Strategic energy planning has become the central focus of energy developments and sustainability in pursuit of energy security and reliability. Energy policy reform is the key framework in shaping the vision and roadmap to energy transition. It provides a strategic direction for economic development, job creation and energy investments. In addition, the impact of effective and strategic energy planning has the potential to ensure successful implementation of such frameworks for energy developments. To achieve this, an integrated approach which comprises of tools, techniques, framework and technologies must be deployed to ensure adequate energy value chain. Advance technologies optimizing artificial neural networks has responded to potential renewable energy risks by deploying modern intelligence to risk response and risk mitigations. Technological developments in artificial intelligence have not only brought capabilities of control and monitoring but has enhanced the speed, reliability and predicting modelling. Therefore, integrated planning approach to renewable energy must incorporate both energy framework and capabilities of technological advancement for future outlook. The reason for this is to ensure sustainability, economic growth, energy security and energy investments. The data was analyzed through qualitative and quantitative research methods. The results obtained from the proposed methodology shows that policy reform is the key driver and backbone of energy development and critical factor for social, environmental and economic growth. Furthermore, the deployment of advanced technologies such as artificial neural networks have enhanced the preventative and predictive models and improves grid reliability and stability. For example, the optimization of AI technologies plays a critical role in generation and distribution networks by significantly mitigating the impacts of intermittency through deploying sophisticated techniques of machine learning, deep learning and data acquisition generated by renewables to improve energy storage, decision making and reducing carbon emission.

Keywords

Energy Planning, Renewable Energy Transition, Artificial Intelligence, Decarbonization, Policy Optimization