The economics, reliability and carbon efficiencyof the hybrid system microgrid (HMS) often conflict; hence,reasonable design of the initial microgrid size is important. Wepropose an improved two-archive many-objective evolutionaryalgorithm (TAMaEA) based on fuzzy decisions to solve theoptimal sizing problem for an HMS. For the HMS, the costof power generation, loss of power supply probability, pollutantemissions, and power balance are considered objective functions.For the proposed algorithm, we employ two archives withdifferent diversity selection strategies to balance convergence anddiversity in the high-dimensional objective space. In addition, afuzzy decision method is proposed to further help decision makersobtain a solution from the Pareto front that optimally balanceseach objective. The effectiveness of the proposed algorithm insolving the HMS size optimization problem is investigated forthe case of Yanbu, Saudi Arabia. The simulation results provethat compared with the two-archive evolutionary algorithm forconstrained many-objective optimization (CTAEA), the improveddecomposition-based evolutionary algorithm (IDBEA) and theclustering-based adaptive many objective evolutionary algorithm(CAMOEA), the proposed algorithm can optimize the size ofthe system; the system cost is reduced by 7%, 13%, and 21%, respectively.

In a deregulated energy market, voltage security (VS) is one of the major concerns, as it improves the loadability limits, loading profiles while concurrently reducing power loss. Further, voltage dependent loads can operate at high efficiency at rated voltage. Therefore, power utilities have to explore options of reconfiguration to secure the voltage level under frequently changing operating conditions. In this study, an efficient heuristic and meta‐heuristic (harmony search) approach for reconfiguration is proposed by imposing VS. Two indices namely node voltage security index (NVSI) and node voltage quality index are developed for aggregated improvement in node voltages. Moreover, efficient methodologies for identification of new tie‐lines, network radiality and the load flow solution are also presented. The effectiveness of the proposed index and the methodology is tested for reconfiguration of various distribution systems and the results are obtained with reduced computational efforts.

Practically, loads are found to be voltage dependent and reconfiguration in distribution systems changes the node voltage profile. Hence reconfiguration affects the load behaviour. In this scenario, the traditional approach of defining energy efficient operation as mere loss minimisation does not give truly energy efficient results. Therefore this study defines energy efficiency as a multi‐variable function in terms of energy efficiency defining parameters and develops an energy efficiency performance index, in order to identify an energy efficient configuration. The proposed approach of reconfiguration gives more flexibility to utilities in operating the distribution system with improved power quality and reliability, and enables them to actively participate in a competitive deregulated environment. In this study, voltage dependent loads are modelled in the form of load combinations to represent the real world loads at a bulk delivery point of the distribution system.

An interconnected power system requires specific restrictions to be maintained for frequency, tie-line power, and the terminal voltage of synchronized generators to avoid instability. Therefore, frequency stability and voltage regulation issues are covered individually and jointly in the current research work. Initially in test system 1, automatic generation control (AGC) investigations are done on two interconnected systems with thermal plants and electric vehicles in one area and distributed generation and electric vehicles in other area. The automatic voltage regulator (AVR) problem alone is chosen for investigation in test system 2. The third test system addresses the combined AGC and AVR issues. The performance of the fractional-order tilt-integral-derivative (TID) controller is compared with that of a widely used proportional integral derivative (PID) controller in all three test systems studies. The findings demonstrate better performance of the TID controller than PID in terms of providing superior dynamic metrics, such as low peak overshoots, undershoots, and settling time, as well as decreased oscillations amplitudes. Additionally, TID performs better than PID despite randomized load disturbance, system non-linearities, and time delays in AGC and the combined AGC and AVR problem. The PSO-tuned TID controller is insensitive to variation in load damping factor and time constants of the AVR system. Finally, the results are validated by an OPAL-RT 4510 real-time digital simulator.

Loads in distribution system changes with time and weather conditions. With the change in loading conditions power utilities usually reconfigured the network topology for optimal operation. In existing literature, network reconfiguration is performed with constant power load models. However, in real time operation, load characteristics changes with system voltage profile differently. In load modeling, the voltage dependent load has their different voltage exponents. The variation in voltage exponents with change in loading further depends upon the type of load. Therefore, the optimal configuration obtained for specific loading may not be optimum if implemented with change in loading conditions. In this paper, different load models are considered and in order to obtain the optimal configuration harmony search algorithm (HSA) is used. The results are demonstrated on an IEEE 33-node distribution system.