A Mixed integer linear programming-based distributed energy management for networked microgrids considering network operational objectives and constraints

IF 1.6 Q4 ENERGY & FUELS
Guodong Liu, Maximiliano F. Ferrari, Yang Chen
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引用次数: 0

Abstract

Mixed integer linear programming (MILP)–based distributed energy management for networked microgrids embedded modern distribution systems is proposed. Considering the diverse ownership of microgrids, distributed energy resources (DERs) that interface directly with utilities and responsive loads, an alternating direction method of multipliers–based distributed framework was formulated for the scheduling of networked microgrids embedded modern distribution systems by adjusting nodal price signals iteratively. In addition, to make the formulated optimization problems resolvable through more accessible and popular MILP solvers, different linearisation techniques were employed to transform the nonlinear terms into linear or mixed integer linear formats. The proposed MILP-based distributed method preserves all participants' autonomy (e.g., microgrids, DERs that interface directly with utilities and responsive loads), while incentivising them to actively participate in the distribution system operation with price signals. The proposed method is validated with results of numerical simulation using a modern distribution system consisting of multiple networked microgrids, DERs that interface directly with utilities, as well as responsive loads.

Abstract Image

考虑网络运营目标和约束的基于混合整数线性规划的网络微电网分布式能源管理
提出了基于混合整数线性规划(MILP)的网络化微电网嵌入式现代配电系统分布式能源管理方法。考虑到微电网、与公用事业直接接口的分布式能源(DERs)和响应性负荷的不同所有权,通过迭代调整节点价格信号,提出了一种基于乘数的分布式框架交替方向方法,用于嵌入式现代配电系统的网络化微电网调度。此外,为了使公式中的优化问题可以通过更易于访问和流行的MILP求解器来求解,采用了不同的线性化技术将非线性项转换为线性或混合整数线性格式。提出的基于milp的分布式方法保留了所有参与者的自主权(例如,微电网,直接与公用事业和响应负载接口的der),同时通过价格信号激励他们积极参与分配系统的运行。采用由多个网络微电网、直接与公用事业接口的分布式电源以及响应负载组成的现代配电系统进行了数值模拟,验证了所提方法的有效性。
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来源期刊
IET Energy Systems Integration
IET Energy Systems Integration Engineering-Engineering (miscellaneous)
CiteScore
5.90
自引率
8.30%
发文量
29
审稿时长
11 weeks
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