and residual energy sources in our energy system, and to reduce its greenhouse gas emissions, district heating networks and seasonal thermal energy storage have the potential to play a key role. Different studies prove the techno-economic potential of these technologies but, due to the added complexity, it is challenging to design and control such systems. This paper describes an integrated optimal design and control algorithm, which is applied to the design of a district heating network with solar thermal collectors, seasonal thermal energy storage and excess heat injection. The focus is mostly on the choice of the size and location of these technologies and less on the network layout optimisation. The algorithm uses a two-layer program, namely with a design optimisation layer implemented as a genetic algorithm and an optimal control evaluation layer implemented using the Python optimal control problem toolbox called modesto. This optimisation strategy is applied to the fictional district energy system case of the city of Genk in Belgium. We show that this algorithm can find optimal designs with respect to multiple objective functions and that even in the cheaper, less renewable solutions, seasonal thermal energy storage systems are installed in large quantities. [ABSTRACT FROM AUTHOR]

The intermittency of solar energy resources has brought a big challenge for the optimization and planning of a future smart grid. To reduce the intermittency, an accurate prediction of photovoltaic (PV) power generation is very important. Therefore, this paper proposes a new forecasting method based on the recurrent neural network (RNN). At first, the entire solar power time series data is divided into inter-day data and intra-day data. Then, we apply RNN to discover the nonlinear features and invariant structures exhibited in the adjacent days and intra-day data. After that, a new point prediction model is proposed, only by taking the previous PV power data as input without weather information. The forecasting horizons are set from 15 to 90 min. The proposed forecasting method is tested by using real solar power in Flanders, Belgium. The classical persistence method (Persistence), back propagation neural network (BPNN), radial basis function (RBF) neural network and support vector machine (SVM), and long short-term memory (LSTM) networks are adopted as benchmarks. Extensive results show that the proposed forecasting method exhibits a good forecasting quality on very short-term forecasting, which demonstrates the feasibility and effectiveness of the proposed forecasting model. [ABSTRACT FROM AUTHOR]

This experiment was designed to study the water-weakening effect of artificially fractured chalk caused by the injection of different compositions of brines under reservoir conditions replicating giant hydrocarbon reservoirs at the Norwegian Continental Shelf (NCS). NaCl, synthetic seawater (SSW), and MgCl2, with same ionic strength, were used to flood triaxial cell tests for approximately two months. The chalk cores used in this experiment originate from the Mons basin, close to Obourg, Belgium (Saint Vast Formation, Upper Cretaceous). Three artificially fractured chalk cores had a drilled central hole parallel to the flooding direction to imitate fractured chalk with an aperture of 2.25 (±0.05) mm. Two additional unfractured cores from the same sample set were tested for comparison. The unfractured samples exposed a more rapid onset of the water-weakening effect than the artificially fractured samples, when surface active ions such as Ca2+, Mg2+ and SO42− were introduced. This instant increase was more prominent for SSW-flooded samples compared to MgCl2-flooded samples. The unfractured samples experienced axial strains of 1.12% and 1.49% caused by MgCl2 and SSW, respectively. The artificially fractured cores injected by MgCl2 and SSW exhibited a strain of 1.35% and 1.50%, while NaCl showed the least compaction, at 0.27%, as expected. Extrapolation of the creep curves suggested, however, that artificially fractured cores may show a weaker mechanical resilience than unfractured cores over time. The fracture aperture diameters were reduced by 84%, 76%, and 44% for the SSW, MgCl2, and NaCl tests, respectively. Permeable fractures are important for an effective oil production; however, constant modification through compaction, dissolution, and precipitation will complicate reservoir simulation models. An increased understanding of these processes can contribute to the smarter planning of fluid injection, which is a key factor for successful improved oil recovery. This is an approach to deciphering dynamic fracture behaviours. [ABSTRACT FROM AUTHOR]

Power systems in many countries have recently undergone a significant transition towards renewable and carbon-free generation sources. Those sources pose new challenges to the grid operation due to their intermittency and uncertainty. Consequently, advanced policy strategies and technologies offering new flexibility solutions on the inelastic demand side are required to maintain the reliability of power systems. Given the diversity of situations, legislation and needs across European countries and the varying nature of distribution system operators, this article reviews the deployment of demand side flexibility at national level to identify best practices and main barriers. The analysis concerns European countries of different progress in solutions that leverage flexibility towards offering electricity grid services. The scope is to explore the operation principles of European electricity markets, to assess the participation of emerging flexible resources, and to propose new approaches that facilitate the integration of flexible assets in the distribution grid. The countries reviewed are the United Kingdom, Belgium, Italy and Greece. These countries were selected owing to their diversity in terms of generation mix and market design. Barriers for market access of flexibility resources are also identified in order to form relevant country-specific recommendations. [ABSTRACT FROM AUTHOR]

Wind and solar energies present a time and space disparity that generally leads to a mismatch between the demand and the supply. To harvest their maximum potentials, one of the main challenges is the storage and transport of these energies. This challenge can be tackled by electrofuels, such as hydrogen, methane, and methanol. They offer three main advantages: compatibility with existing distribution networks or technologies of conversion, economical storage solution for high capacity, and ability to couple sectors (i.e., electricity to transport, to heat, or to industry). However, the level of contribution of electric-energy carriers is unknown. To assess their role in the future, we used whole-energy system modelling (EnergyScope Typical Days) to study the case of Belgium in 2050. This model is multi-energy and multi-sector. It optimises the design of the overall system to minimise its costs and emissions. Such a model relies on many parameters (e.g., price of natural gas, efficiency of heat pump) to represent as closely as possible the future energy system. However, these parameters can be highly uncertain, especially for long-term planning. Consequently, this work uses the polynomial chaos expansion method to integrate a global sensitivity analysis in order to highlight the influence of the parameters on the total cost of the system. The outcome of this analysis points out that, compared to the deterministic cost-optimum situation, the system cost, accounting for uncertainties, becomes higher (+17%) and twice more uncertain at carbon neutrality and that electrofuels are a major contribution to the uncertainty (up to 53% in the variation of the costs) due to their importance in the energy system and their high uncertainties, their higher price, and uncertainty. [ABSTRACT FROM AUTHOR]

Recent EU legislation enforces the integration of European balancing markets, with harmonized products and international platforms for the procurement and activation of reserves; nonetheless, different power balancing strategies remain. The Netherlands and Belgium encourage market participants to support balancing the control block by publishing real-time information. This article refers to such concepts as smart balancing, and a market simulation tool was developed to assess the relevant market parameters for effective smart balancing. This shall contribute to the true integration of real-time balancing energy markets. The scope of the assessment of relevant market parameters was Germany, and the results showed that a pricing scheme had less impact on the results, as currently is understood by European TSOs and regulators. Moreover, the accuracy and frequency of real-time publication indicate the effectiveness of smart balancing and the associated reduction of the activation of balancing energy and associated costs. Consequently, this article proposed a road map for Germany to introduce an adapted smart balancing approach, starting with a simple traffic light. [ABSTRACT FROM AUTHOR]

The EU aims to become the world's first climate-neutral continent by 2050. In order to meet this target, the integration of high shares of Renewable Energy Sources (RESs) in the energy system is of primary importance. Nevertheless, the large deployment of variable renewable sources such as wind and photovoltaic power will pose important challenges in terms of power management. For this reason, increasing the system flexibility will be crucial to ensure the security of supply in future power systems. This work investigates the flexibility potential obtainable from the diffusion of Demand Response (DR) programmes applied to residential heating for different renewables penetration and power system configuration scenarios. To that end, a bottom-up model for residential heat demand and flexible electric heating systems (heat pumps and electric water heaters) is developed and directly integrated into Dispa-SET, an existing unit commitment optimal dispatch model of the power system. The integrated model is calibrated for the case of Belgium and different simulations are performed varying the penetration and type of residential heating technologies, installed renewables capacity and capacity mix. Results show that, at country level, operational cost could be reduced up to €35 million and curtailment up to 1 TWh per year with 1 million flexible electric heating systems installed. These benefits are significantly reduced when nuclear power plants (non-flexible) are replaced by gas-fired units (flexible) and grow when more renewable capacity is added. Moreover, when the number of flexible heating systems increases, a saturation effect of the flexibility is observed. [ABSTRACT FROM AUTHOR]

Since the 1990s, remote sensing data have been available to monitor the surface movement for long periods of time. The analysis of satellite data shows that there is still residual subsidence (i.e., with average rates of about −10 mm/year) several decades after mining longwall panels in an area. Several years after the underground infrastructure was sealed, the surface started to move upwards. In the past, it often was claimed that movement of the surface was limited in time, i.e., a few years after mining a longwall panel. This is not the case for the conditions of the Campine coal basin, Belgium. This knowledge is important when one wants to design new operations in deep coal seams, but also when planning to stop the underground mining and to seal the access to the mine. [ABSTRACT FROM AUTHOR]

To avoid the geographical and topographical prerequisites of the conventional pumped hydro energy storage, the use of underground cavities as water reservoirs allows countries without steep topography, such as Belgium, to increase the potential of the energy storage capacity. Belgium abounds in disused mines and quarries convertible into water basins. In this article, two Belgian case studies are presented and discussed for their singularity. A slate quarry in Martelange is discussed in technical aspects proposing three operating scenarios. Moreover, a preliminary economic analysis of the underground pumped storage system and a greenhouse gas emission evaluation for the storage system's lifetime are presented. The analysis for a 100 MW power plant estimates a total initial investment of over 12 million euros and two million of CO 2 avoided over its lifetime. This article also proposes the use of the coal mine 500 m deep of Pérronnes-lez-Binche. The mine representation discussed here offers a high energy capacity, but the substantial head drop (from about 500 to 200 m) challenges the selection of the hydraulic turbomachinery. A 1D simulation computed in SIMSEN draws out the behaviour of the unusual hydraulic configuration of turbines in series. [ABSTRACT FROM AUTHOR]

Underground pumped-storage hydropower (UPSH) is a promising technology to manage the electricity production in flat regions. UPSH plants consist of an underground and surface reservoirs. The energy is stored by pumping water from the underground to the surface reservoir and is produced by discharging water from the surface to the underground reservoir. The underground reservoir can be drilled, but a more efficient alternative, considered here, consists in using an abandoned mine. Given that mines are rarely waterproofed, there are concerns about the consequences (on the efficiency and the environment) of water exchanges between the underground reservoir and the surrounding medium. This work investigates numerically such water exchanges and their consequences. Numerical models are based on a real abandoned mine located in Belgium (Martelange slate mine) that is considered as a potential site to construct an UPSH plant. The model integrates the geometrical complexity of the mine, adopts an operation scenario based on actual electricity prices, simulates the behavior of the system during one year and considers two realistic scenarios of initial conditions with the underground reservoir being either completely full or totally drained. The results show that (1) water exchanges may have important consequences in terms of efficiency and environmental impacts, (2) the influence of the initial conditions is only relevant during early times, and (3), an important factor controlling the water exchanges and their consequences may be the relative location of the natural piezometric head with respect the underground reservoir. [ABSTRACT FROM AUTHOR]

Different scenarios at different scales must be studied to help define long term policies to decarbonate our societies. In this work, we analyse the Belgian energy system in 2035 for different carbon emission targets, and accounting for electricity, heat, and mobility. To achieve this objective, we applied the EnergyScope Typical Days open source model, which optimises both the investment and the operation strategy of a complete energy system for a target year. The model includes 96 technologies and 24 resources that have to supply, hourly, the heat, electricity, mobility, and non-energy demands. In line with other research, we identify and quantify, with a merit order, different technological steps of the energy transition. The lack of endogenous resources in Belgium is highlighted and estimated at 275.6 TWh/y. It becomes obvious that additional potentials shall be obtained by importing renewable fuels and/or electricity, deploying geothermal energy, etc. Aside from a reduction of the energy demand, a mix of solutions is shown to be, by far, the most cost effective to reach low carbon emissions. [ABSTRACT FROM AUTHOR]

It is unclear whether the production of biochar is economically feasible. As a consequence, firms do not often invest in biochar production plants. However, biochar production and application might be desirable from a societal perspective as it might entail net environmental benefits. Hence, the aim of this work has been to assess and monetize the environmental impacts of biochar production systems so that the environmental aspects can be integrated with the economic and social ones later on to quantify the total return for society. Therefore, a life cycle analysis (LCA) has been performed for two potential biochar production systems in Belgium based on two different feedstocks: (i) willow and (ii) pig manure. First, the environmental impacts of the two biochar production systems are assessed from a life cycle perspective, assuming one ton of biochar as the functional unit. Therefore, LCA using SimaPro software has been performed both on the midpoint and endpoint level. Biochar production from willow achieves better results compared to biochar from pig manure for all environmental impact categories considered. In a second step, monetary valuation has been applied to the LCA results in order to weigh environmental benefits against environmental costs using the Ecotax, Ecovalue, and Stepwise approach. Consequently, sensitivity analysis investigates the impact of variation in NPK savings and byproducts of the biochar production process on monetized life cycle assessment results. As a result, it is suggested that biochar production from willow is preferred to biochar production from pig manure from an environmental point of view. In future research, those monetized environmental impacts will be integrated within existing techno-economic models that calculate the financial viability from an investor's point of view, so that the total return for society can be quantified and the preferred biochar production system from a societal point of view can be identified. [ABSTRACT FROM AUTHOR]