Optimal Reduction of electrical Loads Based on Priorities Developed Using a Genetic Algorithm

Abstract

Most developing countries are now working to combat imbalances between power generation and load demand. In such situations, load shedding schemes have been implemented frequently as rapid solutions for unbalanced conditions to protect networks from collapsing and to sustain stability. The conventional methods of load shedding disconnect loads without considering their priorities. In this work, a logarithmic reduction method is thus proposed to reduce loads according to the priority and criticality. A Reduction Matrix is introduced as a tuning factor scaled to the size of the network, and the paper thus presents an optimisation tool based on Genetic Algorithms, developed in MATLAB, that can be applied to minimise the error between the amount of load to be reduced and the actual load reduced in electric power systems. The proposed algorithm was tested on a practical data system sample as provided by the Iraqi Ministry of Electricity from the control center of the Iraqi national grid in Baghdad, and was shown to offer optimal load reduction with reduce error, which is necessary to eliminate the impact of load reduction in electrical networks on critical loads when total demand cannot be supplied. The simulation results thus support the effectiveness and practicality of the applied method, paving the way for its possible application in power systems.

Application-Based Simulations for Diagnosing the Power Quality When Changes in Load’s Power on Each Bus as an Analogy of the Steady-State Stability Phenomena

“…Depending on the needs of the user, today's linked power networks may supply a range of loads. Naturally, these demands change continually, which causes the system's loading to vary and has a variety of effects [26,27]. Variation in loading has certain negative impacts, with the following listed as the most notable, namely (i) costlier power generation, (ii) complex system control, (iii) a need for more equipment, and (iv) higher losses are just a few of the consequences [27][28][29].…”

“…Naturally, these demands change continually, which causes the system's loading to vary and has a variety of effects [26,27]. Variation in loading has certain negative impacts, with the following listed as the most notable, namely (i) costlier power generation, (ii) complex system control, (iii) a need for more equipment, and (iv) higher losses are just a few of the consequences [27][28][29]. The reduction or addition of power due to the release or inclusion of a number of type and range of loads [25,[28][29][30].…”

“…Buses #2 and #3 are noted as generation buses (voltage control buses, P À V buses), while bus #4 is noted as a load bus (P À Q bus). The next phasing is in the form of making algorithms and compiling MATLAB-based syntax, a number of simulations of the steady-state stability phenomenon with initial assumption values, and making conditions for the steady-state stability phenomenon through changes in power on the load on each bus [26,27].…”