The energy transition encourages using heat pumps at the residential level, which results in a multi-carrier energy system when combined with PV and battery storage. Optimally controlling such systems has proven challenging. The numerous constraints required, different response times per energy carrier, and the need for forecasting methods also increase the complexity and computational cost. We propose an adaptable energy management system strategy for any system architecture with a reduced number of constraints using genetic algorithms with a discrete-continuous approach for the power setpoints. Using random forest regression, we also created short-term estimation models for the PV generation and electric and thermal demand, with error distributions centred near 0 %. Our results demonstrate that the strategy can solve the power allocation problem in the order of 1 s, including forecasting 60 minutes, minimizing electric costs, and ensuring thermal comfort.@en

The urge to reduce the dependence on natural gas for heating at the residential level has led to the deployment of different fossil fuel-free alternatives. In the Netherlands, two technologies are leading the transition: heat pumps, due to their high COP, and photovoltaic–thermal systems, due to their dual electric-thermal output. However, both represent a challenge for users and grid operators, aside from their stochastic behavior. Heat pumps alone can surpass a typical Dutch house's total energy and power consumption. Photovoltaic–thermal systems, as their only electric homologs, usually have a mismatch between generation and demand, causing energy injections to the grid. From the electric perspective, storage systems are a proven solution to reduce the energy exchange with the distribution network. This paper proposes four multi-carrier energy system configurations for a Dutch household, comprising different combinations of a photovoltaic–thermal system, a battery energy storage, a heat pump, and an underground water tank thermal energy system, providing analytical models for every component (including the thermal losses from the thermal storage to the ground), and the space heating and electrical demands. We determined the components’ compatibility and evaluated the combinations considering their thermal performance, electrical performance, and equivalent CO₂ emissions. The results suggest that using a heat pump combined with a photovoltaic system and a battery provides the best trade-off. The photovoltaic–thermal system alone could not supply the thermal demand required for comfortable space heating nor reach temperatures high enough to charge the thermal storage. Combining the thermal storage with the heat pump allows a certain degree of flexibility for the heat pump activation at the cost of COPs between 0.8 and 1.38 when used to charge the thermal storage, thus increasing energy consumption and equivalent emissions considerably.

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Industry plays a significant role in the energy transition due to its share of energy consumption. More complex energy systems are proposed to accelerate the energy transition, including coupling renewable energy sources and energy storage to supply part of the industrial loads locally. In this work, we used a multi-objective genetic algorithm to optimally size an industrial hybrid power system comprising a PV system, a battery energy storage system, and a diesel generator to minimise energy costs and overall equivalent CO2 emissions. The results suggest that the system does not require high power and capacity components to minimise the energy cost and equivalent CO2 emissions, highlighting the importance of the EMS strategy. In our case scenario, the optimal HPS reduced the emission cost by 46.7 % and the energy cost by 8.7 %. For the EMS, we proposed a rolling horizon average approach, which defines a setpoint for the power exchanged with the grid to minimise its change rate in time. The EMS dispatched the power to minimise the sudden changes in the demand from the network, with a power allocation priority order of PV, BESS, and generator. We also evaluated the effect of adding the optimally sized hybrid power system into a CIGRE medium-voltage distribution network, using a real industrial load profile for each node. The hybrid power system improved the voltage sag on the hybrid power energy system node and its neighbouring nodes.@en

The massive deployment of PV systems in residential buildings is causing voltage challenges in low-voltage distribution networks. Worldwide, DSOs started requesting users to curtail power when this is injected back into the grid. Although many commercially available inverters can perform curtailment, the degradation effects of curtailment still have to be investigated. This paper estimated how power curtailment affects the reliability of a boost converter working below MPPT voltages. Using the mission profile method, we determined the conduction and switching losses on the converter switch as the critical component, based on its temperature and current profiles. The results suggest that curtailing the power requires the operation point to move towards lower PV voltages, leading to deeper thermal cycles, therefore reducing the expected lifetime of the converter by up to 80 % for power injection into the grid below 1.5 kW. From the operational perspective, this might require premature replacements compared to operating under MPP conditions, affecting the revenue forecast before the enforcement of curtailment. For power injection above 1.5 kW, the LCoE does not change compared to the case without considering the degradation. However, near zero-injection conditions, the difference in LCoE between considering and not considering replacements increases exponentially up to 135 %.@en

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

In low-voltage distribution networks, the high penetration of renewable energy generators in residential buildings has proven challenging for system operators. In response, the grid operators can reinforce the grid infrastructure or deploy battery energy storage systems throughout the network to compensate for the voltage fluctuations. Alternatively, new energy markets for ancillary services have been proposed to involve the prosumers; however, most are at medium and high voltage levels. This paper investigates, from a cost perspective, what conditions can make it attractive for individual prosumers to participate in a low-voltage ancillary service market, specifically power curtailment and peak shaving. We considered a prosumer with a 2 kWp PV system for both ancillary services, adding a 10 kWh battery for the peak shaving case. Curtailing power to comply with the maximum power exchange with the grid does not create any significant change in the LCoE of the PV system, keeping it near 0.072 €/kWh for permitted return grid powers above 1.25 kW. Scenarios closer to zero-injection increase exponentially the LCoE to 0.222 €/kWh. Using a semi-empirical ageing model, we estimated the degradation of the batteries for the cases with and without providing peak shaving, concluding that doing peak-shaving to avoid demanding more than 1 kW from the grid extends the battery life by up to 320 % while increasing its LCoS only 9.5 % when compared to a zero-consumption scenario due to the reduced depth-of-discharge and number of cycles. The results suggest that power curtailment and peak shaving can be attractive for prosumers, thus creating opportunities for ancillary services business models at the residential scale.@en

Batteries are one of the main tools to provide the flexibility distribution and transmission systems need due to their increasing dependence on weather conditions. However, environmental and economic factors pose a significant problem. New types of batteries that do not rely on rare earth metals and organic solvents but instead use water and more common ions could be a cost-effective and environmentally safe way to provide energy storage in the future. We studied the performance of sea-salt cells designed as a low-cost, environmentally friendly method to store electricity. We used a constant current charge/discharge test with different currents, from 50 mA to 300 mA, to identify the maximum efficiencies of the cell. Then, we introduced a new strategy to determine the cut-off voltage to discharge the battery, inspired by the maximum power point found in photovoltaics. We used a constant voltage charge to determine the cell’s energy density. However, evidence of side reactions urged us to use constant current charge/discharge tests to identify the battery’s capacity based on the efficiencies drop. Results showed a maximum energy efficiency of 74.6% at 200 mA and a maximum Coulombic efficiency of 88.7% at 300 mA. The cut-off voltage of the cell during discharge should be between 1.4 V and 1.6 V. The energy densities range from 10.1 Wh/kg(6.53 WhL) with an efficiency of 57.5% and 4.18 Wh/kg(2.7 WhL) with an efficiency of 69.8%.@en

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

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 energy transition requires electrical alternatives for domestic heating. Heat pumps are the most common alternatives to gas boilers. However, heat pumps consume a significant amount of electrical power. We simulated an 18-node low voltage network with five buildings with six apartments each to evaluate the effect of deploying heat pumps as part of multi-carrier energy systems at the residential level. We also combined heat pumps with solar collectors and thermal energy storage to quantity whether a more complex system benefits the low-voltage network. Replacing the gas boilers for heat pumps in the majority of the buildings resulted in voltage drops below the limit of the standard EN50160. The voltage drops were significantly improved when we included solar collectors and thermal energy storage in the domestic heating system.@en

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

Fifth-generation energy networks are combined networks of heat and electricity, that have the ability to generate, distribute, store and share energy between consumers. Knowledge on the dynamic behaviour of the physical phenomena related to energy generation, distribution and storage provides insight into the performance of the system as a whole. A mixed-integer linear algorithm is proposed, implementing a partitioned clustering program for subsequent classification of typical demand, grouping specific days with similar demand profiles together. From this arrangement, the optimal network configuration can be determined using an objective function, minimizing the economic and environmental impact. To validate the optimization results, a simulation of the network was built, which mimics its physical dynamic behaviour, and through which the distribution and storage capabilities of the network can be assessed. Advanced advice on fifth-generation energy networks is presented that can be applied to early-stage network design, reducing costs and emissions, along with data on the implementation of renewable energy technologies and their performance. Additionally, this research provides the foundation for numerical modelling of such energy networks which contributes to future research.@en