A Novel Optimization Framework for the Least Cost Generation Expansion Planning in the Presence of Renewable Energy Sources considering Regional Connectivity

Abstract

Generation expansion planning (GEP) is a vital step in power system planning after the load forecast. The integration of renewable energy sources makes the GEP problem less reliable due to intermittent nature. The concept of exploiting the energy sources of multiple regions and cross-border power exchange is gaining immense attention in energy policy strategic planning. The aspect of regional connectivity has been incorporated in the least cost GEP by proposing two new models for large-scale power systems as intra-regional and inter-regional GEP. Intra-regional GEP simulates the composite planning for multiple zones of a region, whereas inter-regional GEP accommodates the energy sources of multiple regions and promotes the import–export of electrical power across the border. To pursue the least cost GEP, a novel meta-heuristic GEP optimization framework has been proposed in this paper. The proposed GEP optimization framework is biogeography-based optimization employing the correction matrix method-with-indicators (BBO-CMMI). In BBO-CMMI, a new parallel constraint handling approach called the correction matrix method-with-indicators (CMMI) has been developed. The proposed optimization framework is applied to reliability-constrained and emission-constrained GEP problems from the literature. The proposed framework shows promising results in terms of the least cost and runtime as compared with the results given by recent approaches presented in the literature. Similarly, the framework outperforms to optimize the large-scale power systems for intra-regional and inter-regional GEP. The applicability of the proposed approach has also been evaluated by applying to a real case study of Pakistan’s power system to devise the feasible generation expansion plan .