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Network temperatures in district heating systems are important operational factors for obtaining efficient performance. A low network return temperature allows for the recovery of low-grade heat from assets such as condensing boilers, waste incineration, geothermal sources and industrial waste heat. Fluctuations in heating and cooling demands affect the return temperatures of the building substations and in the network. This variability impacts the economic viability and environmental sustainability of the entire system. This paper presents a nonlinear optimization strategy to maintain sufficient energy flows in the network's primary and secondary circuits to achieve low return temperatures from all substations in the network. The defined optimization strategy incorporates the thermodynamic model of the substation and building heating system as opposed to traditional weather-based supply temperature adjustments. The estimated heat demands and tariffs, CO2 penalties are inputs used by the optimizer to find theoptimal solution. The total operational expenditure for electricity and gas consumption shows an 18% reduction with 8% reduction in emissions and 6% efficiency improvement when compared with the measured weather-based approach. The developed strategy will aid the network operators in the economic dispatch of heat generation while ensuring the user's thermal comfort.

Abstract As main contributors to greenhouse gas emissions, power and transportation are crucial sectors for energy system decarbonization. Their interaction is expected to increase significantly: plug-in electric vehicles add a new electric load, increasing grid demand and potentially requiring substantial grid upgrade; hydrogen production for fuel cell electric vehicles or for clean fuels synthesis could exploit the projected massive power overgeneration by intermittent and seasonally-dependent renewable sources via Power-to-Hydrogen. This work investigates the infrastructural needs involved with a broad diffusion of clean mobility, adopting a sector integration perspective at the national scale. The analysis combines a multi-node energy system balance simulation and a techno-economic assessment of the infrastructure to deliver energy vectors for mobility. The article explores the long-term case of Italy, considering a massive increase of renewable power generation capacity and investigating different mobility scenarios, where low-emission vehicles account for 50% of the stock. First, the model solves the energy balances, integrating the consumption related to mobility energy vectors and taking into account power grid constraints. Then, an optimal infrastructure is identified, composed of both a hydrogen delivery network and a widespread installation of charging points. Results show that the infrastructural requirements bring about investment costs in the range of 43–63 G€. Lower specific costs are associated with the exclusive presence of FCEVs, whereas the full reliance on BEVs leads to the most significant costs. Scenarios that combine FCEVs and BEVs lie in between, suggesting that the overall power + mobility system benefits from the presence of both drivetrain options.

Abstract: To maximize the sustainable and economic benefits of collective heating systems, proper sizing is fundamental. This paper presents the validation of a novel sizing approach for collective systems producing and distributing heat for both space heating and domestic hot water, utilizing residential heat meter data. A validation methodology is developed to overcome the limitations of this type of data to identify the peak heat demand and estimate the peak heat demand under design outdoor conditions. The latter is estimated utilizing multiple linear regression coupled with an analysis of the maximum deviations. The power-storage characteristic, which shows all combinations of thermal power and thermal storage to meet the peak heat demand is determined and used to validate the novel sizing approach for six case studies. Although the results are promising, undersizing problems may arise in cases with decentralized heat storage

Abstract: To achieve net-zero emissions by 2050, as outlined in the European Green Deal, nuclear power is expected to double between 2020 and 2050, mainly due to its low-carbon baseload capacity. Small modular reactors, new nuclear reactors designed to generate up to 300 MW of electricity, could help achieve this goal. Small modular reactors have unique advantages over existing large reactors, such as modularization, learning and co-location economics. However, these small modular reactors should also be economically viable. This review therefore focuses on the costs of small modular reactors. This review found an average capital cost of €7,031/kW and an average levelized cost of electricity of 85 €/MWh for small modular reactors, while capital costs were found to be on average 41% higher than for the large reactors. Carbon and gas prices are not included in this cost estimate, yet these volatile prices also affect small modular reactor costs. However, as the absolute cost is lower, the financial risk is lower for small modular reactors. The importance of regulations, discount rates, country and project specifications and public acceptance are also considered.

Thermo-economically optimal design = optimal molecule + optimal process + optimal equipment.

This paper presents a stochastic bi-level approach for tariff design in the electricity market where the leader is represented by a retailer and the follower by a residential prosumager, i.e. a consumer equipped with an energy system consisting of photovoltaic panels and a battery storage device. Both players solve an optimization problem subject to uncertainty in market prices, weather-related variables and electricity demand. To account for the retailer’s attitude towards risk, the upper level problem includes a safety measure to maximize. The model allows to determine a dynamic pricing scheme with time-variant rates delivering the average profit that can be gained in a given percentage of unfavorable realizations of the uncertain parameters and the optimal load pattern that minimizes the expected prosumager's electricity bill. The stochastic bi-level problem is reformulated as a single level model and different approaches to deal with the lower level problem and the non linearity in the objective function are analyzed and empirically investigated. A large number of numerical experiments have been carried out on real test cases. The results have shown the efficacy of the proposed approach as a tool to define pricing schemes that reflect the retailer's risk attitude underlining the importance of explicitly dealing with uncertainty.

National net zero emission targets could, if fully implemented, reduce best estimates of projected global average temperature increase to 2.0–2.4 °C by 2100, bringing the Paris Agreement temperature goal within reach. A total of 131 countries are discussing, have announced or have adopted net zero targets, covering 72% of global emissions. These targets could substantially lower projected warming as compared to currently implemented policies (2.9–3.2 °C) or pledges submitted to the Paris Agreement (2.4–2.9 °C). Current pledges for emissions cuts are insufficient to meet the Paris Agreement temperature goal. The wave of net zero targets being discussed and adopted could make the Paris goal possible if further countries follow suit.

Vacuum pressure swing adsorption (VPSA) has demonstrated promising features for the upgrading of biogas to biomethane. In this study, a biogas upgrading plant, comprised of a hybrid of an N-column VPSA unit (2 ≤N≤ 6) with a combined heat and power (CHP) engine, was developed and its techno-economic characteristics were assessed via a mathematical approach. Moreover, the techno economic analysis was used for the state-of-the-art VPSA configuration (a sophisticated configuration) and compared with the developed hybrid process. The prominent parameters including feedstock transport, biogas production, desulfurization, drying, upgrading, combustion, and grid injection were considered in the analyses of the plant for the upgrading capacity in the range of 100 - 6,500 Nm3/h. Sensitivity analysis of the most influencing parameters, i.e., electricity price, gas price, and feed processing revenues, was conducted for the developed models. Beside comparing upgrading cost of the sophisticated VPSA with other upgrading technologies, a detailed comparison with the best available membrane unit for biogas upgrading was conducted. The limitations of adsorption process and VPSA in reducing the upgrading cost were also investigated. The results showed that in the absence of subsidies and requirements for CO2 capture, the hybrid plant outperforms the sophisticated VPSA units. Also, higher market price of natural gas or feedstock processing revenues were necessary in order to render the plant profitable. The results showed that, at flowrates larger than 175 Nm3/h, the sophisticated VPSA unit required a lower investment cost than the membrane unit for identical outputs. The results also show that even at the most idealistic conditions in the adsorption process, the upgrading is not economically favorable without subsidies. The findings of this study shed light on the importance of process design for biogas upgrading.