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This article presents a numerical study on the building integration of a liquid sorption storage combined with an air-source electric heat pump. The double staging of the sorption storage (i.e. a chemical heat pump) and an electric heat pump leads to significant electricity demand and CO2 emission reductions. Further, it provides an effective coupling between the heat demand of the building and the electricity supply, allowing for optimal integration of solar energy using photovoltaics. For the buildings analyzed, an autarky level of up to 83% is achieved. Winter electricity demand and emission reductions respectively reached values of up to 41%. The storage integration was studied performing dynamic building simulations. The simulation model for the liquid sorption storage was based on a grey box approach. This features a simple analytical model being tuned to match with performance data available from experiments conducted on a lab scale test rig. The presented integration of a compact seasonal thermal energy storage at the building scale represents a promising approach for a grid compliant integration of renewable energy, significantly reducing electricity demand peaks and related CO2 emissions in winter., Applied Energy, 301, ISSN:0306-2619, ISSN:1872-9118

Seasonal thermal energy storage is an effective measure to enable a low carbon future through the integration of renewables into the energy system. Borehole thermal energy storage (BTES) provides a solution for long-term thermal energy storage and its operational optimization is crucial for fully exploiting its potential. This paper presents a novel linearized control-oriented model of a BTES, describing the storage temperature dynamics under varying operating conditions, such as inlet temperature, mass-flow rate and borehole connection layouts (e.g. in-series, in-parallel or mixed). It supports an optimization framework, which was employed to determine the best operating conditions for a heat pump-driven BTES, subject to different C O 2 intensity profiles of the electricity. It was demonstrated that this boundary condition, due to its seasonal variation, is critical for the optimal operation of the system, as increasing heat pump efficiency in winter while accepting a lower one in summer can be beneficial. Results for an exemplary district case, subject to two different C O 2 intensity profiles, show that a lower relative intensity in summer compared to the one in winter leads to a higher optimal operating temperature of the storage. The district system studied is heating-dominated, effectively enabling the BTES to cover only 20% of the total heat demand, leading to limited total yearly CO2 emissions savings of 2.2% to 4.3%. When calculating the benefits associated with the heating and cooling demand handled by the BTES, a higher C O 2 emission reduction in the range of 12.8%–19.9% was found. This highlights the BTES potential when subject to more balanced loads.

In this paper we will describe didactic elements in the Horizon 2020 project FCHgo. This project is directed at children and adolescents between 8 and 18 years old. Its ultimate goal is to raise awareness for renewable energy sources, in particular hydrogen as a fuel and fuel cells for electric power. As part of the project, we are developing a toolkit for teachers and pupils, based upon a narrative approach to physical science and engineering. We believe the narrative approach to be best suited for this project because it allows us to take into account the cognitive tools available to pupils at various stages of their development.

A review of wind turbine technology showed that many flaws in both the flow models and computations are involved in the traditional fundamentals. While traditional methods for design and computation are all based on the airfoil theory, a new method based on turbine theories has been developed and is shown to be ideally applicable. Against the traditional method, the new method also considers non-uniform pressure distribution in flows downstream of the rotor plane and is thus highly accurate. The blade efficiency or tip swirl number has been introduced. It enables computation of the power coefficient to be very reasonable. Its optimum can be directly applied to the geometrical design of turbine blades. Between the tip speed ratio X, blade efficiency e, and power coefficient cp, a closed solution of both the optimum design and the operation of wind turbines exists. It is demonstrated that the maximum achievable power coefficient can be 10% larger than that predicted by all previous theories.

​© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works., The decreasing cost of photovoltaic (PV) systems allows the production of cheap renewable electricity. This has led to an increasing number of installed systems during the past years. Since the storage of electrical energy is still rather expensive, the optimization of the self-consumption coverage gains importance. One solution to higher self-consumption is a method called “PV-to-Heat”, where excess PV energy is not fed into the grid but stored in the form of hot water in the domestic boiler. This article describes a simplified hardware approach for a three-phase PWM chopper for AC/AC conversion. It is suited for low inductive loads like electric heaters. Compared to existing systems, the proposed converter design offers equal or better performance at very low cost and small size. The circuit allows full control of the power flow and provides sinusoidal and symmetrical load currents. The average electrical efficiency is 94.7% for a 6 kW test system. Unlike certain commercial products, there is no need to use a custom heater or access the star point of the load resistor.

Exergy analysis has been widely used to assess refrigeration systems by evaluating exergy losses or exergy efficiency. The latter is mostly used as an indicator to determine the system performance, which requires the comparison of the actual system with its idealized reversible version, but not the practical achievable efficiency. Therefore, a practice-oriented evaluation method for refrigeration plants in free cooling operation is proposed, based on exergy analysis and technical standards as baseline. By considering the exergy input of auxiliary devices, the overall design of hydraulic circuits can be assessed on subsystem level. The achievable optimization potential compared to the state of the art in technology and the performance is revealed with the introduced optimization potential index (OPI). The application is demonstrated on a case study, where the analysis reveals an adequate operation of the field plant in general. Most cooling locations show potential for improvement, which is indicated by an OPI superior to zero. Moreover, the auxiliary electrical exergy input shows the same magnitude as the thermal exergy input, which emphasizes the importance of reducing the electrical energy usage of auxiliary devices in refrigeration plants to increase the performance.

Exergy analysis allows us to determine the quality of energy sources and losses due to irreversibilities through a system. However, the quantification of possible improvements as compared with the state of the art in technology is complicated. Typically, it is referred to the thermodynamic ideal, which is not achievable in practice. Therefore, this paper introduces the exergy optimization potential index, a new key figure based on exergy analysis and technical standard values, in order to assess the achievable performance and to determine possible improvements in vapor compression refrigeration plants with cold water distribution. By dividing the plant into different subsystems (dry cooler, refrigeration machine, cold storage & transport and cooling location), each of them can be assessed individually. Furthermore, by comparing the actual exergy effort with reference values, the interpretation of the results becomes straightforward. The applicability of the method is demonstrated on two theoretical test cases and on a real system. The investigated refrigeration plant performs well in general, which is revealed with an average optimization potential index inferior to 0. However, the subsystem dry cooler shows potential for improvement in the period of May to mid of July. Also, three out of seven cooling locations have performance issues, which is indicated with an average optimization potential index of at least 0.07. Overall, the electrical exergy input has a major impact on the optimization potential index. This reveals the importance of minimizing the electrical energy usage, as it is the main overhead in the operating cost of refrigeration plants.

In almost 30 years of PEM fuel cell modeling, countless numerical models have been developed in science and industrial applications, almost none of which have been fully disclosed to the public. There is a large need for standardization and establishing a common ground not only in experimental characterization of fuel cells, but also in the development of simulation codes, to prevent each research group from having to start anew from scratch. Here, we publish the first open standalone implementation of a full-blown, steady-state, non-isothermal two-phase model for low-temperature PEM fuel cells. It is based on macro-homogeneous modeling approaches and implements the most essential through-plane transport processes in a five-layer MEA. The focus is on code simplicity and compactness with only a few hundred lines of clearly readable code, providing a starting point for more complex model development. The model is implemented as a standalone MATLAB function, based on MATLAB's standard boundary value problem solver. The default simulation setup reflects wide-spread commercially available MEA materials. Operating conditions recommended for automotive applications by the European Commission are used to establish new fuel cell simulation base data, making our program a valuable candidate for model comparison, validation and benchmarking., 13 pages, 7 figures, 7 tables

Optical losses in a photoelectrochemical (PEC) cell account for a substantial part of solar-to-hydrogen conversion losses, but limited attention is paid to the detailed investigation of optical losses in PEC cells. In this work, an optical model of combined coherent and incoherent light propagation in all layers of the PEC cell based on spectroscopic measurements is presented. Specifically, photoelectrodes using transparent conductive substrates such as F:SnO2 coated with thin absorber films are focused. The optical model is verified for hematite photoanodes fabricated by atomic layer deposition and successfully used to determine wavelength-dependent reflection, transmission, layer absorptances, and charge generation rates. Furthermore, the calculated absorptances enable 20–30% more accurate calculations of the absorbed photon-to-current efficiency of PEC cells. Our optical model is a powerful tool for the optimization of the optical performance of PEC cells focusing on single absorber or tandem configurations and represents a cornerstone of a complete (optical and electrical) model for PEC water splitting cells.

In this work an overview to the dynamic model of Continental Europe from ENTSO-E, where the main characteristics are summarized and discussed, is introduced. Then, the response of the system to different parameter variations is presented. The objective of the analysis is to identify how the system reacts and evolve on time to fluctuation on standard parameters such as machine saturations, voltage regulator gains, inertia values and loads. Nonlinear dynamic simulations using the professional software DIgSILENT PowerFactory are displayed to compare results.

This paper presents a qualitative and quantitative feasibility analysis of the Power-to-Gas (PtG) technology in the future Swiss power grid which will be characterized by a significant share of intermittent renewable energy sources. The focus is placed on establishing a resolution to effectively integrate renewable energy sources (RES) into Swiss power grid through energy storage systems including pumped hydro storage (PHS) and PtG, which is commonly known to offer the advantage of a long-term storage over other storage options. The resolution will be presented through the analysis of designed scenarios that reflect the current and future energy profile of Switzerland, and will utilize the strength of a model predictive controller (MPC) with respect to the optimized dispatch of storage capacity including the existing PHS and the proposed PtG plants in addition thereto.

According to the Energy Strategy 2050 set forth by the Swiss federal government, Photovoltaic (PV) energy shall make up one fifth of the nation's total energy production in 2050. Such a drastic expansion rate of PV and the resulting excess energy thereof can lead to so-called reverse power flow in the low voltage (LV) grid as demonstrated in previous studies. Power-to-Gas (PtG) represents a suitable storage solution to resolve the situation by absorbing the excess PV energy. This paper presents a qualitative and quantitative feasibility analysis of the PtG technology in the future Swiss LV grid. For this purpose, PtG is integrated in simulation into the grid for absorbing the excess PV energy while producing hydrogen. This hydrogen is assumed to be sold in the mobility sector. Three different operational scenarios are established with respect to the input energy source to the PtG plant, including the excess PV energy, curtailed PV excess energy and PV excess energy plus the energy from the grid. Summing up the results, it can be concluded that the PtG plant is still far from economically viable even though significant improvement can be accomplished to the hydrogen production costs by adopting the active PV curtailment and by purchasing additional energy from the grid. The future study to be undertaken by the authors, with respect to economical viability of the PtG, will include other sources of value, including production of methane as main product, production of oxygen and heat as by-products, and provision of services such as biogas upgrading, frequency regulation and voltage.

This work describes an implementation of an office and/or personal smart grid for environmentally friendly buildings. These can be equipped with a local energy source (e.g., photovoltaic panels or combined heat-power units), energy storage devices (batteries, electric hot water boilers, heating, and ventilation systems including air conditioning), a building energy management system with sensors (e.g., providing the room temperatures), and household appliances acting as actuators (in general, split into groups of schedulable and non-schedulable ones). The idea behind this work has been to develop an automatic control system which would optimally decide for the end customer when to buy, sell, or store electric energy with the objective to minimize his total costs. At the same time, it fulfills all constraints in terms of the limits on power allowed to be taken from the grid. For the user, besides the optimal scheduling of household appliances and selling energy to the grid whenever it becomes profitable, the developed prototype gives also the opportunity to monitor the local generation, storage, and consumption in real time. On the other side, the electric utility can produce a real-time pricing signal which reflects daily peaks in consumption. Making such a price signal available for this building energy management system will lead to a decrease of power consumption from the grid. In this project, a model predictive control approach to the energy optimization problem in a building has been proposed. Different scenarios have been run and the results are discussed here.

A session chaired by SAGUF at the International Foresight Academic Seminar 2013 identified strengths and gaps in the energy research landscape in Switzerland. The discussion highlighted the need for inter- and transdisciplinary research and integration of the social sciences.

This paper presents an algorithm for determining an optimum size of Energy Storage System (ESS) via the principles of exhaustive search for the purpose of local-level load shifting including peak shaving (PS) and load leveling (LL) operations in the electric power system. An exhaustive search method is employed to perform the ESS capacity (Q ESS ) and power (P ESS ) optimization. The sizing process involves two distinct steps. In the first step the search for a feasible ESS parameter space in which the requirements of PS and LL are fulfilled and in the second step the search for an optimum point in the feasible space with respect to the cost benefit. Finally, the search is expanded to find a set of storage capacity, Q ESS and peak power limits, P limit 's for each month, in order to perform the load shifting throughout a one year. To validate the ESS size optimization, an appropriate model is created for time-domain simulations. The model consists of variable load, a simple state-space ESS model and a rule-based controller which operates the ESS using a set of rules. A number of time-domain simulations were performed to validate the correctness of the ESS size optimization. It appears that the proposed optimization algorithm produces results that meet the requirements in the peak shaving and load leveling operations.

This paper describes the development and implementation of a method and a prototype solving the problem of optimal integration of the largest battery energy storage system installed so far in Switzerland into an existing power grid in presence of intermittent renewable energy sources. The developed approach is based on model-based predictive control, a well-known method in process automation. Mathematical models of all involved system components, such as local load or weather dependent power generation profiles, were developed. In addition, plant-model uncertainties are handled by an additional fast corrective feedback control loop. The result, an advanced battery controller, has been implemented in cooperation with ABB Ltd. in a real-time prototype and integrated into the existing energy management system used for the manual operation and control of the real 1MW Li-Ion battery installed by the electric power utility of the canton of Zurich (EKZ) in Switzerland. The newly developed functions include automatic peak-shaving and cost optimal battery control subject to time-varying energy prices and predefined physical and operating limits.

The effectiveness of using both local and remote (wide-area) feedback signals for power oscillation damping (POD) controllers is first demonstrated. The challenge is then to guarantee a minimum level of dynamic performance with only the local signals following a sudden loss of remote signals. A case study on the Nordic equivalent system is presented to show that the closed-loop response could deteriorate if the remote signals are lost. A fault-tolerant control (FTC) design methodology is presented to solve this problem and ensure an acceptable performance level even in case of loss of remote signals. The FTC design methodology is based on simultaneous regional pole-placement for normal and loss of (remote) signals conditions. First the problem is solved non-iteratively using a Linear Matrix Inequality (LMI) approximation and then it is shown that, although this procedure is linear and easy to implement, it has a drawback: the value of one of the control matrices is fixed before calculating the others. An iterative procedure is presented instead to ameliorate this problem and potentially improve the damping of the system. Case studies on the Nordic equivalent system confirm that the proposed iterative fault tolerant controller (FTCit) is able to improve performance against the non-iterative fault tolerant controller (FTC) and produce acceptable performance in case of loss of the remote signals while the response with a CC is unacceptable if a fault occurs.

The effectiveness of using both local and remote (wide-area) feedback signals for power oscillation damping (POD) controllers is first demonstrated. The challenge is then to guarantee a minimum level of dynamic performance with only the local signals following a sudden loss of remote signals. A case study on the Nordic equivalent system is presented to show that the closed-loop response could deteriorate if the remote signals are lost. A fault-tolerant control (FTC) design methodology is presented to solve this problem and ensure an acceptable performance level even in case of loss of remote signals. The FTC design methodology is based on simultaneous regional pole-placement for normal and loss of (remote) signals conditions. First the problem is solved non-iteratively using a Linear Matrix Inequality (LMI) approximation and then it is shown that, although this procedure is linear and easy to implement, it has a drawback: the value of one of the control matrices is fixed before calculating the others. An iterative procedure is presented instead to ameliorate this problem and potentially improve the damping of the system. Case studies on the Nordic equivalent system confirm that the proposed iterative fault tolerant controller (FTCit) is able to improve performance against the non-iterative fault tolerant controller (FTC) and produce acceptable performance in case of loss of the remote signals while the response with a CC is unacceptable if a fault occurs.

In this work, real-time evaluation and steps towards implementation of three different types of power oscillation damping controllers (POD) for fast power electronic devices such as FACTS (flexible AC transmission systems) have been done. The performance of classical POD controllers (lead-lags and phasor estimators) are compared with an advanced adaptive approach. The prerequisite for achieving optimal results in damping of electromechanical oscillations is the availability of remote signals through wide-area monitoring and control (WAMC) platforms discussed here. Achieved results are demonstrated on a dedicated real-time hardware platform.

In this paper is presented a semi-active fault-tolerant control (SAFTC) as an alternative to reconfigurable or self-repairing fault-tolerant architectures with application to power systems. The final goal is to achieve stability and a minimum level of system performance following the completely loss of the feedback signals in the controller, which in this case are remote wide-area signals. The proposed controller is designed under the framework of Linear Matrix Inequalities (LMIs) to achieve pole placement. The semi-active design is compared against and ordinary or non-fault-tolerant control design to highlight that following the loss of a wide-area signal in the control, the closed loop response can lead to instability in the non-fault-tolerant case. The results are validated through nonlinear simulations results using a reduced version of the Nordic power system where the effectiveness of the proposed approach is demonstrated.