A Dynamic Programming Approach to Multi-period Planning of Isolated Microgrids

Martin, Benoı̂t; Jaeger, Emmanuel De; Glineur, François; Latiers, Arnaud

doi:10.1007/978-3-319-51795-7_8

Cited by 1 publication

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“…They conclude that properly sized and located DERs provides high reliability . Popovi and Popovi and Martin et al are some of the other works that solve multi‐period planning problems of distributed generations with the use of DP algorithms. These works assessed the voltage stability of the system during the integrations of the DG units though static voltage stability. (vii)Quadratic programming (QP): QP is the optimisation of a quadratic objective function subject to some linear constraints.…”

Section: Optimisation Algorithms For Dg Allocation Planningmentioning

confidence: 99%

Towards maximising the integration of renewable energy hybrid distributed generations for small signal stability enhancement: A review

2020

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Summary Integrating renewable energy hybrid distributed generation (REHDG) into distribution network systems (DNSs) has become increasingly important because of various technical, economic, and environmental advantages accruing from it. However, the output power of REHDGs from photovoltaic (PV) and wind is highly variable because of its dependency on intermittent parameters such as solar irradiance, temperature, and wind speed. Such variability of generated power from large‐scale REHDGs or load introduces small signal instabilities (oscillations). Meanwhile, different locations of integration and sizes of REHDGs in the DNS affect the system oscillation modes by either improving or depriving the small‐signal stability (SSS) of the network. Consequently, a significant number of research has been conducted on the planning of optimal allocation of REHDGs in DNS. In this regard, this paper reviews the existing planning models, optimisation techniques, and resources' uncertainty modelling employed in REHDGs allocations in terms of their capability in obtaining optimal solutions and enhancing SSS of the system. Planning models with optimisation algorithms are evaluated for modelling renewable resource uncertainties and curtailing SSS variables. Research works on planning of optimal allocation of these generations attain minimum cost, but were unable to satisfy the SSS requirements of the system. The existing models for the planning and design of optimal timing, sizing, and placement of REHDGs will need to be improved to optimally allocate REHDGs and satisfy the SSS of the DNS after the integration.

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Section: Optimisation Algorithms For Dg Allocation Planningmentioning

confidence: 99%