A Suite of Intelligent Tools for Early Detection and Prevention of Blackouts in Power Interconnections

Hybrid intelligent technique for voltage/VAR control in power systems

“…Thus, we presented the classic optimisation problem as a multioutput regression problem, which aims to simultaneously predict multiple real-valued output/target variables. The task is to train a multi-target regression model from data set S = x (1) , y (1) , …, x (N) , y (N) calculated using the function h that assigns the vector x, vector y of d target values to each instance:…”

“…where D is the size of input vector of local L-indexes, L and M is the size of the output vector ΔQ, such that, in matrix notation ΔQ = G(b (2) + W (2) (s(b (1) where b (1) , b (2) -bias vectors; W (1) , W (2) -weight matrices and G, sactivation functions The vector g(x) = Φ(x) = s(b (1) + W (1) x) constitutes the hidden layer. This operation can be applied to g(x) itself, but with different parameters (different biases and weights).…”

“…For the high-quality training of deep ANNs, there is a need for big data from high-performance equipment, for example, powerful computers with graphic processors. A quasi-dynamic simulator of power system behaviour [1], developed in Matlab using the PSAT package, was used in the study for the generation of large volumes of data in topology-operation conditions.…”

“…The main elements are various local automated systems providing an automatic sharp increase in reactive power generation in case of short circuits (excitation forcing of automatic excitation regulator and FACTS devices), and automatic switching of RPSs and/or disconnection of consumers in the event of a sharp voltage decrease. However, traditional ways of dealing with voltage collapse may be untimely, or ineffective (correction of excitation force, use of emergency control systems) and in some cases can even aggravate the situation (for example when transformer ratio is controlled undervoltage collapse) [1,2].…”

Optimal Reactive Power Dispatch Using a Chaotic Turbulent Flow of Water-Based Optimization Algorithm

“…There are three main objectives of ORPD, which include reducing and minimizing the active power losses, the voltage deviation values, and the stability index. Researchers have studied several problems related to the power systems, including the security assessment of online power systems [3], a two-stage active and reactive power coordinated optimal dispatch for an active distribution network, considering load flexibility [4], the early detection and prevention of blackouts in power interconnections [5], OPF [6], and economic emissions dispatch [7].…”