Data Scientist (Forecasting) Full-time

Research Fellow In Distribution Network Optimization

Established in 2010, the Energy Research Institute @ NTU (ERI@N) is a pan-university research institute that focuses on systems-level research for tropical megacities. It performs translational research that covers the energy value chain from generation to innovative end-use solutions, motivated by industrialization and deployment. ERI@N has multiple Interdisciplinary Research Programmes which focus on translational Research, Development & Deployment which focus on specific area of the energy value chain, and a number of Living labs and Testbeds which facilitate large scale technology deployment enabling validation and demonstration of real-world applications.

The Multi-Energy System & Grids Team is looking for a Research Fellow in distribution network optimization and flexibility planning using distributed energy resources. The successful candidate will develop and implement a flexibility planning tool for electrical distribution grids. The methodology used shall consider behind-the-meter installations at the consumer side and installations by the utility, considering different scenarios, with the goal of achieving grid reinforcement and deferring capital expenditure. The tool would also assist in computing the technical parameters related to the contractual configuration through which those who possess the distributed energy resources can be engaged.

Key Responsibilities:

• Power system planning, analysing impact of renewable energy and storage on electrical distribution systems, optimization under uncertainty, and flexibility planning using distributed energy resources (DERs).
• Design & develop optimization algorithms/tools to plan the deployment of DERs such as energy storage systems (ESS), photovoltaic generations (PV), electric vehicle charging stations (EVCS), flexible building loads, in view of the advanced utility grid operations, ancillary services, and the changes in distribution network.
• Mathematical modelling of the system-level and device-level constraints of distribution networks with DERs, and applications of stochastic programming/approximate dynamic programming approach. Implementation of distribution power-flow methods for DER-rich networks and practical modelling of flexibility of the DER assets and the network, considering the operating envelopes and probabilistic power-flows. Modelling of DER-based integrated grid ancillary services that maintain reliability and stability (e.g., voltage/power management, fast demand response, peak demand management, network restoration service, and electric vehicles-based services (V2G/G2V)).
• Constrained optimization problem formulations & solution techniques: convex optimization, dynamic programming, NLP, MILP and MINLP.
• Decomposition and relaxation techniques to tackle computational problems in distribution grid planning. Engage the industry research collaborator in the guided development of the flexibility planning and contract configuration.
• Conduct hardware-in-the-loop (HIL) simulations using OPAL-RT solutions.
• Proposal development & grant writing

Job Requirements:

Core Competencies

• Power System Analysis and modelling
• Renewable Energy Integration & Distributed Energy Resources Control & Coordination
• SMART Grid Technologies, Hybrid Systems & microgrids
• Power Electronics & Control System

Technical Proficiency

• Power Flow Analysis (AC/DC), Fault & Stability analysis, grid planning & expansion modelling
• Skilled in tools such as Python, R, MATLAB/Simulink, DlgSILENT PowerFactory, PSCAD, PSS, OpenDSS, HOMER Pro, etc
• MPC, Real-time control, economic dispatch, DR Strategies

Communication Skills: Capable of translating technical insights into actionable recommendations for diverse stakeholders.

Problem-Solving: Innovative and solution-oriented approach to addressing network challenges and improving model accuracy.

Collaboration & Teamwork: Experience working in interdisciplinary teams and engaging with engineers, analysts, and policy experts.

Attention to Detail: Precision in data handling, model validation, and documentation.

Project Management: Ability to manage multiple research tasks, meet deadlines, and contribute to long-term strategic goals.

Continuous Learning: Commitment to staying updated with the latest forecasting techniques, energy technologies, and industry trends.

Qualification

• Education: Ph.D. degree in Electrical/Computer Engineering, specialized in Power Systems/Renewable Energy Planning/Optimization
• Experience: 5-8 years of experience

We regret to inform that only shortlisted candidates will be notified.