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An integrated numerical model that describes the operation of a renewable-energy-based system for a building's heating, cooling, and domestic hot water needs is described in this study. The examined energy system includes a vapor compression multi-source heat pump, PVT collectors, borehole thermal energy storage, and water tanks. Energy balance equations for the collectors and the tanks are coupled with correlations for the heat pump and the piping losses within a thermal network approach. The non-linear system of equations that arises is solved by employing in-house software developed in Python v. 3.7.3. The performance of the numerical tool is validated against measurements collected during the pilot operation of such a system installed in Athens (Greece) for two 5-day periods (summer and winter). It is shown that the proposed model can predict, both qualitatively and quantitatively, the building's energy system performance, whereas limited deviations from the experimental findings are mostly observed when highly transient phenomena occur. The numerical tool is designed with flexibility in mind and can be easily adapted to accommodate additional energy-system configurations and operational modes. Thus, it can be utilized as a supporting decision tool for new energy systems' designs and the optimization of existing ones. [ABSTRACT FROM AUTHOR]

The variability and inhomogeneity of solar energy limits the development of solar heating systems (SHS) in many fields. In order to improve the utilization efficiency of SHS, this paper takes three typical cities (Xi'an, Dunhuang, Lhasa) as the research object, studies the operation state of SHS in student dormitory buildings, and puts forward a corresponding optimization strategy. The research shows that the reduction of water supply temperature will improve the operation efficiency and energy saving effect of a spontaneous combustion heat pump and that there is an optimal volume of heat storage water tank (HSWT), which can make the energy saving effect of SHS run better. The optimization of the SHS shows the water supply temperature is 35 °C, and the optimal volume of HSWT is 15 m3 in the "Resource-general area (Ⅲ)" represented by Xi'an, 25 m3 in the "Resource-rich area (Ⅱ)" represented by Dunhuang, and 40 m3 in the "Resource-richer area (Ⅰ)" represented by Lhasa. With the increase in the abundance of solar energy resources in the region, the optimal volume of HSWT also increases. Meanwhile, the solar energy contribution rate of the three regions in descending order is 61.3% (Lhasa), 32.8% (Dunhuang), and 25.9% (Xi'an). After optimization, the contribution of SHS increased by about 5%. The research results will help improve the efficiency of SHS in cold areas of China and make the system more efficient and energy efficient during operation. [ABSTRACT FROM AUTHOR]

Solar heating technology has the advantages of being high efficiency, energy-saving, and environment protecting; however, the instability of solar energy and its mismatch with the variation characteristics of building heat load have caused great difficulties in the design and the efficient operation strategy of a solar system. A heat storage tank is an important part of a solar hot water system. In order to improve system efficiency, this paper proposes a flat plate PCM storage tank, establishes a mathematical model, and conducts experimental verification under different working conditions. Experiments show that in the heat storage process, the phase change material (PCM) only accounts for less than 20% of the space of the PCM storage tank, and its heat storage can reach 50% of the total heat storage of the tank. In the discharge process, the water temperature of the ordinary tank decreases by 20 °C within 1.5 h, and the phase change process lasts approximately 3 h, with the water temperature remaining at 45~50 °C during this period. In the natural cooling process, the heat discharge of the two water tanks at night was similar, while the temperature of the ordinary water tank decreased by 12 °C and that of the phase change water tank decreased by 7 °C. By simulating the dynamic simulation model of the composite solar phase change thermal storage combined with an air-cooled heat pump system, the results show that the solar heating system with a PCM storage tank (SHS-PCM) saves 34% more energy than a solar heating system with a common tank (SHS-without PCM), and the volume of the PCM storage tank is reduced to 1/5 of the ordinary tank. The investment payback period method of energy saving reconstruction is used to analyze the economy of the SHS-PCM and the SHS-without PCM, the initial investment cost of the SHS-PCM is CNY 9858 higher than the SHS-without PCM, but the annual operation cost is saved by CNY 12,100, and the project investment payback period is 0.81 years, which has energy-saving potential and economic benefits. [ABSTRACT FROM AUTHOR]

Research activity in the field of combined cooling heating power (or trigeneration) systems with high renewable energy source (RES) contributions has increased rapidly over the last few years, in line with the European Union legislation about energy communities. However, technical challenges arise regarding the synergetic, sustainable and optimal integration of RES in local energy systems. In the present study, the operation of a trigeneration system located in the student residences of Democritus University of Thrace in Greece is examined. The system involves a combination of highly promising renewable and storage technologies, including solar thermal energy and biomass for heat generation, hot water tanks for thermal energy storage, absorption refrigeration for cooling, along with Organic Rankine Cycle and photovoltaic systems for electricity generation. System modeling and simulation have been implemented in Dymola environment with the use of Modelica equation-based modeling language. The accuracy of the model response has been validated against available measurements. Specific design and control measures have been proposed, simulated in a transient fashion and evaluated in terms of (i) RES generation, (ii) solar fraction and (iii) temporal flexibility. The measures examined, including the placement of a Li-ion battery, resulted in an increase of 24.6% in the heating demand solar contribution and of 7.9% in the renewable energy generated for the electricity demand, over the examined periods. [ABSTRACT FROM AUTHOR]

Utilizing biological processes for hydrogen production via gasification is a promising alternative method to coal gasification. The present study proposes a dynamic simulation model that uses a one-dimensional heat-transfer analysis method to simulate a biohydrogen production system. The proposed model is based on an existing experimental design setup. It is used to simulate a biohydrogen production system driven by the waste heat from an integrated gasification combined cycle (IGCC) power plant equipped with carbon capture and storage technologies. The data from the simulated results are compared with the experimental measurement data to validate the developed model's reliability. The results show good agreement between the experimental data and the developed model. The relative root-mean-square error for the heat storage, feed-mixing, and bioreactor tanks is 1.26%, 3.59%, and 1.78%, respectively. After the developed model's reliability is confirmed, it is used to simulate and optimize the biohydrogen production system inside the IGCC power plant. The bioreactor tank's time constant can be improved when reducing the operating volume of the feed-mixing tank by the scale factors of 0.75 and 0.50, leading to a 15.76% and 31.54% faster time constant, respectively, when compared with the existing design. [ABSTRACT FROM AUTHOR]

Electric-Steam Integrated Energy Systems (ES-IES) have garnered considerable attention in industrial applications due to their high energy utilization efficiency and energy density. Nonetheless, the limited thermal storage capacity of the steam system impacts the stability of ES-IES, posing a challenge for its implementation in scenarios with a high proportion of renewable energy sources. To address this limitation, this study demonstrates how the integration of a Steam Accumulator (SA) can enhance the stability of ES-IES through a dynamic simulation-based approach. Firstly, a novel method for simulating the steam system is introduced. This method utilizes a resolution-adaptive strategy based on the central implicit difference format to balance simulation accuracy and speed. Furthermore, a simulation framework for ES-IES is delineated, detailing the solution order of subsystems and system coupling interface parameter interaction method. Meanwhile, a comprehensive model and solution for the SA are proposed, aligning well with the aforementioned ES-IES simulation methods in terms of accuracy and complexity. Finally, case study demonstrated that equipping SA in ES-IES can effectively reduce its fault-recovery time by 57.9%, highlighting the efficacy of SA in promoting system stability and security. • A steam accumulator dynamic model and solution. • A novel steam system dynamic simulation approach. • An ES-IES simulation framework. • Fault-state ES-IES operation stability improvement. [ABSTRACT FROM AUTHOR]

The present work focuses on the development of a detailed dynamic model of an existing parabolic trough solar power plant (PTSPP) in Spain. This work is the first attempt to analyse the dynamic interaction of all parts, including solar field (SF), thermal storage system (TSS) and power block (PB), and describes the heat transfer fluid (HTF) and steam/water paths in detail. Advanced control circuits, including drum level, economiser water bypass, attemperator and steam bypass controllers, are also included. The parabolic trough power plant is modelled using Advanced Process Simulation Software (APROS). An accurate description of control structures and operation strategy is necessary in order to achieve a reasonable dynamic response. This model would help to identify the best operation strategy due to DNI (direct normal irradiation) variations during the daytime. The operation strategy used in this model has also been shown to be effective compared to decisions made by operators on cloudy periods by improving power plant performance and increasing operating hours. [ABSTRACT FROM AUTHOR]

Intelligent design and operation optimization allow energy systems to take advantage of the flexibility that multi-generation provides. This study proposes a basic solar-driven system integrated with thermal energy storage for round-the-clock energy harvesting. A modified configuration is then designed incorporating innovative multi-heat recovery approaches to increase the capacity and product diversity of the basic system. The modified system is able to cover vital urban utilities such as electricity, fresh water, cooling, and hydrogen throughout the day. To overcome the time-consuming procedure of dynamic techno-economic simulation as well as the limitation of commercial engineering equation solvers for tri-objective optimization, a deep learning approach is developed to reduce the computational complexity and improve the analysis accuracy. In this regard, the trained neural networks play an intermediary role in coupling the developed code with the MATLAB optimization toolbox. A comparison between the modified and conventional configurations indicates that implementing the multi-heat recovery approach results in a 29% increase in power generation while only increasing the overall system cost by 1.97%. From an economic perspective, the Sankey diagram depicts that the storage unit with a cost rate of 12.25 $/h accounts for 6.77% of the plant's cost rate, which enables the system to operate continuously. According to the sensitivity analysis and contour plots, the number of collectors significantly affects the total cost rate and fresh water production capacity while it has no tangible effect on the exergy efficiency. • A novel multigeneration system with thermal energy storage is designed. • A modified configuration with heat recovery is introduced to boost the capacity. • The comparative study indicates a 17.6% improvement in the power generation. • A dynamic simulation code is developed based on meteorological data. • A deep learning techno-economic optimization is applied to the system. [ABSTRACT FROM AUTHOR]

• An innovative slim decentralised plug-and-play tank is proposed for DHW production. • Model calibration is performed by experimental data in charge/discharge process. • Retrofit solution cuts required annual energy in half of which 82% is RES quota. • Optimised charging scheme reduces the total annual electrical energy by 5.2 %. • A degree increment in draw-off temperature increases annual CO 2 emission by 103 kg. The present study deals with a multi-objective analysis of an innovative decentralised system to produce and store domestic hot water (DHW), emphasising on the combined effects of the technological aspect, control strategy and user's behaviour. The proposed system, by relying on thermal energy storage, decouples energy production and demand while shaves peaks in the energy demand and, at the same time, provides more autonomy to users through local storages. To identify subtle interactions in components of DHW system, dynamic simulations are carried out by establishing a coupled TRNSYS-MATLAB code, calibrated and validated by experimental measurements. The energy analysis implies that the proposed system cuts the required annual electrical energy in half, of which up to 82% of needed primary energy is supplied from renewable sources, compared to previous electrical-decentralised system. The optimisation of the results through applying control strategies indicates that adopting a three-time charging scheme is advantageous in terms of providing a more stable temperature profile as well as a higher hot water temperature. Compared to an available-by-demand operation, this scheme reduces the required total annual electricity by 5.2 % and enhances total thermal loss from components up to 4.0%. Furthermore, a sensitivity analysis on the results emphasises the striking role of the user behaviour in electrical energy consumption either via draw-off temperature or adjusting the pre-defined temperature for activation of the built-in auxiliary heater. [ABSTRACT FROM AUTHOR]

As renewable energies are incorporated in larger shares in the electricity grid and district heating and cooling networks, the integration of storage solutions becomes more important. Thermal Energy Storage is an effective way to store heat and utilize the synergies between different energy carriers. Stratified storage tanks are a promising technology because of their low cost, simplicity and reliability. However, the modeling of the thermocline region in a stratified tank remains a challenge. There is a need to develop a fast and accurate 1D model for simulations and optimizations of TES. In this paper, a new discretization scheme is applied to the vertical axis of the storage tank. Orthogonal Collocation accurately represents the temperature profiles inside the storage tank with less points than the traditional multinode model, therefore running faster. Oscillations appear in the temperature profiles computed with orthogonal collocation if the thermocline represented is too steep and a low number of discretization points is used. But if a realistic thermocline is used as initial condition, the model performs well. Thus, it is appropriate to represent the real behavior of a storage tank, where uniform temperature conditions are avoided. Orthogonal Collocation on Finite Elements runs even faster and represents a good perspective for optimization studies. The model developed in this paper is validated with real data from a solar thermal plant with storage. A continuous and smooth model is also developed for natural convection inside the storage tank. The limitations of the model are discussed and perspectives on the modeling of natural convection for optimization models are given. • Orthogonal collocation is suggested for the 1D storage tank model discretization. • The proposed model runs faster than the multinode model for the same accuracy. • Orthogonal collocation on finite elements is suggested for optimization studies. • The storage tank model is validated with real plant data. • A continuous and smooth model for natural convection is developed. [ABSTRACT FROM AUTHOR]

The capability to dynamically plan, predict, and control indoor conditioning allows to adapt to individual preferences of inhabitants and enables demand side management. While former mainly improves thermal comfort of inhabitants so does latter unlock ecological and financial opportunities mostly for energy utilities. Commonly, dynamic indoor conditioning is based on piece-wise constant indoor temperature constraints. This paper's contribution is the presentation of additional constraints: in particular ones expressed relative to the nominal behavior of a hydronic heating system. This allows to simultaneously harness the relevant process variables in particular during the pre-loading and post-loading phases of a load reduction. The findings are based on data sets acquired on 10 inhabited, residential buildings in Stockholm over a whole year. One of the findings is that building models need to be adaptable if predictive control is applied in practice. This adaptability is assured by a novel concept, i.e. a so called model manager on which the control is relying for the selection of the most accurate model. Centralized optimal control of buildings connected to a district heating network is challenging in practice due to a high computational load. In order to reduce it, the herein presented method elaborates plans only every hour instead of at every control step for optimal control. Since these plans cannot be optimal due to the lack of regular update a hitherto unknown cascaded control logic has been developed that corrects planning errors and other disturbances. Capabilities are demonstrated and compared to conventional controllers in dynamic simulations of a multi-zoned building. The herein presented method is to our knowledge the first to provide all flexibility desired by energy utilities and inhabitants alike through harnessing the consequences of transitions. [ABSTRACT FROM AUTHOR]

As a result of the increased penetration of intermittent renewable energy sources, Combined Heat and Power (CHP) units are being looked upon as one of the sources that might provide for the ever growing need for electrical flexibility. However, CHP units are often considered as must-run units on the grid for their main purpose is generally to cover the heat demand of an adjoining District Heating Network (DHN). This paper demonstrates how a CHP–DHN system may be used as a frequency reserve without excessively compromising the lifetime of the CHP, using either a specific storage tank or the DHN's thermal inertia in order to compensate for the resulting heat imbalance. In the latter case, it is shown that a buffer tank, although smaller than a specific Thermal Energy Storage (TES), is required due to restrictions for acceptable DHN temperature gradients. In both approaches, the size of the tank has been mapped out considering frequency reserve's duration and capacity. The results show that a simplistic static model of the DHN is sufficient for the design of a specific TES, while a detailed dynamic simulation is required when the DHN is used as storage, to prevent overestimating the flexibility of the CHP–DHN system. This research could be used to assess the potential for improving CHP–DHN systems flexibility, using them as frequency reserves, and to design the required storage or buffer tanks. • A control strategy to use a CHP-DHN system as a frequency reserve is proposed. • Dedicated storage tanks and/or DHN thermal inertia are used. • The DHN can be used as heat storage, but a buffer tank is required. • A detailed dynamic DHN model is needed to determine the DHN flexibility. • The flexibility of the CHP–DHN system was determined for 370 MW CHP. [ABSTRACT FROM AUTHOR]