AC/DC Hybrid Distribution System Expansion Planning Under Long-Term Uncertainty Considering Flexible Investment

Abstract

This paper presents a novel flexible multistage AC/DC distribution system expansion planning model, where the flexible investment strategy is taken into account to address the long-term development uncertainty of load demand and DG. Uncertainty is modeled through a multistage scenario tree to capture the possible system states across the planning horizon. As uncertain information revealed gradually over the planning horizon, the planning decisions at each stage are made sequentially within limited disposable reservation funds (RFs). The overall problem is formulated as a mixed-integer linear programming model that guarantees the convergence to optimality by using commercially available software. We compare the total costs of the optimal planning solutions within different proportions of RFs and analyze the flexibility value of RFs for long-term planning problems. In addition, the impact of RFs on the adjustment ability of the plans and the investment risks under uncertainty are evaluated. Case studies are carried out on an AC/DC hybrid system to validate the effectiveness of the proposed model to constitute flexible options when facing long-term uncertainty. The obtained results show the importance of reserving a suitable proportion of RFs in the planning stage, which has a significant influence on the adaptability of the planning solution to uncertain factors. INDEX TERMS AC/DC distribution system, expansion planning, mixed-integer linear programming, flexible investment, long-term uncertainty. NOMENCLATURE INDICES

Electric Power Systems in More and All Electric Aircraft: A Review

“…In [73], uncertainties were taken into consideration and although a ground based ac-dc hybrid system was assumed, the idea could be applied to MEA/AEA EPS. A multistage scenario tree was employed and possible scenarios were determined in advance; using a rolling planning method, a decision was made based on constructed scenarios; in addition, regarding new uncertainties, new stages were added to the scenario tree.…”

Multi-stage Co-planning Model for Power Distribution System and Hydrogen Energy System Under Uncertainties

“…In [10], a joint PDS and renewable energy expansion planning model that considers demand response and energy storage is developed, and the overall problem is linearized and formulated as a scenariobased stochastic MILP model. Reference [11] proposes an MILP-based AC/DC hybrid PDS planning model to resist long-term load growth uncertainties, in which the power line thermal quadratic constraints are linearized by several square constraints. In [12], a bi-level multi-objective RES and energy storage co-planning model is developed considering both RES and power load uncertainties.…”

“…In [14], a security-constrained AC/DC hybrid PDS expansion planning model is established to accommodate the high penetration of RES in weak grids, and the overall problem is formulated as a mixed-integer second-order cone programming (MISOCP) model. Reviewed from the aspect of solution techniques, the commonly-used methods in existing literature can be divided into three groups: mathematical optimization methods [10], [11], [14], heuristic methods [12], and hybrid algorithms [15]. As for mathematical optimization methods, it can formulate PDS planning problems into tractable models and solve them with efficient off-the-shelf software.…”

“…Besides, only one investment of the candidate alternatives is allowed for each device throughout the planning horizon. Constraint (10) ensures that the investment for PVs, WTs, PtHs, and HSs will exist if it has been installed previously, while constraint (11) imposes the upper bounds on them at each planning stage. Constraints (12) and (13) restrict that the transformers and power lines cannot be installed on the attached substations that have not been built.…”

“…In practical engineering, the long-term IPDHS co-planning problem will face load growth uncertainties during the planning horizon [11], [28]. To address this problem, a multistage stochastic model with non-anticipativity constraints [29], [30] is utilized in this paper to obtain flexible investment decisions to resist long-term uncertainties.…”