Multi-objective Integrated Power System Expansion Planning With Renewable Energy Constraints Using Adaptive Hybrid Meta-heuristic Approach

Abstract

Multi-objective Integrated Power System Expansion Planning with Renewable Energy Constraints using Adaptive Hybrid Meta-Heuristic Approach Federal and state government agencies as well as utilities have been using optimization models in evaluating their power system expansion plans. In the recent past, the separation of generation and transmission expansion optimization processes has caused many challenges, which have forced network planners and researchers to reconsider going back to the integrated planning approach. The available integrated Generation and Transmission Expansion Planning (GTEP) formulations are majorly based on DC power flow models, which are usually over simplified leading to less accurate or infeasible expansion results. In this research work, the GTEP problem is formulated based on the more accurate and reliable AC-power flow representation while considering optimal penetration of intermittent renewable energy sources. The complexity, increased dimensionality and non-linearity of the formulated optimization problem required a powerful solution methodology. To solve this, an adaptive hybrid meta-heuristic approach was formulated and tested using standard benchmark functions and selected constrained engineering optimization problems. Transmission Constrained Generation Expansion Planning (TC-GEP), Multi-Objective Dynamic GTEP (MODGTEP) and Multi-Area MODGTEP (MAMODGTEP) optimization problems have been formulated and solved applying standard test networks frequently used by previous researchers in this area (IEEE 6-b�������� and Ga��������e������������ ����e�������� ����������������em����). The problems were simulated in MATLAB R2015b. Compared to other existing methods, the proposed methodology reduced total TC-GEP and MODGTEP costs by 4-5% and 7% respectively. Inclusion of N-1 contingency criterion in the optimization increased the TC-GEP and MODGTEP costs by 16% and 9% respectively. The optimal vRES shares in TC-MOGEP problem were 6.5% and 4.5% for installed capacity and generated energy mix respectively while for MODGTEP the shares increased to 20.2% and 12.8% respectively. Optimal vRES penetration in TC-MODGEP problem reduced the overall costs by approximately 19%. Up to 28% and 17% annual vRES penetration levels in installed capacity and energy mix were achieved for MAMODGTEP. Averagely, the optimized vRES penetration level resulted to a 55% reduction in CO2 emissions.