• Energy Research
• Open Access close
• Closed Access close
• Restricted close
• Open Source close
• other engineering and technologies close
• BE close

Abstract Emissions and efficiency of a pellet boiler (40 kW) at nominal load were compared with emissions and efficiency at reduced load, while fired with six biomass pellets. The pellets include reed canary grass ( Phalaris arundinacea ), pectin waste from citrus shells ( Citrus reticulata ), sunflower husk ( Helianthus annuus ), peat, wheat straw ( Triticum aestivum ) and wood pellets. The measurements of emissions comprised of carbon monoxide (CO), nitrogen oxides (NO x ), sulphur oxides (SO x ) and flue dust mass concentrations (using DIN plus and isokinetic sampling techniques). Emissions varied as a function of operational loads, for each type of pellets. The CO emissions were insignificant with reed canary grass (RCG), citrus pectin waste (CPW) and straw pellets at nominal load, however, at reduced load same pellets emitted 1.9, 4.0 and 7.4 times higher CO than wood pellets, respectively. Peat pellets emitted maximum CO at nominal load (4221.1 mgNm −3 , 12.6 times higher than wood pellets) however; at reduced load CO emission was insignificant. The highest NO x emissions were reported with CPW, which were 3.4 and 4.6 times higher than wood pellets at nominal load and reduced load, respectively. Dust emissions were highest with sunflower husk and lowest with RCG pellets, at both operational modes. The best performance was reported with wood pellets, followed by RCG and pectin pellets, however, wood pellets combustion emitted 1.7 and 2.0 times higher dust DIN plus than RCG at nominal and reduced loads, respectively. Not only fuel specific combustion optimization but also operational load specific optimization is essential for efficient use of agro-pellets in this type of boilers.

In the current situation with the unprecedented deployment of clean technologies for electricity generation, it is natural to expect that storage will play an important role in electricity networks. This paper provides a qualitative methodology to select the appropriate technology or mix of technologies for different applications. The multiple comparisons according to different characteristics distinguish this paper from others about energy storage systems. Firstly, the different technologies available for energy storage, as discussed in the literature, are described and compared. The characteristics of the technologies are explained, including their current availability. In order to gain a better perspective, availability is cross-compared with maturity level. Moreover, information such as ratings, energy density, durability and costs is provided in table and graphic format for a straightforward comparison. Additionally, the different electric grid applications of energy storage technologies are described and categorised. For each of the categories, we describe the available technologies, both mature and potential. Finally, methods for connecting storage technologies are discussed.

Nature-based solutions may actively reduce hydro-meteorological risks in urban areas as a part of climate change adaptation. However, the main reason for the increasing uptake of this type of solution is their many benefits for the local inhabitants, including recreational value. Previous studies on recreational value focus on studies of existing nature sites that are often much larger than what is considered as new NBS for flood adaptation studies in urban areas. We thus prioritized studies with smaller areas and nature types suitable for urban flood adaptation and divided them into four common nature types for urban flood adaptation: sustainable urban drainage systems, city parks, nature areas and rivers. We identified 23 primary valuation studies, including both stated and revealed preference studies, and derived two value transfer functions based on meta-regression analysis on existing areas. We investigated trends between values and variables and found that for the purpose of planning of new NBS the size of NBS and population density were determining factors of recreational value. For existing NBS the maximum travelling distance may be included as well. We find that existing state-of-the-art studies overestimate the recreational with more than a factor of 4 for NBS sizes below 5 ha. Our results are valid in a European context for nature-based solutions below 250 ha and can be applied across different NBS types and sizes.

This article demonstrates how a cultural reading of consumption that focuses on the meaning and materiality of domestic indoor microclimates can contribute to conceptual developments in the field of practice theory that refocus attention on cultural patterns, including prevailing norms and prescriptions regarding indoor temperature and thermal comfort. Drawing on evidence collected during a research-led change initiative that encouraged people to reduce energy use in the home by lowering indoor temperature to 18°C, we deploy the heuristic device of “indoor microclimate as artifact” to show how the manifestation of this new artifact initiated significant changes in everyday practices that revolve around heating. We observe that these changes may also spill over into the public sphere – from home to workplace. By making the microclimate a tangible and visible thing, we describe how people appropriate and appreciate this new object of consumption, what it says about different bodies in diverse and bounded spaces, and what the artifact as a commodity reveals about broader systems of heating and energy provision, and associated actors. Due to the increasing spread of central heating and the growing importance of complex technological devices to monitor and control indoor temperature, heating is no longer a practice in and of itself for many urban dwellers in Europe. However, when people appropriate the indoor microclimate, new heating-related practices emerge that can lead to energy sufficiency. We thus argue that by deliberately “materializing” domestic indoor microclimate as part of a change initiative, more sustainable forms of energy use can be made to matter.

Abstract Many countries committed themselves in the Kyoto protocol to reduce greenhouse gas (GHG) emissions. Some of these targeted emission reductions could result from a switch from coal-fired to gas-fired electricity generation. The focus in this work lies on Western Europe, with the presence of the European Union Emission Trading Scheme (EU ETS). For the switching to occur, several conditions have to be fulfilled. First, an economical incentive must be present, i.e. a sufficiently high European Union Allowance (EUA) price together with a sufficiently low natural gas price. Second, the physical potential for switching must exist, i.e. at a given load, there must remain enough power plants not running to make switching possible. This paper investigates what possibilities exist for switching coal-fired plants for gas-fired plants, dependent on the load level (the latter condition above). A fixed allowance cost and a variable natural gas price are assumed. The method to address GHG emission reduction potentials is first illustrated in a methodological case. Next, the GHG emission reduction potentials are addressed for several Western European countries together with a relative positioning of their electricity generation. GHG emission reduction potentials are also compared with simulation results. GHG emission reduction potentials tend to be significant. The Netherlands have a very widespread switching zone, so GHG emission reduction is practically independent of electricity generation. Other counties, like Germany, Spain and Italy could reduce GHG emissions significantly by switching. With an allowance cost following the switch level of a 50% efficient gas-fired plant and a 40% efficient coal-fired plant in the summer season (like in 2005), the global GHG emission reduction (in the electricity generating sector) for the eight modeled zones could amount to 19%.

The widespread use of optimization methods in the design phase of District Heating Networks is currently limited by the availability of scalable optimization approaches that accurately represent the network. In this paper, we compare and benchmark two different approaches to non-linear topology optimization of District Heating Networks in terms of computational cost and optimality gap. The first approach solves a mixed-integer non-linear optimization problem that resolves the binary constraints of pipe routing choices using a combinatorial optimization approach. The second approach solves a relaxed optimization problem using an adjoint optimization approach, and enforces a discrete network topology through penalization. Our benchmark shows that the relaxed penalized problem has a polynomial computational cost scaling, while the combinatorial solution scales exponentially, making it intractable for practical-sized networks. We also evaluate the optimality gap between the two approaches on two different District Heating Network optimization cases. We find that the mixed-integer approach outperforms the adjoint approach on a single-producer case, but the relaxed penalized problem is superior on a multi-producer case. Based on this study, we discuss the importance of initialization strategies for solving the optimal topology and design problem of District Heating Networks as a non-linear optimization problem.

Electric water heaters have the ability to store energy in their water buffer without impacting the comfort of the end user. This feature makes them a prime candidate for residential demand response. However, the stochastic and nonlinear dynamics of electric water heaters, makes it challenging to harness their flexibility. Driven by this challenge, this paper formulates the underlying sequential decision-making problem as a Markov decision process and uses techniques from reinforcement learning. Specifically, we apply an auto-encoder network to find a compact feature representation of the sensor measurements, which helps to mitigate the curse of dimensionality. A wellknown batch reinforcement learning technique, fitted Q-iteration, is used to find a control policy, given this feature representation. In a simulation-based experiment using an electric water heater with 50 temperature sensors, the proposed method was able to achieve good policies much faster than when using the full state information. In a lab experiment, we apply fitted Q-iteration to an electric water heater with eight temperature sensors. Further reducing the state vector did not improve the results of fitted Q-iteration. The results of the lab experiment, spanning 40 days, indicate that compared to a thermostat controller, the presented approach was able to reduce the total cost of energy consumption of the electric water heater by 15%. Submitted to IEEE transaction on smart grid