Robust design and operation of stand-alone hybrid renewable energy systems

独立混合可再生能源系统的稳健设计和运行

• 批准号: RGPIN-2018-04745
• 负责人: Saif, Ahmed
• 金额: $ 1.89万
• 依托单位: Dalhousie University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2019
• 资助国家: 加拿大
• 起止时间: 2019-01-01 至 2020-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=681652
• 关键词: Robust; design; operation; stand; alone

Hybrid renewable energy systems (HRES), which combine conventional and renewable energy generators and energy storage, are becoming a viable and attractive alternative to grid connection for serving not only remote and isolated communities, but also independent buildings and urban communities. However, given the intermittent and unpredictable nature of renewable energy sources, the variability of demand and the high cost of energy storage, they need to be carefully designed and operated so they can serve demand reliably, economically and eco-friendly. Current HRES planning approaches are either too optimistic, naively assuming that the supply and demand are deterministic or have known probability distributions, or too pessimistic, planning them based on the worst-case scenario which leads to oversized and technically/economically infeasible systems. In this research program, we investigate new practical and balanced, i.e., neither optimistic nor pessimistic, approaches for planning HRES that effectively utilize the information contained in the historical supply and demand data to capture and deal with the uncertainty issue. We will implement and extend modern mathematical and statistical techniques in decision-making under uncertainty to tackle the HRES planning problem, which include time-series analysis, robust simulation-optimization, data clustering and distributionally-robust optimization. The research will also explore new efficient solution methods for these large-scale and computationally-challenging problems that can be applied also to handle other decision-making problems. Furthermore, we will study the co-optimization of electrical and thermal energy supply in buildings and communities that use combined-heat-and-power (CHP) units while considering the effect of new technologies such as electric vehicles and solar roofs. This research is expected to significantly improve the technical and economical feasibility of stand-alone HRES through better design and operation, putting them on par with (or even better than) our current fossil-based centralized energy supply systems. On one hand, this will enable rural Northern communities in Canada, including aboriginal communities, to have reliable and economical energy supply that uses locally-abundant renewable energy resources such as wind, hydro, tidal and solar energies. On the other hand, implementing the proposed robust HRES planning framework in energy management systems for grid-connected urban and suburban communities will increase the penetration of renewable energy sources and foster the transition towards a more sustainable and secure energy system.

结合了常规和可再生能源生成器和能源存储的混合可再生能源系统（HRES）已成为网格连接的可行且有吸引力的替代方案，不仅为遥远和孤立的社区提供服务，还为独立的建筑物和城市社区提供服务。但是，鉴于可再生能源的间歇性和不可预测的性质，需求的可变性和储能的高成本，需要仔细设计和操作，以便它们可以可靠，经济和环保。当前的HRES计划方法要么太乐观，要么天真地假设供求是确定性或已知的概率分布，要么过于悲观，或者是基于最坏的情况，这会导致超大且技术上不可行的系统。在该研究计划中，我们研究了新的实践和平衡，即既不乐观也不是悲观的方法，即有效地利用历史供求数据中包含的信息来捕获和处理不确定性问题。我们将在不确定的决策中实施并扩展现代数学和统计技术，以解决HRES计划问题，其中包括时间序列分析，强大的模拟优化，数据群集和分布型优化。该研究还将探索这些大规模和计算挑战性问题的新有效解决方案方法，这些方法也可以应用于处理其他决策问题。此外，我们将研究使用联合加热和电力（CHP）单元的建筑物和社区中电气和热能供应的合法化，同时考虑了新技术的效果，例如电动汽车和太阳能屋顶。预计这项研究将通过更好的设计和操作来显着提高独立HRE的技术和经济可行性，使其与目前基于化石的集中能源供应系统相当（甚至比）。一方面，这将使包括原住民社区在内的加拿大农村北部社区能够拥有可靠且经济的能源供应，该供应使用本地丰富的可再生能源，例如风，水力，潮汐和太阳能。另一方面，针对网格连接的城市和郊区社区实施拟议的强大的HRES计划框架将增加可再生能源的渗透，并促进向更可持续和安全的能源系统的过渡。