Optimal double Q AC-DC hybrid distribution system planning with explicit topology-variable-based reliability assessment. (15th September 2022) - Wang, Ziyao; Zhong, Lipeng; Pan, Zhenning; Yu, Tao; Qiu, Xingyu
Highlights: An explicit topology-variable-based reliability assessment for ADHDS planning is proposed. A linearized power flow for ADHDS planning model is formulated. A Globally Pareto-optimal set for reliability and economy is constructed based on adaptive ε-constraint method. Key factors that restrict the development of DC distribution system are revealed. ADHDS can provide a promising solution to the system with high proportion of DC elements. Abstract: AC-DC hybrid structure offers a promising solution to accommodate AC/DC loads and distributed generators (DGs) in future smart grid. However, due to the complexity brought by reliability assessment and hybrid power flow, almost existing planning models of AC/DC hybrid distribution systems (ADHDS) are solved by heuristic algorithms, which cannot guarantee the optimality of solution. A novel ADHDS planning model that achieves two objectives: economy and reliability (double Q planning technique) is established in this paper. This novel planning model incorporates reliability indices, i.e., SAIDI, SAIFI, and EENS explicitly, which established the relationship between reliability and planning topology with an explicit method. Moreover, a linearized hybrid power flow for ADHDS planning is utilized in this paper. Finally, ADHDS planning model can be established as MILP and solved efficiently. Further, a globally Pareto-optimal set for reliability and economy is constructed based on adaptive ε-constraint method, enabling planners to make better trade-offs. Case studies demonstrate that ADHDS outperform than pure AC or DC solution for systems with high proportion of DC elements, effectively reducing distribution system cost with low-level reliability sacrifice. Besides, the effect of DG penetration, DC proportion, and failure rate of voltage source converter (VSC) on optimal double Q planning solution are revealed.