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【Applied Energy最新原创论文】具有非凸多相最优潮流的分布式能源系统离散优化设计

AEii国际应用能源  · 公众号  ·  · 2023-11-17 18:30

正文

原文信息:

Discrete optimal designs for distributed energy systems with nonconvex multiphase optimal power flow

原文链接:

https:/www.sciencedirect.com/science/article/pii/S0306261923015003

Highlights

(1)      The selection of discrete technologies in the presence of MOPF constraints is enabled.

(2)      An improved formulation selects feasible ASHP - thermal storage combinations.

(3)      The algorithm finds feasible solutions where the state-of-the-art MINLP solver fails.

(4)      The proposed heuristic modification decreases computational time.

(5)      ASHPs with local renewable energy generation can help minimise network violations.

摘要

在并网分布式能源系统(DES)中,小规模技术的最佳选择、规模和位置有助于减少碳排放、消费者成本和网络不平衡。目前,关于DES设计,特别是那些带有电气化加热系统的设计,如何影响大多数DES连接的不平衡低压配电网的研究明显缺乏。这是第一个提出优化框架的研究,用于获得并网DES设计的离散技术规模和选择,同时考虑多相最优潮流(MOPF)约束,以准确地表示不平衡低压配电网络。提出一种求解混合整数非线性规划(MINLP)公式的算法。它采用基于混合整数线性规划(MILP)和非线性规划(NLP)的分解,并使用整数切割和互补重构来获得相对于网络约束也是可行的离散设计。为了提高计算速度,对原算法进行了启发式改进。改进的配方选择可行的组合的空气源热泵(ASHPs)和热水储罐也提出。使用两个不同大小的网络来测试优化方法。采用电加热(空气源热泵和储罐)的设计与传统燃气锅炉进行了比较。该算法优于现有最先进的商业确定性MINLP求解器之一,后者无法在指定的时间限制内在两个实例中找到任何解。虽然所有情况都得到了可行的解,但并非所有情况都实现了收敛,特别是对于那些涉及较大网络的情况。在收敛的地方,启发式修正算法的结果比原算法快了70%。案例研究的结果表明,与燃气锅炉相比,包括空气源热泵可以支持高达16%的可再生发电容量,尽管空气源热泵的投资成本更高,因为当地发电和消费将与过剩电力出口相关的网络违规行为降至最低。结果还表明,在DES设计问题中考虑非线性潮流约束的重要性。优化框架和结果可用于通知政策制定者和网络运营商等利益相关者,以增加可再生能源容量并帮助国内供暖系统的脱碳。

更多关于"unmanned aerial vehicles"的研究请见:

https://www.sciencedirect.com/search?qs=unmanned%20aerial%20vehicles&pub=applied%20energy

Abstr act

The optimal selection, sizing, and location of small-scale technologies within a grid-connected distributed energy system (DES) can contribute to reducing carbon emissions, consumer costs, and network imbalances. There is a significant lack of studies on how DES designs, especially those with electrified heating systems, impact un[1]balanced low-voltage distribution networks to which most DES are connected. This is the first study to present an optimisation framework for obtaining discrete technology sizing and selection for grid-connected DES design, while simultaneously considering multiphase optimal power flow (MOPF) constraints to accurately represent unbalanced low-voltage distribution networks. An algorithm is developed to solve the resulting Mixed-Integer Nonlinear Programming (MINLP) formulation. It employs a decomposition based on Mixed-Integer Linear Programming (MILP) and Nonlinear Programming (NLP) and uses integer cuts and complementarity reformulations to obtain discrete designs that are also feasible with respect to the network constraints. A heuristic modification to the original algorithm is also proposed to improve computational speed. Improved formulations for selecting feasible combinations of air source heat pumps (ASHPs) and hot water storage tanks are also presented. Two networks of varying size are used to test the optimisation methods. Designs with electrified heating (ASHPs and tanks) are compared to those with conventional gas boilers. The algorithms outperform one of the existing state of-the-art commercial deterministic MINLP solvers, which fails to find any solutions in twoinstances within specified time limits. While feasible solutions were obtained for all cases, convergence was not achieved for all, especially for those involving the larger network. Where converged, the algorithm with the heuristic modification has achieved results up to 70% faster than the original algorithm. Results for case studies suggest that including ASHPs can support up to 16% higher renewable generation capacity compared to gas boilers, albeit with higher ASHP investment costs, as local generation and consumption minimises network violations associated with excess power export. The results also show the importance of including nonlinear power flow con[1]straints in DES design problems. The optimisation framework and results can be used to inform stakeholders such as policymakers and network operators, to increase renewable energy capacity and aid the decarbonisation of domestic heating systems.

Keywords

Distributed energy

Technology selection

Discrete sizing

Nonlinear

Multiphase optimal power flow

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