The uncontrolled inclusion of renewable energy sources in the distribution network causes severe overvoltages. Simultaneously, electrification strategies, such as heat pumps and electric vehicles, increase the peak demand, causing undervoltages. The combination of both phenomena has proven challenging for distributed system operators who are accountable for power quality and accessibility. System operators address those voltage issues with network reinforcements, but such projects are costly and time-consuming. We identified that the cost and qualified workforce availability are the main challenges of premature grid reinforcement. This paper evaluated peak-shaving and power curtailment at the low voltage distribution level as market-based alternatives to provide flexibility using the business model canvas. We identified the main actors that would benefit from peak-shaving and power curtailment at the residential level, their relationships, and the value proposition's challenges. We proposed a business model where residential prosumers receive compensation for supporting the network to prevent the distribution system from surpassing the projected power flows. Both alternatives offer system operators more control over the power flow to ensure power quality while decreasing costs, as fewer or no premature grid reinforcements might be needed. The business opportunity resources are categorized as technical and regulatory, highlighting the latter as the main challenge for the business model. We discussed two residential prosumer case scenarios for the Dutch context, one with a PV system and one with a PV and a heat pump. Our analysis suggests that the business models are technically possible for peak-shaving and power curtailment with existing technologies for the selected target. However, the former requires more complex activities and is limited to a narrower segment, as it requires prosumers with PV, storage and high-load devices, such as heat pumps.@en

This thesis titled "Addressing voltage sag contribution of an optimally sized Industrial Hybrid Power System" introduces a framework for sizing an industrial Hybrid Power System (HPS) to minimise Cost and CO2 emissions relative to connecting the industrial site directly to the grid with the help of a genetic algorithm, specifically NSGA-II. The framework utilises an Energy Management System (EMS) that is based on a rolling average principle which attempts to restrict the change in grid consumption from one time step to the next. The optimally sized configuration and its new grid consumption profile are analysed in the CIGRE MV Distribution Network to assess the effects of the new consumption profile on the bus voltages. The combination of a rolling average-based EMS and an optimal sizing with NSGA-II resulted in a $47\%$ reduction of the CO2 emissions while not worsening the voltage behaviour in the system (with a focus on voltage sag introduced by large loads).

Energy storage is vital for a future where energy generation transitions from a fossil fuels-based one to an energy system that relies heavily on clean energy sources such as photovoltaic (PV) solar energy. To foster this transition, engineers and practitioners must have open-access models of PV systems coupled with battery storage systems (BESS). These models are fundamental to quantifying their economic and technical merits during the design phase. This paper contributes in this direction by carefully describing a model that accurately represents the power directions and energy dealings between the PV modules, the battery pack, and the loads. Moreover, the general model can be implemented using two different PV generation methods, the Gaussian model and the meteorological data-based model (MDB). We found that the MDB model is more appropriate for short-term analysis compared to the Gaussian model, while for long-term studies, the Gaussian model is closer to measured data. Moreover, the proposed model can reproduce two different energy management strategies: peak-shaving and maximizing self-consumption, allowing them to be used during PV–BESS sizing stages. Furthermore, the results obtained by the simulation are closed when compared to a real grid-tied PV–BESS, demonstrating the model’s validity.@en

In the context of building electrification the operation of distributed energy resources integrating multiple energy carriers poses a significant challenge. Such an operation calls for an energy management system that decides the set-points of the primary control layer in the best way possible. This is done by fulfilling user requirements, minimizing costs, and balancing local generation with energy storage. This last component is what enables building flexibility. This paper presents a novel aging-aware strategy for operating grid-connected buildings that combine multiple energy carriers (heat and electricity), storage devices (electric vehicles, batteries, and thermal storage), and power sources (solar photovoltaics, solar collectors). The novel energy management algorithm presented considers the aging of the batteries to enhance the operational differences between storage technologies, thus making explicit the trade-off between the services provided by the hybrid energy storage system and its degradation. This unlocks grid cost reductions between 20–45 % depending on the season when compared to state-of-the-art solutions.@en

As demand for clean and renewable energy around the world increases, solar photovoltaic (PV) technology becomes substantially popular, especially in low-voltage (LV) distribution networks. However, the integration of PV in LV distribution networks requires careful planning as it introduces voltage violations. To maintain network voltage, distributed control of residential-scale battery energy storage systems (BESS) is a possible option. Previous studies considered only one-day simulations with limited testing conditions. However, it is important to evaluate voltage control capability over an extended period of time. Moreover, it is important to estimate battery lifetime for the economic feasibility evaluation of distributed control.

This work aims to present a distributed control method for BESSs at a residential scale to provide voltage support in a highly PV-penetrated LV network while providing insights into their lifetime estimation. A control method based on a consensus algorithm with the addition of SOC balancing control is proposed and tested on a modified CIGRE LV distribution network using MATLAB/Simulink. Evaluations on the voltage support capability and control behavior are performed in various testing conditions and are extended beyond one day of simulation. Moreover, a battery lifetime estimation is performed using the resulting cycling profile from the proposed control.

The proposed control strategy can provide voltage support in most case variations with the exception of cold seasons and extreme addition of PV power generation. Concerning battery lifetime, there is only a small observable capacity fade from the proposed strategy’s cycling profile. It is important to investigate calendar aging because of the small cycling current from the operating conditions presented in this work.

Along with the widespread adoption of solar energy, it is fundamental to develop methods and tools that help practitioners during the design phase of photovoltaic (PV) systems. Currently, multiple commercial software can quantify a particular location's annual energy yield while including the horizon's shading effect (e.g., mountains, buildings, and trees). To do so, precise information about the PV system's surroundings is necessary. This information is gathered by specialized equipment or by having access to satellite imagery. Therefore, to offer a more practical approach, we propose a method that requires only a cellphone camera, a fixed point for taking a panoramic photograph, and a compass. Once the panoramic image is taken, the obstacles’ width, height, and altitude are calculated, and the skyline is built. With this information, the method correlates the position of the sun with meteorological data to include the effect of shading on direct irradiation. The method was tested using one–year meteorological data to determine the best orientation of a PV system. The image processing method and the general method were validated by getting PV power generation data and aerial images and comparing them to the method's predictions. Therefore, we introduce a method that, with low computational complexity, facilitates the study of shading on the performance of PV systems.

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The Netherlands is currently undergoing an energy transition in an effort to decarbonize its electrical grid and build a more sustainable generation model. This transition is being led by the integration of non-controllable, sustainable generation sources such as wind and photovoltaic (PV) power. The Dutch wholesale energy market has an imbalance settlement period in which the TSO penalizes or rewards deviations from the last submitted trading program (based on whether the deviations aggravate or relieve the overall market imbalance), and therefore, non-controllable sources are at a higher risks of suffering undesired deviations. The consequences of this are twofold: on one hand, they impose a strain on the grid and an increased demand of ancillary services; and on the other, they risk the economic profitability of the plant.
This issue can be bridged by combining non-controllable generation sources with storage assets.

Although the the dispatch of non-controllable energy sources has been studied extensively, there is a research gap in the proposal of revenue-maximizing strategies for operating hybrid power plants (with wind and PV generation, and energy storage capabilities) in the Dutch wholesale energy market, that account for the stochastic nature of the weather resources and include financial contingency factors.
This thesis aims to bridge that gap by setting up an optimization-based dispatch, using Mixed Integer Linear Programming. The optimization was extended to a scenario-based stochastic optimization, and the Conditional Value at Risk was introduced to account for the intrinsic financial risk of the dispatch under random weather conditions. The resulting problem is a two-stage optimization which was solved using a modified Bender's cut. The intra-day optimizations were also adapted as rolling-horizon dispatches, permitting the operation with periodic updates to the weather forecasts.


The study case for this research was the SWITCH lab, a small-scale laboratory developed by TNO to conduct empirical research on the integration of renewable energies and storage into the grid. TNO also provided the basis for a non-optimized dispatch strategy based on price benchmarking, which was used to compare the performance of the optimized strategy.

The optimized dispatch proved to be an effective strategy for producing maximal-revenue trading programs on all market closings. The optimized revenue provided revenues between 85.8% and 260.1% higher than a generation-alone plant configuration; and an increase in revenue with respect to a generation-only baseline between 300.0% and 8962.9% compared to the non-optimized strategy. Operation under a hybrid configuration using the optmized dispatch also yielded the best economic outlook, having the highest 10-year Net Present Value projections, an average Internal Return on Investment 57.2% higher than the hybrid plant under a non-optimized scheme and a 47.5% lower payback time.

The optimized strategy provided the most profitable trading programs for both the case of deficit and surplus of generation at delivery, turning a positive revenue even under unfavourable market conditions. Conversely, the non-optimized dispatch had the lowest economic outlook of any configuration, with worse NPV, IRR, and payback times than the generation-only plant.

These results highlight the importance of developing dispatch strategies that consider the long-term behaviour of generation and prices, as opposed to here-and-now strategies whose performance was shown to be comparatively deficient; and the synergy between storage and renewable generation sources to bridge the non-controllability problem.

To enable affordable and environmentally friendly eletrical energy storage, a battery was designed using sea-water as electrolyte. The performance of this battery was tested through repeated cycling under a variety of circumstances. The Coulombic and energetic efficiency were around 80% and 68% respectively. The battery saw a strong drop in performance after ~60 cycles. This was corroborated with results gained from four separate cells. Efforts to model the battery were limited by the accuracy of the utilized model itself.

The majority of Dutch homes currently use natural gas boilers to meet their space heating demand. Changes in this significantly large sector are required to achieve the sustainability goals established by the Paris Agreement. Since most renewable energy sources produce electricity, transitioning residential heating systems might cause problems managing national electricity grids. Furthermore, the intermittent nature of renewable energy sources leads to an imbalance between supply and demand.

These challenges can be overcome by combining different storage techniques. An example of such a technique is the thermal energy buffer developed by Borg, which focuses on single-household use. This thesis looks into the feasibility of such a system by comparing different scenarios for residential heating systems.

Three scenarios were modelled using Simscape. In scenario I, a natural gas boiler provided all the heating demand of the house. In scenario II, the heating system consisted of Photovoltaic Thermal (PVT) panels and the thermal energy buffer. In scenario III, the house was heated by PVT panels, the thermal energy buffer, and a heat pump. In all scenarios, the same house was connected to the heating system.

In scenario II, the system sizes were 0, 1, 2, and 3 PVT panels, combined with buffer capacities of 0, 2, 4, and 6 m3. In scenario III, the system sizes were: 3 PVT panels with 6 m3 buffer capacity, 1 PVT panel with 4 m3 buffer capacity, and 3 PVT panels with 2 m3 buffer capacity.

The total yearly heat consumption of the modelled house was 5109 kWh. In scenario I, 378 kg of CO2 was emitted. In scenario II, CO\textsubscript{2} emissions were highly dependent on the sizing of the PVT system and the TESS and ranged from 20 to 405 kg, based on a heating demand of 9444 kWh.

Scenarios I and III maintained a comfortable temperature during the entire year. The heating system of scenario II was insufficient to heat the house throughout the year for all modelled system sizes; however, the scenario could be acceptable with larger PVT and TESS sizing. By comparing CO2 emissions and payback time, the optimal capacity of the thermal energy buffer was found to be 6 m3.

The uncertainty of the future gas price causes a challenge in comparing the cost of electrified heating systems to traditional heating systems. Additionally, it underlines the necessity of decarbonizing residential heating systems to secure comfortable, affordable housing.

Renewable energy power plants and transport and heating electrification projects are being deployed to enable the replacement of fossil fuels as the primary energy source. This transition encourages distributed generation but makes the grid more weather-dependent, thus reducing its inertia. Simultaneously, electrical network operators face voltage, frequency, and stability challenges at the distribution level. Networks were not designed to manage the stochasticity of renewable energy sources or the congestion caused by the new transport and heating demands. Such challenges are commonly addressed through infrastructure reinforcements. This review studies how energy storage systems with different carriers can provide a collaborative solution involving prosumers as ancillary services providers at the distribution level. We focused on the European urban context; thus, we analyzed renewable energy sources, batteries, supercapacitors, hydrogen fuel cells, thermal energy storage, and electric vehicles. A thorough review of successful implementations proved that including storage in one or more carriers benefits the distribution system operators and the prosumers, from both technical and economic perspectives. We propose a correlation between individual energy storage technologies and the ancillary services they can provide based on their responses to specific grid requirements. Therefore, distribution system operators can address network issues together with the prosumers. Nevertheless, attractive regulatory frameworks and business models are required to motivate prosumers to use their assets to support the grid. Further work is recommended to describe the joint operation of multiple storage technologies as multicarrier systems, focusing on the coupling of electrical and thermal energy storage. Additionally, how ancillary services affect the energy storage system’s aging should be studied.@en