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Consultant- Power Markets
Consultant- Power MarketsCouncil on Energy, Environment and Water (CEEW) • New Delhi, India
Consultant- Power Markets

Consultant- Power Markets

Council on Energy, Environment and Water (CEEW) • New Delhi, India
3 days ago
Job description

Purpose

The Power Markets team at CEEW is seeking a Consultant to join our dynamic team and expand ongoing research on building evidence for accelerated renewable energy (RE) offtake in the power grid, as well as the corresponding need for building evidence on delivering reliable power through renewables. The role will include conducting literature reviews of statistical and advanced models used to forecast demand and RE power for the short and medium term, identifying the gaps and identifying integrated approaches to minimise the uncertainty for renewables. This position requires a strong demonstrable experience in time series analysis, data science and machine learning models, with an ability to apply real-world scenarios. The candidate should also be informed of the basics of power system scheduling and operations so that he / she / they can understand and support the change in business-as-usual approach towards forecasting and scheduling power generators

Job duties and accountabilities

Primary responsibilities

Research

  • Review various approaches, including data requirements, tools and techniques used in Indian

states, industries and globally for short (day / week-ahead) and medium (seasonal) forecasting

for solar, wind, and demand

  • Consultations on the existing forecasting methods and challenges faced by developers,
  • Renewable Energy Implementation Agencies, and key industry players in the sector

  • Identify integrated approaches to improve the predictability of renewables and power demand
  • Assist the team in testing the implications and readiness of the generation and demand
  • uncertainties in the power sector using grid modelling tools

  • Support the team in utilising statistical techniques and metaheuristic algorithms to support the
  • RE integration strategies, while diversifying the risk of uncertainty

  • Stay informed about developments in the technological and regulatory landscapes related to
  • renewable energy and demand forecasting, as well as operational planning and scheduling

    practices.

    Programme Assistance

  • Assist with project implementation, including preparing tools, presentations, factsheets, reports
  • and other communication material.

  • Contribute policy memos and technical documentation as part of the research team
  • Accompany team members for meetings with other stakeholders, and prepare formats for data
  • collection.

    Selection Criteria

    Qualification

  • Completed a Master’s or doctorate degree with a specialisation in the application of data science
  • or machine learning in power systems, energy systems, renewable energy technologies, or

    related fields

  • Demonstrable experience of at least 2 years in data and time series models will be
  • advantageous.

    Key Skills

  • Strong ability to review, analyse statistical and probabilistic models widely used in time series
  • analysis to forecast solar, wind and demand

  • Proficiency in using Python libraries, linear and non-linear optimisation techniques and MS Excel
  • Prior experience in conducting a vast literature review on numerical mathematical models
  • Ability to learn new tools to manage, process and drive insights from acquired data
  • Prior understanding of the power sector schedule and operations, and relevant policy and
  • regulatory environment

  • Ability to effectively work in an interdisciplinary team while being able to independently drive
  • research with minimum assistance when time demands

    CEEW operates in a dynamic environment, and the candidate will be required to show flexibility in

    undertaking a variety of tasks.

    Compensation

    Competitive compensation – commensurate to the experience and matching the best of standards

    adopted by industry or other similar organisations for similar roles.

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