Energy Flexibility Research Articles

Energy profiles and electricity flexibility potential in apartment buildings with electric vehicles – A Norwegian case study

Energy flexibility in buildings has the potential to reduce the grid burden of neighbourhoods, yet its practical implementation remains limited. This paper presents a data-based case study from Norway, examining the electricity flexibility potential of electric vehicles, within the context of apartment building loads and PV generation. The results highlight the significant electricity flexibility potential in apartment buildings with EVs, where EV charging can be shifted in time by means of a shared energy management system. Energy profiles are presented, showing how EV charging can increase the average electricity use in apartments by a factor of 1.5 and the power use by a factor of 3.5 to 8.6. Furthermore, the study demonstrates how electricity flexibility KPIs of optimised EV charging in apartment buildings are affected by different energy tariffs, PV generation, V2G technology, and the location of the billing meters. The simulated scenarios showed a maximum reduction of peak loads of 45 %, while a maximum of 38 % of the EV charging was covered by PV generation. The study confirms that residential EV charging emerges as a viable frontrunner in the practical realization of end-user flexibility, paving the way for effective solutions in real-life applications.

Energieflexibilität in der Matrixproduktion/Energy flexibility in matrix production - Method for assessing the potential for energy flexibility and determing energy flexibility measures

Matrixproduktionssysteme sind modular aufgebaut und flexibel steuerbar. Für die Steuerung des Energiebedarfs auf der Nachfrageseite kann mit diesen Eigenschaften das große Potenzial der Energieflexibilität genutzt werden. Hierfür wird eine Methode zur Erfassung des Energieflexibilitätspotenzials und der Ableitung von Energieflexibilitätsmaßnahmen in cyber-physischen Matrixproduktionssystemen entwickelt. Organisatorische Energieflexibilität steht im Mittelpunkt.

Energy flexibility using thermal mass for Swedish single-family houses

This paper characterised the potential of energy flexibility in relation to building envelop properties, heat emitters and ventilation for the Swedish context. Simulation results indicated that the potential was higher for newer houses with floor heating and lower for older houses with radiators in winter. Older houses with different levels of insulation showed a similar ability of conserving heat due to different extents of heat losses from ventilation. A house with balanced ventilation tended to be over-ventilated especially if the house was not airtight. The flexibility was decreased with increasing outdoor temperatures, and it was higher in winter and lower in spring/autumn.

Reinforcing built-in electric field to enable efficient carrier extraction for high-performance perovskite solar cells

This review presents an overview of the carrier separation and extraction mechanism influenced by the built-in electric field (BEF) in PSCs and various strategies used to enhance the BEF.

Novel Quantification Method of Aggregated Energy Flexibility Based on Power-Duration Curves

Novel Quantification Method of Aggregated Energy Flexibility Based on Power-Duration Curves

Aggregator Index for 24-Hour Energy Flexibility Evaluation in an ADN Including PHEVs

Aggregator Index for 24-Hour Energy Flexibility Evaluation in an ADN Including PHEVs

Expanding Building Archetypes to Estimate the Indoor Environment Thermal Storage Capacity in the Danish Building Stock when Performing Demand Response

Short-term demand response leveraging the energy flexibility of the building stock is a key solution to decarbonise and ensure the reliability and sustainability of smart energy grids dominated by intermittent renewable energy sources. Most of the building demand response capacity depends on different forms of energy storage in the built environment. In addition to electric batteries, hot water storage tanks, ground source heat exchanger or dispatchable on-site renewable energy sources, buildings possess a tremendous thermal storage capacity within the thermal inertia of their structure and indoor environment. The latter can easily be harnessed with heating/cooling indoor temperature setpoint modulation strategies. However, there is a clear lack of large-scale estimates of this indoor environment thermal storage capacity in the different building stocks. To tackle this issue, detailed dynamic numerical models of the different building typologies in European countries are generated to assess the potential of demand response strategies at nationwide levels. The current paper presents the preliminary results on the thermal storage capacity in the Danish building stock when performing heating temperature setpoint modulation. These results are based on estimates of the effective thermal inertia of the different building archetypes in Denmark. They show that the Danish building stock contains immense thermal storage capacity, which is comparable to all combined batteries in a large fleet of electric vehicles or all industrial-size storage tanks in district heating plants.

Development of Realtime Co-Simulation Platform Harnessing Consumer Energy Flexibility Through an Aggregator to Provide Grid Support

Development of Realtime Co-Simulation Platform Harnessing Consumer Energy Flexibility Through an Aggregator to Provide Grid Support

Simulation-based Investigation of Energy Flexibility in the Optimization of Hinterland Drainage

Simulation-based Investigation of Energy Flexibility in the Optimization of Hinterland Drainage

Estimating the Long-Term Thermal Comfort Elasticities of Diverse Households

District energy systems simulation models are developed to investigate whether the demand-supply energy balance can be maintained despite the energy transition. To adapt these models to the future energy system, models of residential energy flexibility are required. We hypothesize that a quantification of households’ comfort elasticities is needed to model residential energy flexibility more accurately. Therefore, this study aims to identify diverse households’ long-term thermal comfort elasticities. Eight longitudinal mixed methods case studies with an explanatory sequential design were conducted in seven Belgian dwellings. Data were collected before and during the recent energy crisis. They include sensor measurements, a questionnaire, and follow-up interviews. All households show elasticities. Some differ the average set point temperature, the average heated volume to a limited extent, or the temperature of no more heating. Differences between households could be explained by differing household and dwelling characteristics.

Energy, economic and environmental benefits of Demand Response for improving building energy flexibility

The increasing penetration of intermittent renewable sources in power generation at local and building-level poses growing issues in balancing generation and demand. To avoid imbalances, it is therefore necessary to ensure adequate levels of flexibility in the building energy system. This can be done both on the generation side, through the coupling of different energy carriers (cogeneration, power-to-heat solutions) and/or the integration of storage systems, and on the demand side, through smart “demand response” programs. This paper considers a tourist facility located in central Germany as a case study to evaluate the energy, economic and environmental benefits that can be obtained from the application of appropriate demand response strategies. The electrical demand data of the facility are monitored at both aggregate and individual load levels and made available by means of a cloud platform. The facility includes two stationary combined heat and power internal combustion engines powered by natural gas and a photovoltaic system. The results show how, thanks to appropriate load management, it is possible, on the one hand, to increase the self-consumption of PV-generated energy and, on the other hand, to keep more constant the load of the engines, which can therefore operate with better efficiencies. This results in both a reduction in energy expenses and a decrease in carbon dioxide emissions attributable to the building.

A component-based design approach for energy flexibility in cyber-physical manufacturing systems

AbstractEnergy flexibility of manufacturing systems helps to meet sustainable manufacturing requirements and is getting significant importance with rising energy prices and noticeable climate changes. Considering the need to proactively enable energy flexibility in modern manufacturing systems, this work presents a component-based design approach that aims to embed energy flexibility in the design of cyber-physical production systems. To this end, energy management using Industry 4.0 technologies (e.g., Internet of Things and Cyber-physical Systems) is compared to the literature on energy flexibility in order to evaluate to what extent the energy flexibility practice takes advantage of Industry 4.0 technologies. Another dimension is the coverage of the life cycle of the manufacturing system which guarantees its sustainable design and the ability to achieve energy flexibility by configuring the energy consumption behaviour. A data-based design approach of the energy-flexible components is proposed in the spirit of the Reference Architectural Model Industrie 4.0 (RAMI 4.0), and then it is exemplified using an electric drive (as a component) in order to show the practical applicability of the approach. The energy consumption behaviour of the component is modelled using machine learning techniques. The digital twin of the studied component is developed using Visual Components virtual engineering environment, then its energy consumption behaviour is included in the model allowing the system integrator/decision-maker to configure the component based on the energy availability/price. Finally, external services in terms of an optimisation module and a deep learning module are connected to the digital twin.

Ni-MOF Based Flexible Solid-State Supercapacitors in Aqueous and Non-Aqueous Electrolytes

Supercapacitors are high power density devices which acts a bridge between the batteries and conventional capacitors. Several emerging materials like Metal Organic Frameworks (MOFs) have been developed as electrode material for energy storage. MOFs are highly porous materials containing metal centers and organic moieties called ligands [1].They are widely employed for energy storage applications owing to their structural and morphological tunability [2]. In our recent research work, Ni MOF is synthesized using microwave assisted solvothermal technique at different temperature and metal to ligand ratios. Ni MOF is synthesized by varying metal to ligand ratio (M:L) as 1:1, 2:1, 3:1 and 4:1. The solution is heated by microwave irradiation technique [3] from room temperature to 150, 165, 180 and 200 °C to obtain light green colored samples. It is interesting to observe that different synthesis parameters lead to different morphologies thereby resulting in improved performance of Ni MOF. The structural and electrochemical characterizations reveal “why does a particular morphology exhibits better charge storage capacity?” The three electrode configuration experiments were conducted in aqueous electrolyte to evaluate the charge storage capacity. The results show that globules (∼1360 F g-1) perform better than nanoflower (∼850 F g-1), flakes (∼650 F g-1) and plates (∼450 F g-1) [4] respectively in 2M KOH at 0.5 A g-1. The reason is attributed to the low solution resistance (R sol) for globules, reduced charge transfer resistance (R ct) and the global and local n values of CPE.The synthesized material (Ni MOF) will be used as positive electrode material for flexible asymmetric supercapacitor. Recently, flexible state supercapacitors (FSSCs) have gained popularity due to their formability, flexibility and high energy density. Here, the objective is to increase energy density and power density by extending the operating potential window of the device. Hence, the aqueous electrolyte is substituted with PVDF based ionogels (ionic liquid gel polymer) to impart flexibility, bendability and high power density to FSSC. It is observed that the potential window improved remarkably from ~0.6 V (aqueous electrolytes) to ~5 V (ionic liquid). The reason is attributed to the absence of water, results in thermodynamic stability of the electrolyte. Also, the ionic liquid based FSSCs are non-flammable, non-toxic, thermally stable. In order to improve the conductivity and charge storage capacity some additives are incorporated in the gel polymer matrix. Herein, certain polar solvents are added to enhance the conductivity due to their high dielectric constant giving rise to faster ionic dissociation. MOF based flexible supercapacitors are fabricated and tested for their energy and power densities in conjunction with electrochemical and structural characteristics .

Robust energy management through aggregation of flexible resources in multi-home micro energy hub

This study introduces a novel approach to home energy management systems (HEMS) through the development of a micro energy hub. The hub proficiently aggregates flexible resources across multiple homes, underpinned by a detailed modeling of appliance characteristics for enhanced energy management accuracy. The integration of Distributed Energy Systems (DES) further enriches the micro energy hub's capabilities, while a multi-objective two-stage robust optimization (M-TSRO) model is developed to address the inherent uncertainty of DES, aiming to concurrently realize energy savings, carbon emission reduction, and load smoothing. The effectiveness of the proposed micro energy hub is evaluated using real-world REFIT data set, demonstrating improved load scheduling, smoother load profiles, and enhanced energy flexibility. The results indicate significant improvements in grid control levels, reaching 68.75% in the basic scenario and 56.25% in the prosumer scenario. The prosumer scenario exhibits a significant reduction of 13.34% in the integrated objective compared to the basic scenario. This reduction is primarily driven by a notable decrease of 31.44% in the operational cost and an 8.06% decline in carbon emissions of the micro energy hub. These findings highlight the potential of micro energy hubs in optimizing energy consumption and increasing power flexibility through collaborative load scheduling strategies.

Control strategies for active distribution networks based on soft open point

The application of SOP instead of traditional tie line switches in distribution networks can im-prove the controllability, flexibility, and renewable energy accommodation of the distribution grids. Compared with traditional tie line switches, SOP have high costs and large land occupation. When power transfer is not considered, the location and capacity of SOP can be optimized through planning algorithms to reduce the overall costs. However, the main function of tie line switches is power transfer. If SOP as alternative devices do not meet this requirement, their ex-tensive application will be restricted. Therefore, this paper designs the direct current volt-age-power smooth switching control strategy, phase angle pre-synchronization control strategy, and voltage support control strategy based on the parallel structure of SOP and tie line switches to ensure stable operation during the power transfer process, through this complete control strategy, smooth switching can be achieved to keep the DC voltage stable during the switching process, effectively suppress the impulse current and maximize the utilization of SOP capacity Simulations on the SIMULINK plat-form verify the feasibility of the control strategies.

The positive and negative impact of novel utility demand response programme and stochastic utility-driven events on renewable penetration and flexibility activation of train and station systems

Integrating an incentive-driven demand response program (DRP) into a metro railway system can enhance the techno-economic benefits of grid operators and metro railway operators by modulating the grid interactions. To facilitate demand response (DR), all energy flexibility resources within the metro network, such as heating, cooling, electrical, and vehicle systems, should be individually regulated by optimal control strategies. Therefore, an automated energy management system was developed and implemented to prioritise and logically control various energy flexibility resources to maximise the annual performance based on the requirements of the DR signal from the utility grid. Automated DR management helps to achieve an annual DR incentive of 0.57 × 106 HKD, enabling a 2.9 times lower annual operational cost of 0.28 × 106 HKD compared to the reference, even after accounting for the annual electricity tariff of 0.84 × 106 HKD. The techno-economic impacts of becoming a DR participant were stochastically studied using Hong Kong’s DRP by examining all crucial factors in the DR business model. In addition, this study defines a methodology for determining the optimal demand reduction target without biasing any stakeholders. Then, the DR business model was comparatively evaluated between a prosumer-based energy system and the same system without renewable energy support. The former system loses the DR incentive in proportion to the load matching compared to the latter system. Moreover, the DRP was extended from static to dynamic DR support, and the results show that considering dynamic DR can further increase the economic benefit of all stakeholders.

Secondary system modeling and primary system coupled simulation using MARS-KS

The flexibility of nuclear energy can be achieved by the load following operation and the thermal energy utilization for hydrogen production, desalination, district heating, and Thermal Energy Storage (TES). Thermal energy utilization is performed by transferring the remaining thermal energy over the energy required for electric power generation without changing the reactor power level significantly. For the Pressurized Water Reactor (PWR), it becomes possible by extracting steam from the secondary system and circulating it to a thermal energy application such as the TES system. However, the steam extraction operation affects the behavior of all thermal–hydraulic (TH) variables in the secondary system and further influences the primary system in terms of coolant temperature, reactivity, and reactor power. For thermal energy utilization, it is necessary to secure a technology that can examine the overall stability of the primary and secondary systems in a Nuclear Power Plant (NPP). In this study, based on the system analysis code MARS-KS, an NPP analysis model for SMART, a small-sized integral type PWR, was developed that can simulate major TH variables behavior in the primary and secondary systems at once. Its strength is that major components in the secondary system are modeled without any boundary conditions under matching the heat and mass balance. From the verification calculation of the steady state, it was confirmed that this SMART analysis model can predict the main TH variables of the primary and secondary systems similarly to the plant data. Furthermore, an example calculation was performed for the TES application. The analysis results show that the analysis model is sufficiently applicable to the transient calculation of the primary and secondary systems during the steam extraction operation. This analysis model is expected to be used for the development of technologies such as load following operation and thermal energy utilization in the future.

Flexibility potential quantification and regulation measure comparison for the building air-conditioning system

Air-conditioning (AC) systems are the resources with the greatest flexibility potential for building demand response (DR). However, there is no unified method to quantify its flexibility under different DR measures, which results in difficulties in fully utilizing the DR potential and determining a proper regulation measure for the AC system operation strategies. To bridge this gap, the indicators of energy flexibility and power flexibility are firstly proposed in this study to compare three measures, active storage, passive storage, and temperature resetting, during the DR process of AC systems. According to the regulation measures with quantified flexibility potentials, different DR regulation measures are combined to explore the maximized stack flexibility. Based on a case study of an office building in Tianjin, the results show that among the different stacking strategies, stacking the active energy storage and temperature reset strategies produces the lowest operating cost, which is 13.8% and 22.5% lower than the stacking all three measures’ operating cost and total energy consumption, respectively. In the case of stacking the two measures, the highest energy flexibility is achieved when stacking the active and passive energy storage measure. If the temperature reset measure is further stacked, the energy flexibility can be increased by 15%.

Techno-Economic Evaluation of a Compressed CO2 Energy Storage System for Load Shifting Based on Dynamic Modelling

To reduce the electricity grid’s valley—peak difference, thereby resulting in a smoother electricity load, this study employs a compressed CO2 energy storage system to facilitate load shifting. Load shifting by the CCES system not only enhances the energy flexibility of the electricity load but also creates energy arbitrage from variations in the electricity prices. An optimization model is developed to optimize the operation of the CCES system to minimize the standard deviation of the electricity load. Thereby, load shifting by the CCES system can be achieved. Based on the real electricity loads and prices, results indicate that, with an energy storage capacity of 267 MWh, the CCES system can provide 3845 MWh, 4052 MWh, and 3816 MWh of upward flexible energy and 3846 MWh, 3180 MWh, and 3735 MWh of downward flexible energy during a week in summer, winter, and the transition season, respectively. With a lifespan of 35 years, the CCES system can attain a net present value (NPV) of MUSD 239.9 and a payback time of 2 years. The sensitivity analysis shows that increasing the energy storage capacity of the CCES system augments both the upward and downward flexible energy of the electricity load but reduces the NPV of the CCES system.

Thermal modeling for control applications of 60,000 homes in North America using smart thermostat data

As smart thermostats become increasingly available in residential buildings, there is an opportunity to use measured building data to calibrate models for community and district applications, instead of relying on high-fidelity simulations. This study used smart thermostat data from 60,000 houses in North America to create single-zone models. The model structure was defined with an automated forward selection procedure. 61% of the final models were classified as good fits and the structure of 80% of them was of 5th-order (5 thermal capacitances). An investigation of the 24-hour prediction error of the models showed that the ones classified as good fits are accurate enough for day-ahead predictions and Model Predictive Control (MPC) applications. An analysis of the model parameters suggested no strong correlation between them and the available metadata. The time constants of the houses were estimated, providing valuable information about the houses thermal inertia. Building models that can accurately capture and leverage building thermal inertia are ideal candidates for MPC and energy flexibility applications.