Thematic Spotlight: History of OR in Energy and Environment

Energy management and modeling include planning and operation of energy systems, production, and consumption. The Energy sector is characterized by a diversity of technical and operational problems of distinct nature with different levels of players involved ranging from big oil firms to small power distribution companies. Further, the global mission of “making the world green and better place to live in” has created socio-economic and environmental responsibility for every individual in our society and made Operations Research (OR) tools indispensable. Recent advancements in energy management have led to well-known modeling tools, such as supply-demand modeling and demand forecasting, but the roots of the energy management travel far back in time.

In September 1957, an economist in UK showcased the problems faced by Central Electricity Authority in transporting coal from pits to power plant using a linear programming approach in the first International Conference on Operational Research. The oil industry has been a heavy user of OR techniques to support refinery operations. Therefore, the applications of OR models and methods has made a successful contribution to the evolution of decision support system in the energy sector.

Energy modeling for policy studies exploded in the United States after the Arab oil embargo of 1973. As the immediate chaos of oil embargo subsided, the effort to deal with its implications expanded rapidly and resulted in the formation of the Department of Energy (DOE). The immediate role of DOE was “Project Independence” (PI) set forth by President Nixon. Project Independence was aimed at achieving energy independence by 1980.  The PI team of analysts and other business experts looked into this issue. The initial model was multiple regression analysis of fuel demands. Later, another group analyzed each technology and the transportation links for moving energy products from the producing regions to the consuming regions.  The demand and supply curves from the models along with an underlying network of transportation and market equilibrium lead to an optimization model which can be cast as a linear programming problem. This eventually became what is known as Project Independence Evaluation System (PIES), which was extensively used to analyze the demand and supply shadow prices for energy products. With the help of PIES, it was concluded that energy independence in not possible by 1980.  The standard toolkit of operations research, especially mathematical programming, played a prominent role in these days and the subsequent analytical history over the rest of the century. The field is too extensive for this chronicle to be in any way comprehensive.

In 1978, Energy Modeling Forum was established at Stanford University, to increase the use of the energy models and bridging the gap between researchers and modelers. EMF started projects that are considered as major issues in the energy sector. Energy and economy research group compared the six models of the link between energy and economy to isolate the key factors determining the effect of energy system changes on long–run growth of the US economy. Electric load forecasting team examined the use of ten forecasting models and identified prominent issues and limitations of the models while alternate energy demand elasticities group conducted a specialized test of the aggregate price elasticity of eighteen prominently used models under multiple scenarios to identify the sensitivity of the models response to variations in the prices of oil, gas, etc.

The changes in the organization of the electric sector, towards the unbundling of the generation, transmission, distribution and commercialization activities, lead to the need for evaluating the adequacy of the transmission system independently from the generation system. Fuzzy approaches seem more adequate than probabilistic models to tackle uncertainty regarding generation due to the market influence concerning scheduled units and generation amounts, and due to their capability to describe mathematically qualitative declarations about load or generation.

The power flow computation is an important tool for planning and operating electric power systems. The state variables of the fuzzy power flow problem can be calculated in an exact and symmetrical way, by means of solving multiple constrained nonlinear programming problems in which power flow constraints or voltage constraints can be included. High-pressure natural gas transportation and distribution systems are very complex structures made up of several pipe sections of different diameters that must be adapted to different conditions of flow and pressure. Gas transportation companies need to plan the reinforcement of those networks. Heuristics for solving the large-scale integer non-linear problem of minimizing investment costs of an existing gas transportation network, finding the pipeline segments to be reinforced and their sizes under demand satisfaction constraints with respect to different pressures is done by solving a continuous relaxation followed by a branch and- bound scheme.

In the last decade, energy modeling gained importance with the modern day computers capable of solving large scale problems. Energy-economy optimization models have emerged as an important tool to explore energy futures using a structured and self-consistent set of assumptions and decision rules. Such models have been used at the international, national, and regional levels to perform integrated assessments of future energy system development and its impact on social, economic, and natural systems over the next several decades. Open source, as well as commercial software which can model wide varieties of energy problems, such as supply-demand problems, energy generation, stochastic energy production, alternate energy network design, electricity demand forecasting, etc., has significant contributions. LEAP (Long Range Alternatives Planning System) was developed at Stockholm Environment Institute's (SEI) US Center as a software tool for energy policy analysis. MARKAL is an integrated energy systems modeling platform, used to analyze energy, economic, and environmental issues at the global, national, and municipal level over time-frames of up to several decades. MARKAL can be used to quantify the impacts of policy options on technology development and natural resource depletion. The software was developed by the Energy Technology Systems Analysis Program (ETSAP) of the International Energy Agency (IEA) over a period of almost two decades. NEMS (National Energy Modeling System) is a long-standing United States government policy model, run by the Department of Energy (DOE). NEMS computes equilibrium fuel prices and quantities for the US energy sector. To do so, the software iteratively solves a sequence of linear programs and nonlinear equations. NEMS has been used to explicitly model the demand-side, especially, determine consumer technology choices in the residential and commercial building sectors. Tools for Energy Model Optimization and Assessment (TEMOA) is another open source framework for conduction energy system optimization to minimize the cost of energy supply by efficient use of energy system over a period of time to meet the end user demand. The models are formulated as linear programming problems and TEMOA also presents scenario generation tools to analyze stochastic nature of energy deployment and investment in energy sector over the near future.

In summary, OR tools have been used from White House to power house on various applications with significant success. OR methodologies in energy sector provides solutions to a range of questions such as, what is the most effective way to carbon generation in the power sector, carbon taxes, or indirect methods, such as renewable portfolio standards. In the face of aging transmission infrastructure, how should the existing system be reinforced and expanded to meet efficiency, reliability, robustness, and economic criteria? What is the impact of renewable integration on the power system? What is its impact on dynamics, stability, and control? What is its impact on daily operations? What is its impact on long term generation and transmission capacity planning? Answers to these questions has become efficient and reliable with the application of OR tools to move the world in the path of sustainable energy development.

 

References

Hogan, William W. “Energy Modeling for Policy Studies.” Operations Research, vol. 50, no. 1,    2002, pp. 89–95., www.jstor.org/stable/3088454.

Sweeney, James L and Weyant, John P “The Energy Modeling Forum: Past, Present and Future”. Energy Modeling Forum, Stanford, pp 6.1.

Murphy, Frederic H., and Susan H. Shaw. “The Evolution of Energy Modeling at the Federal Energy Administration and the Energy Information Administration.” Interfaces, vol. 25, no. 5, 1995, pp. 173–193., www.jstor.org/stable/25062058.

https://en.wikipedia.org/wiki/Energy_modeling.

(Edited by Karthick Gopalswamy)