In this study, a new meta-heuristic optimization method inspired by the behavioral choices of animals and hunger-driven activities, called hunger games search (HGS), is suggested to solve and formulate the single- and multi-objective optimal power flow problem in power systems. The main aim of this study is to optimize the objective functions, which are total fuel cost of generator, active power losses in transmission lines, total emission issued by fossil-fueled thermal units, voltage deviation at PQ bus, and voltage stability index. The proposed HGS approach is optimal and easy, avoids stagnation in local optima, and can solve multi-constrained objectives. Various single-and multi-objective (conflicting) functions were proposed simultaneously to solve OPF problems. The proposed algorithm (HGS) was developed to solve the multi-objective function, called the multi-objective hunger game search (MOHGS), by incorporating the proposed optimization (HGS) with Pareto optimization. The fuzzy membership theory is the function responsible to extract the best compromise solution from non-dominated solutions. The crowding distance is the strategies carried out to determine and ordering the Pareto non-dominated set. Two standard tests (IEEE 30 bus and IEEE 57 bus systems) are the power systems that were applied to investigate the performance of the proposed approaches (HGS and MOHGS) for solving single and multiple objective functions with 25 studied cases using MATLAB software. The numerical results obtained by the proposed approaches (HGS and MOHGS) were compared to other optimization algorithms in the literature. The numerical results confirmed the efficiency and superiority of the proposed approaches by achieving an optimal solution and giving the faster convergence characteristics in single objective functions and extracting the best compromise solution and well-distributed Pareto front solutions in multi-objective functions.

Optimal power flow (OPF) represents one of the most important issues in the electrical power system for energy management, planning, and operation via finding optimal control variables with satisfying the equality and inequality constraints. Several optimization methods have been proposed to solve OPF problems, but there is still a need to achieve optimum performance. A Slime Mould Algorithm (SMA) is one of the new stochastic optimization methods inspired by the behaviour of the oscillation mode of slime mould in nature. The proposed algorithm is characterized as easy, simple, efficient, avoiding stagnation in the local optima and moving toward the optimal solution. Different frameworks have been applied to achieve single and conflicting multi-objective functions simultaneously (Bi, Tri, Quad, and Quinta objective functions) for solving OPF problems. These objective functions are total fuel cost of generation units, real power loss on transmission lines, total emission issued by fossil-fuelled thermal units, voltage deviation at load bus, and voltage stability index of the whole system. The proposed algorithm SMA has been developed by incorporating it with Pareto concept optimization to generate a new approach, named the Multi-Objective Slime Mould Algorithm (MOSMS), to solve multi-objective optimal power flow (MOOPF) problems. Fuzzy set theory and crowding distance are the proposed strategies to obtain the best compromise solution and rank and reduce a set of non-dominated solutions, respectively. To investigate the performance of the proposed algorithm, two standard IEEE test systems (IEEE 30 bus IEEE 57 bus systems) and a practical system (Iraqi Super Grid High Voltage 400 kV) were tested with 29 case studies based on MATLAB software. The optimal results obtained by the proposed approach (SMA) were compared with other algorithms mentioned in the literature. These results confirm the ability of SMA to provide better solutions to achieve the optimal control variables.

The microgrids can function as a single controllable system in a grid-connected or islanded operation mode. The transition from grid-connected mode to islanded mode can result in microgrid excess generation or demand, which must be spilled or curtailed. This paper proposes an optimization model for optimizing the microgrid operations accounting for distributed energy resources (stochastic generation and time-varying demand), as well as microgrid operation constrains. The objective is to minimize the microgrid operational costs considering the classical generation capacities and exchanged power with the upstream grid, as well the operational constraints. The analyzed microgrid is composed of a thermal engine, a photovoltaic system, an electrochemical storage system, critical and interruptible loads. The deterministic and stochastic optimization model were formulated, and each optimization model is tested in various case studies considering the different operational states of the microgrid.

A techno-economic study of a hybrid PV/Battery/Grid-connected system for energy supply is carried out in this paper to respond to the problem of electrical load shedding. An optimal design of the system is realized thanks to a double-objective optimization based on a proposed operational strategy of the system and on Firefly Algorithm (FA). The system is designed for household energy supply in three different towns of the northern part of Cameroon. For different LPSP (Loss of Power Supply Probability), the double objective simulation determines the optimal configurations of the system with their related cost. The optimal and reliable PV/Battery subsystem configuration corresponding to LPSP of 0% obtained for one household is composed for the towns of Maroua and Garoua by 8 PV modules and a battery capacity of 11.304 kWh with 1-day autonomy. For the town of Ngaoundéré, it is composed by 10 PV modules and battery capacity of 11.304 kWh with 1-day autonomy. The related investment costs corresponding to these optimal configurations are USD 6225.6 for Maroua and Garoua and USD 7136.6 for Ngaoundéré. The great proportion of the monthly energy demand consumed by the load is provided by the PV/Battery system. The monthly PV/Battery energy represents 60.385% to 72.546% of the load consumed in Maroua, 58.371% to 71.855% of the load consumed in Garoua, and 61.233% to 74.160% of the load consumed in Ngaoundéré. The annual main grid energy consumed for one household is 1299.524 kWh in Maroua, 1352.818 kWh in Garoua, and 1260.876 kWh in Ngaoundéré. Moreover, the annual PV/Battery energy consumed for one household is 1580.730 kWh in Maroua, 1527.815 kWh in Garoua, and 1619.530 kWh in Ngaoundéré. Thus, the PV/Battery system, by reducing the grid energy consumption, acts as the principal source of energy of the whole system. The time the PV/Battery/Grid-connected system needs to be economically more advantageous than the electric grid without blackouts is 17 years for Maroua and 18 years for both Garoua and Ngaoundéré. It is demonstrated in this paper that the hybrid PV/Battery/Grid-connected system is an effective solution for electrical load shedding in sub-Saharan zones. This system is very useful for grid energy consumption reduction. For a long-term investment, the PV/Battery/Grid-connected system is more economically advantageous than the main grid alone.