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Energy hubs play an important role in implementing the integrated energy system as an interconnection point between various energy components and networks. Energy networks also influence the management of the energy hubs. Therefore, the problem of optimal operation of the energy hubs and energy networks is modeled as a bi-level optimization problem in this paper. In the proposed bi-level model, the...
This paper presents an evolutionary algorithm, reference point based multi-objective group search optimizer using non-dominated sorting approach (r-NSGSO), for optimal power flow problem with multiple objectives. First, the six objectives of optimal power flow are reduced to two objectives which represent the secure and economic indices, respectively. The r-NSGSO integrates the non-dominated sorting...
This paper focuses on implementing a dimensional Q-learning (DQL) for solving reactive power optimization with discrete control variables. The proposed algorithm applies the traditional Q-learning to search the feasible region dimensionally, so that the memory amount of each agent can be largely reduced. Meanwhile, the safety margin of voltage amplitude and reactive power output of generators are...
This paper proposes a multi-objective optimization method for solving the Security-Constrained Optimal Power Flow (SCOPF) problem with the consideration of solar farm integrated and distributed load variations in the grid. In this scheme, the power generated by solar farm is affected by the weather uncertainty. The dispatch objectives are formulated to minimize fuel cost and emission simultaneously...
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