• Energy Research

The integration of increasing shares of intermittent renewable energy necessitates flexibility in both energy generation and consumption. Typically, the operation of flexible energy resources is orchestrated through optimization models. However, the manual creation of these models is a complex and error-prone task, often requiring the expertise of domain specialists. This work introduces a methodology for the automatic generation of optimization models for systems of flexible energy resources to simplify the modeling process and increase the use of energy flexibility. This methodology utilizes a modular, generic model structure designed to depict systems of flexible energy resources. It incorporates algorithms for model parameter derivation from operational data and an information model that represents the system’s structure and dependencies of resources. The efficacy of this methodology is demonstrated in two case studies, highlighting its relevance and ability to significantly streamline the optimization modeling process by minimizing the need for manual intervention.

Abstract The combination of solar thermal (ST) systems and heat pumps (HP) is a promising hybrid heating system concept for efficient energy supply of buildings. In this work, a simulation study on the performance of combined ST and HP systems and a comparison with systems without ST collectors for different types of buildings and climates is presented. With regard to the dominating market-available systems, the evaluation is limited on systems with parallel integration of ST collectors. For a better transparency of the results, the simulation models and the main model parameterization are explained in detail. The results of the simulations show that the performance of HP systems can significantly be increased by adding a ST system. The relative increase of the performance decreases with increasing space heating demand of the building and is lower for climates with low ambient temperatures. In contrast, in most cases the absolute electricity savings increase with increasing space heating demand and are higher for systems with air source HPs. The seasonal performance factor (SPF) of parallel solar thermal and ground source heat pump (SGSHP-P) systems is between 0.5–1.1 (Strasbourg) and 1.0–2.0 (Helsinki) higher than the SPF of parallel solar thermal and air source heat pump (SASHP-P) systems with the same ST collector area. Hence, the difference between the performance of SASHP-P and SGSHP-P systems increases with increasing heat load and decreasing ambient temperatures of the location. However, in case of moderate climates like Strasbourg, SASHP-P systems can achieve the same or even higher values of SPF than ground source heat pump (GSHP) systems without ST collectors. Especially for buildings with low energy demand for space heating, the SPF is higher (up to 78.5% with a collector area of 25 m2) and the systems can compete with each other. In a nutshell, in particular if the investment costs of a borehole heat exchanger and a ST system are similar or if there is no possibility to use a GSHP system with borehole heat exchanger, using a SASHP-P system may be a useful opportunity for a heating system concept with high energy performance and low electricity demand.

This paper discuss new consumers termed as “Prosumers” visualized as Cyber Physical Energy Systems (CPES). These CPES require being agile smart autonomous energy entities possessing capability to be interconnected at Local Power Distribution (LPD) level to share renewable energy. This build concept of Internet of Energy (IoE), forming bottom up decentralized model for energy network. In order to coordinate these CPES to share energy at LPD level, distributed smart cooperative control mechanism based on Service Oriented Architecture (SOA) and Multi Agent System (MAS) termed SoMAS is proposed in this paper. This mechanism include smart energy sharing scheme for cooperation and coordination to manage energy sharing among interconnected CPES. Simulation setup for proposed mechanism is also presented in paper.

The increasing integration of renewable energy sources necessitates efficient energy storage solutions, with large-scale battery energy storage systems (BESS) playing a key role in grid stabilization and time-shifting of energy. This study presents a multi-level simulation framework for optimizing BESS operation across multiple markets while incorporating degradation-aware dispatch strategies. The framework integrates a day-ahead (DA) dispatch level, an intraday (ID) dispatch level, and a high-resolution simulation level to accurately model the impact of operational strategies on state of charge and battery degradation. A case study of BESS operation in the German electricity market is conducted, where frequency containment reserve provision is combined with DA and ID trading. The simulated revenue is validated by a battery revenue index. The study also compares full equivalent cycle (FEC)-based and state-of-health-based degradation models and discusses their application to cost estimation in dispatch optimization. The results emphasize the advantage of using FEC-based degradation costs for dispatch decision-making. Future research will include price forecasting and expanded market participation strategies to further improve and stabilize the profitability of BESS in multi-market environments.

Abstract Energy conservation and efficiency in the residential building sector is an important field to control carbon emissions worldwide. Solar energy integration in domestic buildings decreases the grid dependency and carbon emissions. This paper investigates techno-economic feasibility, energy, exergy, and life cycle emissions analysis of solar energy integration to achieve an annual net-zero energy balance for a household. A local survey is carried out in the regions of Pakistan to define the representative building structure, services, and schedules. A representative household is then analyzed. TRNSYS is used for modelling and annual transient simulation of household thermal load and energy systems. TRNSYS-GenOpt co-simulations determine the optimal insulation thickness of the building envelope to minimize the thermal load. The on-site renewable energy supply system consists of solar PV, solar space heating, solar domestic hot water generation, and solar absorption cooling. The envelope insulation results in a 37.2% reduction in annual thermal load. Solar PV system supplies 93.4% of annual electricity demand. Solar collectors provide hot water during winter and thermal comfort during 92.4% of air conditioning hours. Energy and exergy analyses are used to evaluate the thermal performance of solar PV, thermal collectors, and absorption system. The life cycle cost analysis performed for a conventional and the proposed building shows that the net present value of the zero-energy solar household (ZESH) becomes lower than that of the conventional household in 8 years. Also, the life cycle emissions are calculated for conventional and ZESH. The CO2 emissions of ZESH are only 8.7% of that of a conventional household. This study reveals that a ZESH is technically as well as economically viable in humid subtropical climate regions.

Accurate solar radiation data are crucial for solar energy applications, yet ground-based measurements are limited in many regions. Satellite-derived and reanalysis products offer an alternative, but their accuracy varies across spatial and temporal scales. This study evaluated the performance of four widely used GHI products—CAMS, SARAH-3, ERA5 and MERRA-2—against ground measurements at hourly, daily (summed from hourly) and monthly (averaged from daily) timescales. The analysis also examined how temporal aggregation influenced error characteristics using correlation coefficients, the rMBD, the rRMSD and the combined performance index (CPI). At an hourly scale under clear-sky conditions, satellite products outperformed reanalysis products, with r≈1 and R2≈0.9 and the rMBD, rRMSD and CPI ranging from 0.1%, 11.4% and 11.8% to −14.7%, 33.3% and 75.1% for CAMS; 0.2%, 11.4% and 10.9% to 13.5%, 22.4% and 120.7% for SARAH-3; −0.2%, 21.6% and 23.8% to 21.5%, 40.9% and 128.8% for MERRA-2; and 0.8%, 14.6% and 16.3% to 22%, 48.2% and 88.3% for ERA5. Under cloudy conditions, all products overestimated GHI, with the rMBD reaching up to 39.7% (SARAH-3), 35.9% (CAMS), 22.9% (MERRA-2) and 28% (ERA5), while the rRMSD exceeded 40% for all. Overcast conditions yielded the poorest performance, with the rMBD ranging from 45.8% to 124.6% and the CPI exceeding 800% in some cases. From the hourly to daily and monthly datasets, aggregation reduced errors for reanalysis products by 5.5% and up to 12.4%, respectively, in clear-sky conditions, but for satellite-based products, deviations slightly increased up to 3.1% for the monthly dataset. Under all-sky conditions, all products showed reductions up to 23%. These results highlight the significant challenges in estimating GHI due to limited knowledge of aerosol and cloud dynamics in the region. They emphasize the need for improved parameterization in models and dedicated measurement campaigns to enhance satellite and reanalysis product accuracy in West Africa.

Abstract In this contribution, a step toward the immediate usage of Modelica models in the solution of optimal control problems is demonstrated. For this purpose, a model of a steam boiler in a power plant taken from literature was implemented in the high-level modeling language Modelica. The optimal control problem of the steam boiler start-up is formulated and solved using the JModelica framework with the Optimica extension. The results demonstrate the effort saved in solving an optimal control problem when using the JModelica framework in comparison to individual, case-specifically arranged solutions.

Zeolite 13X molecular sieve with high sorption capacity and significant sorption rate has been considered a promising candidate for seasonal heat storage. In this study, a code is developed to simulate the adsorption process between zeolite and water in all ranges of partial pressures, temperatures, and sorbate loadings. The results from the proposed code were compared with experiments and good agreement was observed. After validation, the developed model was used to study the effective parameters involved in the adsorption process of binder-free Zeolite 13X. A parametric study considering various temperatures and water content in the inflow air was conducted and the influence of different factors on the outlet temperature and adsorption enthalpy has been studied. This parametric study gives a good insight into the measures which can be taken for achieving the desired released energy or having the outlet temperature in the preferred range. The simulations have been conducted in a variety of temperature ranges provided during the desorption process, the humidity amount, and the mass flow rate of the incoming air. The relative influence of each parameter in the specified ranges is presented. The results have demonstrated the direct relationship of the partial pressure of water vapor and the desorption temperature with the adsorbed water amount and adsorption enthalpy while changing the mass flow rate mostly influences the discharging time.

The interconnection of distributed generation units has a significant impact on the performance of an energy system. In this paper, challenges in designing grid-connected and islanded distributed energy systems (DES) are described and a concept of simulation models in the component-oriented modeling language Modelica® is presented, wherein simulation models are divided into physically detailed and physically abstracted models.