59 research outputs found

    Impact of network modelling in the analysis of district heating systems

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    Network modelling is crucial for the simulation of district heating system responses to changes in operating conditions. Various applications, aimed at finding optimal district heating design and operations, neglect or strongly simplify the network dynamics. In this paper, the effect of including network dynamics in district heating system modelling has been analyzed. Different physical contributions have been considered separately: thermal losses, thermal transients and delay time due to the various costumer distances. This allows estimating the significance of the various phenomena in the estimation of the thermal request, in particular during demand peaks. Results shows that the thermal power required by the thermal plant is significantly different if evaluated relying on a network model or not; in case of thermal peak this is under-estimated up to 20% if the network dynamic is not taken into account. In particular, the inclusion of the thermal transient in the model is found to be crucial for considerably improving the result accuracy in the peak estimation. Effects for inclusion of thermal losses calculation have been quantified; errors reaches 4% in case of not perfectly insulated pipelines. The effect of neglecting network dynamics have also been analyzed in the context of demand side management (DSM) district heating systems. In particular, the effects are tested on a model for the best rescheduling of on-off time of the building heating device to optimally shave the thermal peak. Results show that the benefits achieved by the demand response model that include the thermal dynamics contribution increase from 1 to 18%; this is because the contribution of the different times the water trains takes to reach the plants (from the buildings) and of the water in the pipelines cooled down during night are relevant. Furthermore, different options are discussed to take into account compactly the network dynamic

    Impact of thermal masses on the peak load in district heating systems

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    During district heating operations, part of the heat supplied to the network is used to increase the temperature of the various components (e.g. transport and distribution networks, heat exchangers installed in the substations, heating circuits and heating devices in buildings). The mass of these components acts as a thermal storage, storing heat when their temperature increases and releasing heat when they cool down. The impact may become significant, especially during shutdown or setback. In this paper, the components are analyzed in order to estimate the impact of their thermal capacity on the district heating demand. This provides a clear image of the additional supply used to heat the other thermal masses, that can be managed differently since partially independent from the indoor temperature. Results show that in the case study analyzed, i.e. large system mainly switched off during night, the heat absorbed by the thermal masses corresponds to the 4% of the heat supplied during the entire day and 70% of the heat provided during the peak. The various thermal masses affect the extra heat absorbed to a similar extent (except for radiators). Results provide a clue that proper management of thermal masses for energy saving might be considered

    Implementing Optimal Operation of Multi-Energy Districts with Thermal Demand Response

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    The combination of different energy vectors in the context of multi-energy systems is a crucial opportunity to reach CO2 reduction goals. In the case of urban areas, multi-energy districts can be connected with district heating networks to efficiently supply heat to the buildings. In this framework, the inclusion of the thermal demand response allows for significantly improve the performance of multi-energy districts by smartly modifying the heat loads. Operation optimization of such systems provides excellent results but requires significant computational efforts. In this work, a novel approach is proposed for the fast optimization of multi-energy district operations, enabling real-time demand response strategies. A 3-step optimization method based on mixed integer linear programming is proposed aimed at minimizing the cost operation of multi-energy districts. The approach is applied to a test case characterized by strongly unsteady heat/electricity and cooling demands. Results show that (a) the total operation cost of a multi-energy district can be reduced by order of 3% with respect to optimized operation without demand side management; (b) with respect to a full optimization approach, the computational cost decreases from 45 min to 1 s, while the accuracy reduces from 3.6% to 3.0%

    Exergoeconomic analysis for the design improvement of supercritical CO2 cycle in concentrated solar plant

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    In this work, an exergoeconomic analysis is applied to the power cycle of a concentrated solar plant for its design improvement. A supercritical CO2 cycle connected with the exothermic reactor of a thermochemical storage unit is considered. The analysis is conducted with the goal of highlighting the advantages of exergoeconomic analysis while suggesting changes to both the design parameters and the system configuration. Starting from the plant configuration which guarantees the maximum efficiency, the exergoeconomic analysis is iteratively applied with the goal of reducing the unit cost of electricity. The analysis is conducted in a way that cost functions of the components can be substituted with the cost analysis of specific designs. This is a big advantage of this procedure, which is suitable for applications in which economic analysis requires a detailed knowledge of the system characteristics. The procedure is then validated comparing the results with those obtained through mathematical optimization

    Demand side management in district heating systems by innovative control

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    Demand side management can be successfully applied to district heating systems for shaving thermal peaks. Peak shaving allows increasing share of convenient and less pollutant sources (waste heat, cogeneration and renewables) and enabling further building connections without modifying the pipelines. Demand side management in district heating is mainly done by shifting the load. Another interesting option consists in adjusting the substation regulation strategy; this approach not affects the heating schedule. This paper aims at analysing the opportunities for peak shaving using an innovative regulation strategy in the district heating substations, by controlling with a building model the effects on the indoor comfort conditions. The regulation strategy adopted is the Differential of Return Temperatures (DRT), that includes a constraint on the cold outlet section of the heat exchanger. This paper shows that thermal peak of building demand reducing on average of 15% by using the DRT regulation. Considering an entire distribution network, taking into account its thermal dynamics, the total peak request can be shaved of about 24%. Setting of the DRT regulation strategy has been shown being crucial for achieving satisfying peak shaving without compromising the indoor comfort conditions

    Optimal Installation of Heat Pumps in Large District Heating Networks

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    Power-to-heat technology represents a promising solution for the decarbonization of the energy sector. The installation of large-scale heat pumps within district heating systems is widely recognized to be a cost-effective and competitive way to provide flexibility to the electric system, enhancing the use of intermittent renewable energy sources. The goal of this paper is to show how the economic and environmental benefits provided by the installation of a large-scale heat pump in existing district heating systems vary according to the installation location in different scenarios. To do that, an integrated methodology is developed. This includes a physical model of the thermo-fluid dynamic of the district heating network and a detailed modeling of the heat pump. To compare the different positions and also the different operating conditions, an approach based on exergy analysis is adopted. Moreover, a specific control strategy of the mass-flow rate is analyzed to further reduce greenhouse gas emissions. The application to a real large-scale district heating network shows that reductions in CO2 emissions of almost 4% can be obtained by installing a single heat pump of about 4 MWe (over a total thermal load of about 305 MWt), while this positive effect can be reduced by up to 63% if placing the heat pump at non-optimal locations

    Integration of ThermoChemical Energy Storage in Concentrated Solar Power. Part 1: energy and economic analysis/optimization

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    Coupling of Concentrated Solar Power and Thermo-Chemical Energy Storage is a very interesting option because of the high efficiencies attainable with a renewable source and the large variation of solar radiation. Thermo-Chemical Energy Storage based on Calcium-Looping represents a promising opportunity thanks to high operating temperature, high energy density, null thermal losses and cheap calcium oxide precursor exploitable. The large variety of suitable power blocks and the importance of their integration in the discharging process makes it necessary to perform a coherent analysis of the selected alternatives, in order to compare them and establish the most convenient integration. Many aspects must be taken into account, such as system efficiency, investment costs and layout complexity. The purposes of the present work are: the development of a methodology to simulate the entire plant operations; the synthesis of heat recovery systems for both the charging and discharging processes; the execution of an economic analysis and the development of economic optimizations for the design/dimensioning of solar side and calciner side. Between the options investigated, power blocks based on supercritical CO2 are the most convenient both in terms of global efficiency (higher than 19%) and capital investment, keeping this advantage also for higher plant sizes. The methodology here developed and the results obtained are useful information for a deeper analysis of the most promising integration alternative, which is performed in the second part of this study

    Integration of ThermoChemical Energy Storage in Concentrated Solar Power. Part 2: comprehensive optimization of supercritical CO2 power block

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    Abstract Among the various options of Thermo-Chemical Energy Storage, Calcium-Looping represents a promising alternative for Concentrated Solar Power plants, thanks to high operating temperatures, high energy density and absence of thermal losses. Finding the most suitable power cycle for this system is a task that has still to be solved and is not trivial because it consists in a complex process synthesis problem. From a preliminary analysis (Part 1), supercritical CO2 cycles results to be the most promising option. In the present work, the integration of this power block (pilot plant size, 2 MWe) is deeply investigated through a comprehensive analysis. Numerous thermal cycle layouts are considered and two options for the power block thermal feeding are assumed. The HEATSEP methodology (comprising genetic algorithm, pinch analysis and bisection) is adopted to optimize both components operating conditions and heat transfer processes in the discharging phase. The plant section devoted to the charging process is optimized and dimensioned taking into account the transient operation. Thanks to the complex problem structure developed, the algorithm is free to find the most suitable configuration between a huge set of feasible combinations. Both energy and economic optimizations are performed for the complete plant and, being in contrast between them, a multi-objective optimization is executed. The independent variables influence on the resulting configuration is assessed and intermediate layouts obtained from the Pareto curve are commented. Carbonator inlet temperature of reactants are observed to increase with plant efficiency. The maximum efficiency (21%) is obtained with the most complex power block (recompression, intercooling and reheating) exchanging heat directly on the carbonator wall. Less performing discharging processes are cheaper but determine higher costs of charging sections; the resulting effect is positive and the integration of simpler power blocks results economically convenient. A power cycle with single intercooling and thermal feeding performed on the carbonator outflows is the result of economic optimization (efficiency equal to 16.3%). The algorithm gives precedence to power block thermal feeding and then to reactants preheating. Novel plant layouts are designed for these configurations and data useful for further investigations are provided in the last part of this work

    Including thermal network operation in the optimization of a Multi Energy System

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    The combined production of different energy vectors with Multi Energy Systems is a very attractive opportunity to increase the generation efficiency, compensate the oscillations of renewable sources, and improve the flexi-bility in power generation. Optimizing their operation is a complex task, since the problem can easily reach high dimensions, representing a challenge for commercial solvers. The inclusion in the optimization of a thermal network whose simulation is based on temperatures and flowrates allows to significantly improve the applica-bility of the obtained results. In addition, the effect of the operating temperatures on the performances of thermal components should be included as well. With these purposes, the present study proposes a strategy for the operation optimization of a MES and its internal thermal network. The model relies on a decomposition approach, where the original problem is divided in two subproblems. In the first one, the MES operating costs are minimized without considering the effects of the thermal network, while in the second one, the thermal network operation is optimized in order to find the operating conditions that are more favourable to the ones found for the MES. These subproblems are iteratively solved until the process converges to a stable solution. Some efforts are taken to keep the mathematical formulation as simple as possible (the MES is a Mixed Integer Linear Pro-gramming, while the heating network is a Quadratically Constrained Programming). The developed model al-lows to find near-optimal solutions which satisfy the numerous physical and technical constraints addressed. The results provide an optimized schedule for the thermal storage in terms of mass flowrates and temperature. One of the strengths of the model is the relatively low computational time required to reach the convergence and, despite not being the global optimum, the high quality of the solution obtained

    Optimal operation of district heating networks through demand response

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    In this paper, an optimization method aiming at minimizing the thermal peaks in district heating networks is proposed. The method relies on a thermo-fluid dynamic model of both the supply and return networks and permits to analyze the opportunities for thermal peak shaving through “virtual storage”. The latter is obtained through variation of the thermal request profiles of the users. The presence of a peak in the morning is due to the shut-down or attenuation of the heating systems during the night, which lead to a dramatical increase of the thermal request early in the morning. The peak compromises a full exploitation of cogeneration and renewable plants that are able to cover just a portion of the maximum load. Consequently, boilers have to be used, leading the system to a performance reduction and to an increase of primary energy consumption. Moreover, the peak makes the possibility of network extension quite difficult, because of the limitation on mass flow rates in the pipes. For this reason, a model is developed to make the thermal profile as flat as possible. The model is applied to a portion of the Turin district heating network, which is the largest network in Italy. Results show that reductions between 20% and 42% are possible, depending on the maximum changes in the possible schedules
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