High Performance Grids and the Significance of Strategic Project Development

By Amir Kalantari

Unlike consumer products that can be designed, manufactured and operated with a high degree of certainty, the only certainty in governing the very same process for power grids is the uncertainty. As a result, while the lifecycle of consumer products can potentially be engineered for maximum value, it is overly ambitious to expect so for the power grid, one of the most critical and capital-intensive types of infrastructure ever designed and built on the planet. Why? The sheer scale and complexity, the large number of stakeholders involved, the living and fast evolving nature compounded by the tight interconnectedness with almost any other major infrastructures are a few of the reasons. And right there lies the possibility for a significant loss of resources and, by corollary, a significant potential to save the taxpayers’ money.

So, how do we put our best foot forward in the face of this mighty challenge? What measures do we have in place today to get around this? What else can we do to maximize the lifecycle value of these living behemoths? We may first break down the entire lifecycle of power grids into three phases of (i) planning, (ii) development and (iii) operation. Based on this categorization, we can then assume that a precondition for system-wide productivity is harmony among the largest pool of stakeholders, hence, it is safe to say that we are very much advanced in the planning and operation phases. Examples would include initiatives such as regional transmission planning and Independent System Operators (ISOs) that cover far larger geographical footprints than traditional utility models with ingrained self-sufficiency agendas. So, how about the development phase where the building blocks of power grids such transmission lines, substations, etc., are materialized through power projects?

Initiatives such as FERC 1000 (a Federal Order requiring public utility transmission providers to participate in regional transmission planning, reforming cost allocation methods and introducing competition in development of transmission projects) has democratized the transmission planning process through a wide-open solicitation mechanism, which paves the way for selection of the fittest and the most cost-effective alternatives. What happens next though, in terms of the action plan and the actual development, is a tricky one; it could make or break the earlier efforts in the planning stage and any later efforts during the lifetime of the projects and the power grid at large. The very same holistic vision employed at the planning and operation phases, but now at the project level including all the ramifications, would go a long way at the development phase. Otherwise, the blind spots could affect the stakeholders for the lifetime of the project.

Like any other major industrial development project, maximizing the lifecycle value of power projects is a multilevel nested optimization problem, which starts with pre-investment studies and followed by the investment and operation phases. Each stage is characterized by many constraints, parameters and decision variables, every one of which has the potential to act as a tipping point with considerable compounding effects down the road; for example, the outcome of an opportunity or prefeasibility and feasibility studies, the decision to build/tender/bid, the basis of cost estimates, the rationale for site selection, the accuracy and adequacy of energy yield assessments, the quality of project planning and subsequent delays and pressures on the crew, the engineering design criteria, the desk research and field investigations, the input data and parameters for engineering design, the choice of technology, supplier and contractors, the extent of scope of works and specifications, etc.

There is a fair chance of suboptimal decisions at these tipping points. This is particularly true for high voltage installations, which are inherently complex and of interdisciplinary nature. Also, what further amplifies the chances of suboptimality is our “bounded rationality” as humans compounded by the subjective approaches and the limited available resources to support the decision-making process. These suboptimal decisions are admittedly hard to quantify and clearly pinpoint, and a confident approach to reduce their probability is through due diligence, both at macro and micro levels;

  • At the macro level: Adopting a holistic approach to map out the critical tipping points and identify their ramifications. As a result, facilitating interdisciplinary, interdepartmental and inter-organizational interactions to serve a common agenda
  • At the micro level: Adopting an objective approach built upon the best industry practices and the senior experts’ knowledge, as well as the latest developments in technology, to properly optimize the individual tipping points

Both areas are heavily influenced by the human factor. In fact, in the absence of a computerized decision-making system of gigantic scale that could handle the aforementioned problem in full and singlehandedly, the human factor is a key asset to diligently and purposefully follow through and optimize the decision variables, or tipping points, through both collective and objective efforts. One approach to enhance the efficiency of these efforts is to empower the human capital and cultivate a collaborative and entrepreneurial environment within projects encouraging a self-driven due diligence attitude.

It is safe to say that due diligence at the tipping points is the cornerstone of strategic power projects with maximum lifecycle value. It has the potential to turn a stigmatized failure into a remarkable success story or transform an exasperating lifetime operation compounded by hefty infusion of taxpayers’ money into a long-lasting, cost-effective and hassle-free experience. To this end, perhaps some key questions to ask would include;

  • How do we account for the mega trends; the prospects of technology shifts, grid modernization, policy changes, cyber threats, natural disasters, aging infrastructure, etc.?
  • To what level do we document and incorporate experiences from the past projects, the knowledge of grey hairs, the proven industry practices, etc.?
  • How do we factor in the interdisciplinary, inter-infrastructural and lifecycle implications of projects?
  • How strongly do we scrutinize and clarify the pivotal input parameters and assumptions for planning and design processes, e.g. substation spec sheets?
  • What our key decisions are driven by? Spot prices or lifecycle considerations?
  • What does mark our due diligence for selection of a specific technology, vendor, contractor, site location, etc.?
  • What mechanisms do we have in place to meet the immediate industry needs with some cost-effective and state-of-the-art technology solutions?
  • How do we bridge the gaps between office and field operations?
  • How do we create a streamlined communication platform and promote a productive team spirit?
  • How do we empower human capital to creatively get to the fittest solutions out of a mountain of fast changing of alternatives?
For a downloadable copy of the October 2017 eNewsletterwhich includes this article, please visit the IEEE Smart Grid Resource Center





Amir Kalantari is a power grids professional who has proudly served the power industry in the past 15 years or so in both engineering and research capacities. He has a PhD in electrical engineering from McGill University and is a member of Ordre des ingénieurs du Québec (OIQ). Amir has contributed to development of many power generation and transmission projects as well as cutting-edge research works centered on large-scale power system modeling and operational planning. He has a deep appreciation for the big picture of the power supply chain and in 2016, he founded rmsGrid Inc. in Montreal, Canada, to actively engage in development and provision of interdisciplinary and strategic engineering solutions whose principal objective is to help maximize the lifecycle value of capital-intensive power projects and optimum resource allocation.

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