Response-surface-model-based system sizing for nearly/net zero energy buildings under uncertainty

Properly treating uncertainty is critical for robust system sizing of nearly/net zero energy buildings (ZEBs). To treat uncertainty, the conventional method conducts Monte Carlo simulations for thousands of possible design options, which inevitably leads to computation load that is heavy or even impossible to handle. In order to reduce the number of Monte Carlo simulations, this study proposes a response-surface-model-based system sizing method. The response surface models of design criteria (i.e., the annual energy match ratio, self-consumption ratio and initial investment) are established based on Monte Carlo simulations for 29 specific design points which are determined by Box-Behnken design. With the response surface models, the overall performances (i.e., the weighted performance of the design criteria) of all design options (i.e., sizing combinations of photovoltaic, wind turbine and electric storage) are evaluated, and the design option with the maximal overall performance is finally selected. Cases studies with 1331 design options have validated the proposed method for 10,000 randomly produced decision scenarios (i.e., users’ preferences to the design criteria). The results show that the established response surface models reasonably predict the design criteria with errors no greater than 3.5% at a cumulative probability of 95%. The proposed method reduces the number of Monte Carlos simulations by 97.8%, and robustly sorts out top 1.1% design options in expectation. With the largely reduced Monte Carlo simulations and high overall performance of the selected design option, the proposed method provides a practical and efficient means for system sizing of nearly/net ZEBs under uncertainty

RES (Renewable Energy Sources) Availability Assessments for Eco-fuels Production at Local Scale: Carbon Avoidance Costs Associated to a Hybrid Biomass/H2NG-based Energy Scenario

Eco-fuels are a sustainable solution to face increasing global energy consumptions and GHG emissions. This work was firstly focused on available renewables assessment linked to a local dimension. Furthermore, identifying the potential Eco-fuels capability, it was discussed how the capital expenditure for infrastructures is associated with carbon avoidance costs. A coastal municipality and an inland one, located in Central Italy, are selected as case studies. In order to assess PV and agro-forestry residues availability, a GIS-based analysis was performed. In this framework, a new energy scenario, based on H2NG blends use and ligneous biomass conversion, was presented. Specifically, the hydrogen for NG enrichment was produced by renewable electricity, while biomass energy content was evaluated considering gasification process. Finally, the governmental incentive schemes incidence (in force for bioenergy and hypothesized for hydrogen) on investments economic sustainability and on infrastructure deployment was compared in terms of carbon avoidance costs

An Economic, Energy, and Environmental Analysis of PV/Micro-CHP Hybrid Systems: A Case Study of a Tertiary Building

Our present standard of living depends strongly on energy sources, with buildings being a primary focus when it comes to reducing energy consumption due to their large contribution, especially in tertiary buildings. The goal of the present study is to evaluate the performance of two different designs of hybrid systems, composed of natural gas engines and photovoltaic panels. This will be done through simulations in TRNSYS, considering a representative office building with various schedules of operation (8, 12, and 24 h), as well as different climates in Spain. The main contributions of this paper are the evaluations of primary energy-consumption, emissions, and economic analyses for each scenario. In addition, a sensitivity analysis is carried out to observe the influence of energy prices, as well as that of the costs of the micro-CHP engines and PV modules. The results show that the scenario with the conventional system and PV modules is the most profitable one currently. However, if electricity prices are increased in the future or natural gas prices are reduced, the scenario with micro-CHP engines and PV modules will become the most profitable option. Energy service engineers, regulators, and manufacturers are the most interested in these results

Optimal Microgrid Topology Design and Siting of Distributed Generation Sources Using a Multi-Objective Substrate Layer Coral Reefs Optimization Algorithm

n this work, a problem of optimal placement of renewable generation and topology design for a Microgrid (MG) is tackled. The problem consists of determining the MG nodes where renewable energy generators must be optimally located and also the optimization of the MG topology design, i.e., deciding which nodes should be connected and deciding the lines’ optimal cross-sectional areas (CSA). For this purpose, a multi-objective optimization with two conflicting objectives has been used, utilizing the cost of the lines, C, higher as the lines’ CSA increases, and the MG energy losses, E, lower as the lines’ CSA increases. To characterize generators and loads connected to the nodes, on-site monitored annual energy generation and consumption profiles have been considered. Optimization has been carried out by using a novel multi-objective algorithm, the Multi-objective Substrate Layers Coral Reefs Optimization algorithm (Mo-SL-CRO). The performance of the proposed approach has been tested in a realistic simulation of a MG with 12 nodes, considering photovoltaic generators and micro-wind turbines as renewable energy generators, as well as the consumption loads from different commercial and industrial sites. We show that the proposed Mo-SL-CRO is able to solve the problem providing good solutions, better than other well-known multi-objective optimization techniques, such as NSGA-II or multi-objective Harmony Search algorithm.This research was partially funded by Ministerio de Economía, Industria y Competitividad, project number TIN2017-85887-C2-1-P and TIN2017-85887-C2-2-P, and by the Comunidad Autónoma de Madrid, project number S2013ICE-2933_02

Multi-objective design optimisation of standalone hybrid wind-PV-diesel systems under uncertainties

Optimal design of a standalone wind-PV-diesel hybrid system is a multi-objective optimisation problem with conflicting objectives of cost and reliability. Uncertainties in renewable resources, demand load and power modelling make deterministic methods of multi-objective optimisation fall short in optimal design of standalone hybrid renewable energy systems (HRES). Firstly, deterministic methods of analysis, even in the absence of uncertainties in cost modelling, do not predict the levelised cost of energy accurately. Secondly, since these methods ignore the random variations in parameters, they cannot be used to quantify the second objective, reliability of the system in supplying power. It is shown that for a given site and uncertainties profile, there exist an optimum margin of safety, applicable to the peak load, which can be used to size the diesel generator towards designing a cost-effective and reliable system. However, this optimum value is problem dependent and cannot be obtained deterministically. For two design scenarios, namely, finding the most reliable system subject to a constraint on the cost and finding the most cost-effective system subject to constraints on reliability measures, two algorithms are proposed to find the optimum margin of safety. The robustness of the proposed design methodology is shown through carrying out two design case studies

Techno-Economic Analysis of Rural 4th Generation Biomass District Heating

Biomass heating networks provide renewable heat using low carbon energy sources. They can be powerful tools for economy decarbonization. Heating networks can increase heating efficiency in districts and small size municipalities, using more efficient thermal generation technologies, with higher efficiencies and with more efficient emissions abatement technologies. This paper analyzes the application of a biomass fourth generation district heating, 4GDH (4th Generation Biomass District Heating), in a rural municipality. The heating network is designed to supply 77 residential buildings and eight public buildings, to replace the current individual diesel boilers and electrical heating systems. The development of the new fourth district heating generation implies the challenge of combining using low or very low temperatures in the distribution network pipes and delivery temperatures in existing facilities buildings. In this work biomass district heating designs based on third and fourth generation district heating network criteria are evaluated in terms of design conditions, operating ranges, effect of variable temperature operation, energy efficiency and investment and operating costs. The Internal Rate of Return of the different options ranges from 6.55% for a design based on the third generation network to 7.46% for a design based on the fourth generation network, with a 25 years investment horizon. The results and analyses of this work show the interest and challenges for the next low temperature DH generation for the rural area under analysis