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Curtailable loads (CLs) are regarded as one of the last lines of defence to maintain the security and stability of power systems. Nevertheless, if organised carefully, they can also be exploited as preventive security procurement measures for power systems. This is especially true for heavily loaded power systems in which the normal control schemes are already exhausted. In this study, a new power market approach is proposed to utilise CLs' potential in ensuring voltage stability margin (VSM) for heavily‐loaded power systems. The proposed method aims to provide a mechanism to engage CLs as active players in the power market, and hence, minimise the disruptive effect of the load curtailment. Next, CLs participation in the power market is utilised to minimise the cost of achieving a desired level of VSM, at normal and N − 1 contingency conditions, in a preventive manner. The most efficient load curtailment and power generation pattern are determined, using a modified particle swarm optimisation algorithm, to minimise the system's total cost, while meeting grid's VSM requirements. The simulation results verify that the desired level of VSM can be effectively obtained using the proposed approach, with much less operational cost compared to the established methods. [ABSTRACT FROM AUTHOR]

High intermittency in today's renewable-rich distribution systems, and the prohibitive cost of upgrading the system infrastructure, has rendered voltage instability a real concern for heavily loaded systems. The voltage instability of distribution systems can spread to the corresponding transmission grid, as proven by real-life incidents. Recent advances in energy storage systems (ESSs), however, have offered a viable means of enhancing the reliability and robustness of power systems. In this paper, the optimal placement, sizing, and operation of ESS devices in wind-intensive distribution power systems are studied. The objectives of this paper are to minimize the ESS size (power and energy), required to ensure a desired voltage stability margin (VSM), and to minimize the reactive power loss and reactive power import from the upstream network. Wind uncertainty has been accounted for through a risk-based stochastic optimization framework. Besides, active network management (ANM) tools, such as the tap position of on-load tap changers, modelled by using a new method, and reactive power capabilities of both ESS devices and wind farms, are used as additional means to reduce the required ESS size. The results show that the required ESS significantly increases with increase in the desired VSM. Nevertheless, the increase can be considerably curtailed by using risk-based VS constraints and ANM tools. [ABSTRACT FROM AUTHOR]

High intermittency in today's renewable‐rich power systems, and the prohibitive cost of upgrading the network infrastructure along with the load growth, has rendered voltage instability an imminent threat for many power systems. This necessitates faster and more efficient ways of identifying the voltage stability (VS) limits, associated with specific bifurcation points of power system model, which are suitable for real‐time applications. To date, continuation power flow (CPF) has conventionally been used to identify bifurcation points of power systems, through plotting power–voltage (P –V) curves. However, existing CPF methods are complex and computationally demanding. To tackle this issue, in this study, accurate identification of both saddle‐node and limit‐induced bifurcation points of power systems is carried out by using a new and efficient continuous power flow algorithm, in which all the complexities associated with the existing CPF methods are relaxed. Low execution time (as compared to the existing CPF methods), ease of implementation, and automated applicability, make the proposed algorithm highly suitable for fast and accurate VS assessment of renewable‐rich, uncertain, power systems. Experiments, carried out on several different size power systems, verify that the proposed method can be effectively used to identify the VS limits of practical real‐life power systems, despite its ease of implementation and lower computational burden. [ABSTRACT FROM AUTHOR]