Equilibrium-Inspired Multiple Group Search Optimization With Synergistic Learning for Multiobjective Electric Power Dispatch

Hierarchical energy and frequency security pricing in a smart microgrid: An equilibrium-inspired epsilon constraint based multi-objective decision making approach

“…The drawback of fuzzy based decision making approaches is that the trade-off between competitive objective functions is not considered and it stands on experience in the construction of membership functions. In this paper, owing to the analogy between the various objective functions in the multi-objective optimization to a set of non-cooperative players in the game theory, the concept of Pareto optimality selection is proposed to be transformed to a Nash equilibrium point derivation on the basis of the game theory [33]. Thus, each objective function is modeled as a non-cooperative player in the proposed game theory framework in which Nash equilibrium point will be optimized subject to some probability and rationality constraints according to the trade-off between various points in the Pareto front space.…”

A wolf pack hunting strategy based virtual tribes control for automatic generation control of smart grid

“…Based on the game theory, many advanced algorithms have been employed to obtain system equilibriums, such as correlated-Q (CE-Q) [25], asymmetric-Q [26], and their modifications [24]. Author's previous work on the single-agent reinforcement learning (SARL) and MAS-SG has demonstrated that an optimal AGC can be achieved when the agent number is relatively small [27][28][29][30][31][32][33][34][35]. However, multi-equilibrium may emerge as the agent number increases, which inevitably consumes longer time resulted from the extensive online calculation of all system equilibriums, and may even lead to a severe system stability collapse.…”

“…However, multi-equilibrium may emerge as the agent number increases, which inevitably consumes longer time resulted from the extensive online calculation of all system equilibriums, and may even lead to a severe system stability collapse. However, the aforementioned literatures [23][24][25][26][27][28][29][30][31][32][33][34][35] only calculated an optimal total power reference, which is then dispatched through a fixed proportion to the adjustable capacity. In general, they may not obtain an optimal dispatch due to the static optimization.…”

Improved group search optimization method for optimal power flow problem considering valve-point loading effects

“…In [34], a similar GSOMP algorithm with the modified coordinate transformation and circular shifting operator was proposed for dynamic economic emission dispatch. In [35], Zhou et al proposed a Nash equilibrium-inspired multiple group search optimizer with learning automata based synergistic learning for multi-objective economic dispatch. However, little research has been focused on the OPF problem.…”