• Energy Research

Optimizing unit sizes and operation within a Renewable Energy Community (REC) can match intermittent renewable energy generation with variable user energy demands. These uncertain variables are often represented by pre-defined stochastic scenarios, without searching for the “best” scenarios and testing the optimization models with these scenarios. Moreover, little work both optimized RECs under uncertainty and distributed optimal life-cycle costs (investment and operation) among members. Thus, the objectives are: i) identifying the “best” set of stochastic scenarios of solar irradiance and user electricity demands and ii) assessing the accuracy of the “stochastic forecasts” of the total system costs and unit sizes, obtained by solving a stochastic programming model based on the “best” scenarios. The proposed novel procedure shifts the “present moment” back in time to split historical data into “past” and “future” periods used to identify the “best” scenarios and compare the “stochastic forecasts” with the utopic “perfect forecasts” based on the perfect knowledge of real data, respectively. The small errors between these forecasts in the optimal life-cycle costs (less than 2 %) and sizes (3–13 %) indicate good effectiveness of the suggested procedure. Also, the optimal life-cycle costs of “stochastic forecasts” are fairly distributed among users by applying the Shapley value mechanism.

A realistic pursuit of decarbonization targets requires planning and designing new configurations of “multi-energy systems” to identify the optimal number, type, location and size of the energy conversion and storage units and their interconnections with the end users of different forms of energy. The common approach in the literature is to treat the optimization problem of energy conversion and storage separately from that of energy networks, and the few attempts to address the two problems simultaneously have led to oversimplifications due to the very large number of decision variables involved. To fill this gap, this study introduces “DOMES” (Design Of Multi-Energy Systems), a general optimization method for the integrated synthesis, design and operation of a multi-energy system in its entirety. With the goal of minimizing costs and reducing carbon emissions, DOMES can simultaneously find the location, type, size and operation of the energy conversion and storage units, as well as t...

Preheating is often required to prevent hydrate formation during the pressure reduction process in a natural gas distribution network’s pressure reduction station. This paper examines an energy recovery method to avoid the cost and energy consumption of this preheating. The primary aim is to assess the techno-economic feasibility of an energy recovery system based on the Ranque–Hilsch vortex tube coupled to a heat exchanger for large-scale application to the gas grid. To this end, a techno-economic model of the entire energy recovery system was included in an optimisation procedure. The resulting design minimises the payback period (PP) when the system is applied to the pressure reduction stations belonging to a particular gas grid. The pressure reduction stations always operate at an outlet pressure above atmospheric pressure. However, available performance models for the Ranque–Hilsch vortex tube do not permit prediction at backpressure operation. Therefore, a novel empirical model of the device is proposed, and a cost function derived from several manufacturer quotations is introduced for the first time, to evaluate the price of the Ranque–Hilsch vortex tubes. Finally, a nearly complete set of pressure reduction stations belonging to the Italian natural gas grid was chosen as a case study using actual operating parameters collected by each station’s grid manager. The results indicate that the environmental temperature strongly affects the technical and economic feasibility of the proposed energy recovery system. In general, pressure reduction stations operating at an ambient temperature above 0 °C are economically desirable candidates. In addition, the higher the energy recovery system convenience, the higher the flow rate and pressure drop managed by the station. In the Italian case study, 95% of preheating costs could be eliminated with a PP of fewer than 20 years. A 40% preheating cost saving is still possible if the maximum PP is limited to 10 years, and a small but non-negligible 3% of preheating costs could be eliminated with a PP of fewer than 4.5 years.

Energy Communities (ECs) are aggregations of users that cooperate to achieve economic benefits by sharing energy instead of operating individually in the so-called “disagreement” case. As there is no unique notion of fairness for the cost/profit allocation of ECs, this paper aims to identify an allocation method that allows for an appropriate weighting of both the interests of an EC as a whole and those of all its members. The novelty is in comparing different optimization approaches and cooperative allocation criteria, satisfying different notions of fairness, to assess which one may be best suited for an EC. Thus, a cooperative model is used to optimize the operation of an EC that includes two consumers and two solar PV prosumers. The model is solved by the “Social Welfare” approach to maximizing the total “incremental” economic benefit (i.e., cost saving and/or profit increase) and by the “Nash Bargaining” approach to simultaneously maximize the total and individual incremental economic benefits, with respect to the “disagreement” case. Since the “Social Welfare” approach could lead to an unbalanced benefit distribution, the Shapley value and Nucleolus criteria are applied to re-distribute the total incremental economic benefit, leading to higher annual cost savings for consumers with lower electricity demand. Compared to “Social Welfare” without re-distribution, the Nash Bargaining distributes 39–49% and 9–17% higher annual cost savings to consumers with lower demand and to prosumers promoting the energy sharing within the EC, respectively. However, total annual cost savings drop by a maximum of 5.5%, which is the “Price of Fairness”.

Abstract Absorption cycle is the leading technology among solar thermally driven cooling/heating systems thanks to its high performance and favourable economics. Most studies deal with specific layouts or compare the performance of different systems. However, a clear comparison of the main configurations at the same boundary conditions and modelling approach is still missing, and the search for improved configurations is still an open field. The goal of this article is twofold: searching for the conceptual development in the evolution of the main existing configurations (single, half, double effect and GAX systems) and identifying new configurations to improve system performance. The first goal is accomplished by analysing in detail the design features and variables of all configurations and creating and running design models at the same cooling duty and ambient conditions. The second one is accomplished by optimizing the design of each configuration using the general methodology “HEATSEP”, which is able to take into account every possible internal thermal interaction in each optimization step. Results include a complete conceptual overview of the development of the existing configurations and the proposal of new ones, which show higher than 3% COP gains in comparison with the best corresponding single effect configurations in the literature.