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Abstract Because of environmental issues and the depletion of fossil fuels, the world energy sector is undergoing many changes toward increased sustainability. Among the many fields of research and development, power generation from low-grade heat sources is gaining interest and the organic Rankine cycle (ORC) is seen as one of the most promising technologies for such applications. In this paper, it is proposed to perform an experimentally-validated comparison of different modelling methods for the off-design simulation of ORC-based power systems. To this end, three types of modelling paradigms (namely a constant-efficiency method, a polynomial-based method and a semi-empirical method) are compared both in terms of their fitting and extrapolation capabilities. Post-processed measurements gathered on two experimental ORC facilities are used as reference for the models calibration and evaluation. The study is first applied at a component level (i.e. each component is analysed individually) and then extended to the characterization of the entire organic Rankine cycle power systems. Benefits and limitations of each modelling method are discussed. The results show that semi-empirical models are the most reliable for simulating the off-design working conditions of ORC systems, while constant-efficiency and polynomial-based models are both demonstrating lack of accuracy and/or robustness.

Abstract Efforts towards ensuring clean and affordable electricity for all have been progressing slowly in rural, off grid areas of developing countries. In this context, hybrid microgrids may offer reliable and potentially clean electricity for isolated locations. Nevertheless, the process of planning and operation of these systems faces several challenges, often due to the uncertainties related to the renewable resources and to the stochastic nature of electricity consumption in rural contexts. This paper tackles this problem and contributes to the literature in bridging the gap between field practices and two-stage stochastic modeling approaches by identifying an open-source modeling framework which is then applied to real local data. As reference case-study, we consider a microgrid built in 2015 in Bolivia. Overall, the optimal system results from a compromise between the Net Present Cost, the peak capacity installed and the flexibility (to balance variable generation). Different approaches to size isolated microgrids are tested, with the conclusion that methods accounting for the uncertainty in both demand and renewable generation may lead to a more robust configuration with little impacts on the final cost for the community.

Abstract The coupling of the heating and the electricity sectors is of utmost importance when it comes to the achievement of the decarbonisation and the energy efficiency targets set for the 2020 and 2030 in the EU. Centralised cogeneration plants connected to district heat networks are fundamental element of this coupling. Despite the efficiency benefits, the effects of introducing combined generation to the power system are sometimes adverse. Reduced flexibility caused by contractual obligations to deliver heat may not always facilitate the penetration of renewable energy in the energy system. Thermal storage is acknowledged as a solution to the above. This work investigates the optimal operation of cogeneration plants combined with thermal storage. To do so, a combined heat and power (CHP) plant model is formulated and incorporated into Dispa-SET, a JRC in-house unit commitment and dispatch model. The cogeneration model sets technical feasible operational regions for different heat uses defined by temperature requirements. Different energy system scenarios are used to assess the implications of the heating–electricity coupling to the flexibility of the power system and to the achievement of the decarbonisation goals in an existing non interconnected power system where CHP plants provide heating and electricity to nearby energy dense areas. The analysis indicates that the utilisation of CHP plants contributes to improve the overall system efficiency and reduce total cost of the system. In addition, the incorporation of thermal storage increases the penetration of renewable energy in the system.

Abstract The present paper focuses both on the thermodynamic and on the economic optimization of a small scale ORC in waste heat recovery application. A sizing model of the ORC is proposed, capable of predicting the cycle performance with different working fluids and different components sizes. The working fluids considered are R245fa, R123, n-butane, n-pentane and R1234yf and Solkatherm. Results indicate that, for the same fluid, the objective functions (economics profitability, thermodynamic efficiency) lead to different optimal working conditions in terms of evaporating temperature: the operating point for maximum power doesn’t correspond to that of the minimum specific investment cost: The economical optimum is obtained for n-butane with a specific cost of 2136 €/kW, a net output power of 4.2 kW, and an overall efficiency of 4.47%, while the thermodynamic optimum is obtained for the same fluid with an overall efficiency of 5.22%. It is also noted that the two optimizations can even lead to the selection of a different working fluid. This is mainly due to additional fluid properties that are not taken into account in the thermodynamic optimization, such as the fluid density: a lower density leads to the selection of bigger components which increases the cost and decreases the economical profitability.

Flexibility is crucial to enable the penetration of high shares of renewables in the power system while ensuring the security and affordability of the electricity dispatch. In this regard, heat–electricity sector coupling technologies are considered a promising solution for the integration of flexible devices such as thermal storage units and heat pumps. The deployment of these devices would also enable the decarbonization of the heating sector, responsible for around half of the energy consumption in the EU, of which 75% is currently supplied by fossil fuels. This paper investigates in which measure the diffusion of district heating (DH) coupled with thermal energy storage (TES) units can contribute to the overall system flexibility and to the provision of operating reserves for energy systems with high renewable penetration. The deployment of two different DH supply technologies, namely combined heat and power units (CHP) and large-scale heat pumps (P2HT), is modeled and compared in terms of performance. The case study analyzed is the future Italian energy system, which is simulated through the unit commitment and optimal dispatch model Dispa-SET. Results show that DH coupled with heat pumps and CHP units could enable both costs and emissions related to the heat–electricity sector to be reduced by up to 50%. DH systems also proved to be a promising solution to grant the flexibility and resilience of power systems with high shares of renewables by significantly reducing the curtailment of renewables and cost-optimally providing up to 15% of the total upward reserve requirements.

Abstract For decades, electrification planning in the developing world has often focused on extending the national grid to increase electricity access. This article draws attention to the potential complementary role of decentralized alternatives – primarily micro-grids – to address universal electricity access targets. To this aim, we propose a methodology consisting of three steps to estimate the LCOE and to size micro-grids for large-scale geo-spatial electrification modelling. In the first step, stochastic load demand profiles are generated for a wide range of settlement archetypes using the open-source RAMP model. In the second step, stochastic optimization is carried by the open-source MicroGridsPy model for combinations of settlement size, load demand profiles and other important techno-economic parameters influencing the LCOE. In the third step, surrogate models are generated to automatically evaluate the LCOE using a multivariate regression of micro-grid optimization results as a function of influencing parameters defining each scenario instance. Our developments coupled to the OnSSET electrification tool reveal an important increase in the cost-competitiveness of micro-grids compared to previous analyses.

Abstract Organic Rankine cycles (ORC) are an effective way to convert low-medium temperature heat to electricity that cannot be used for conventional high-temperature Rankine cycles. Even though there has been many studies of ORC systems over the past few decades, ORC heat sources have received relatively little attention. The heat sources providing energy to the ORC have different characteristics that significantly impact the theoretical analyses and system designs of ORC systems. This paper gives a theoretical categorization of heat sources to give uniform boundary conditions for further theoretical studies on cycle choices and working fluid screening. The ideal cycles for each heat source type are analyzed. Performance metrics are recommended for different heat source ORC systems. The general characteristics of the different heat sources including waste heat from industrial and power systems and geothermal, solar and biomass sources are given with their influences on the ORC systems. Finally, the market characteristics for ORC systems using different heat sources are reviewed with suggestions for future developments of ORC systems.