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Abstract: Power demand forecasting is of vital importance to the management and planning of power system operations which include generation, transmission, distribution, as well as system’s security analysis and economic pricing processes. This paper concerns the modeling and short-term forecast of daily peak power demand in the state of Victoria, Australia. In this study, a two-dimensional wavelet based state dependent parameter (SDP) modelling approach is used to produce a compact mathematical model for this complex nonlinear dynamic system. In this approach, a nonlinear system is expressed by a set of linear regressive input and output terms (state variables) multiplied by the respective state dependent parameters that carry the nonlinearities in the form of 2-D wavelet series expansions. This model is identified based on historical data, descriptively representing the relationship and interaction between various components which affect the peak power demand of a certain day. The identified model has been used to forecast daily peak power demand in the state of Victoria, Australia in the time period from the 9th of August 2007 to the 24th of August 2007. With a MAPE (mean absolute prediction error) of 1.9%, it has clearly implied the effectiveness of the identified model. [Copyright &y& Elsevier]

As rooftop solar PVs installed by residential customers penetrate in low voltage distribution network (LVDN), some issues, e.g. over/under voltage and unbalances, which may undermine the network's operational performance, need to be adequately addressed. To mitigate unbalances in LVDN, phase-switching devices (PSDs) and static var compensator (SVC) are two equipment that is cost-effective and efficient. However, most existing research on operating PSDs is based on inflexible heuristic algorithms or without considering the network formulation, which may lead to strategies that violate operational requirements. Moreover, few pieces of literature have been reported on mitigating unbalances in LVDN via SVC and PSDs together. This paper formulates the decision-making process as a mixed-integer non-convex programming (MINCP) problem after developing an SVC model for dispatch purpose. Compared with existing work, the proposed method aims at minimizing current unbalance based on their phasor values and takes the network's operational requirements into account. To efficiently solve the challenging problem, the MINCP is reformulated as a mixed-integer second order-cone programming (MISOCP) problem based on either exact reformulations or accurate approximations, making it possible to employ efficient off-the-shelf solvers. Simulations based on two modified IEEE systems and a practical Australian LVDN demonstrates the efficiency of the proposed method in mitigating unbalances in LVDN. [ABSTRACT FROM AUTHOR]