Today, it’s no surprise that reducing energy costs is a top priority for companies. The uncertain economic and financial climate and the associated drop in revenue have actually increased the pressure to reduce expenditure on energy in order to prevent even greater erosion of margins. More specifically, comparatively high energy prices, increased environmental awareness globally and increasing “real” deregulation of the energy markets have given rise to increased interest in energy-saving opportunities. While most operators are aware of the need to reduce energy costs, there are obstacles that keep companies from meeting projected energy goals. On the one hand, firms often lack the appropriate IT systems and supporting business processes to measure their energy performance and produce actionable information. On the other, the responsibility for energy costs is often shared between several people within an organization, adding another layer of complexity to the mix. In light of this, one approach that has proved to be effective in helping organizations reduce energy costs and take advantage of potential savings which have been largely unexploited is model-based energy management. The key lies in technology solutions that utilize precise simulation models of the major process and utility systems. These include all the peripheral production, costs, and commercial information analyzed in a consistent way for, decision-makers. This knowledge is useful for guiding long-term strategic decisions, concluding energy supply contracts, preparing budgets and investment plans, and optimizing the energy costs of ongoing operations on the basis of current demand, costs and plant availability. In fact, Saudi Aramco is just one organization that has experienced a significant return to date with model-based energy management. The organization built an integrated planning model for several process facilities involved in their gas processing business. These simulations were designed to reduce time in the planning process. Post-implementation, not only did they accomplish their time savings goal, they also achieved a 3%-5% reduction in energy use while increasing throughput 3%-8%. This integrated approach to energy performance management consistently achieves significant savings in a number of critical areas: • Utilities production planning – An accurate utilities requirement prediction for production plants (demand forecasting), combined with current cost information on utilities supply sources, and allows production plans to be drawn up with optimized costs and back-up plans. • Optimum utilities execution – It is important to not only undertake optimized and realistic energy production planning; organizations also need to be in a position to implement the plan. Optimum execution is only possible when the plan is both communicated to the decision-makers involved and adapted to the constantly changing production conditions. • Utilities contract management – As a general rule, energy purchasing costs can be noticeably reduced if demand can be planned and conveyed to the energy supplier in advance (nominated). Frequently, these nominations are based on the experience and know-how of the respective employees, but rarely from all requirement data available from a model-based simulation. Such an energy management system can automatically produce an energy demand prediction according to production plans, thus drastically improving the quality of the nominations. Better accuracy reduces the chance of costly contractual penalties. For a producer who is using part of the production stream for fuel, this process does not reduce cost but increases revenue and the accuracy of sales nominations. • Improved utilities purchasing – With good information on demand, employees are in a better position to acquire fuel at the best prices and take advantage of opportunities. • Optimized investment decisions – A model-based understanding of the energy supply system allows maximum use of common utility systems and investments to be planned that account for optimum energy use and emissions overtime. • Optimized energy and emission trading – Site operators can react to fluctuations in the electricity market and emissions limitations. Model-based energy management allows operators to export power when power prices are high and comply with emissions limits. However, in order to minimize the risk traders need to know exactly how much electricity can be exported at that precise moment and at what cost. This information is available from a model-based energy management system. Although a great deal has been invested in energy-saving programs over the last 30 years, it’s clear that there is still huge potential for savings through strategic energy and emissions management in order to achieve further longer-term cost reductions. In what ways does your organization leverage energy and emissions management? What do you believe is the best approach to capitalize on energy-based cost savings? Mike Strathman, Director, Exploration & Production Group, AspenTech
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