Simultaneous expansion of the electrical and thermal energies collected with conventional expansion options is scrutinised. A robust, bio-inspired evolutionary optimisation method is proposed, to handle the complex expansion planning of a system consisting of both electrical and thermal forms of energy. Rewiring, network reconfiguration, installation of new lines and also new electrical and thermal generation units are considered as the traditional alternatives in expansion planning. To solve the problem, overall generation requirements of a network are assigned along the planning horizon. The allocation problem is formulated as a mixed-integer non-linear programming problem that minimises the overall system cost owing to generation capacity among the grid nodes and the newly added or upgraded lines.
The performance of the original shuffled frog leaping (SFL) optimisation algorithm is advanced to overcome the complexity of the proposed expansion planning problem. Two modification steps were added to the original SFL technique to enable the proposed modified SFL algorithm to extricate from local minima. The two modification phases pledge a fast convergence rate by achieving a rapid adaptive algorithm, besides a better diversification which is the key to extricate from local minima. The efficacy and robustness of the proposed methodology are verified by applying the method to two modified standard test systems.