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I plucked this story from a growing and vibrant, "inside the Emerson firewall" community. This community connects Emerson global sales, project, and application folks together, primarily to ask about references--"has this has been integrated with that" sort of exchanges. The particular question was about examples of distillation control.

Emerson's Doug White responded with an example of a European refiner with the business objectives to maximize throughput, maximize the value of product recovery, maximize heat recovery, and maximize heater efficiency to improve overall energy efficiency. The fractionating distillation process involved fired heaters and atmospheric, stripping, and vacuum distillation towers.

The Emerson team, led by Project Manager Chibuike Ukeje-Eloagu, worked with the refinery's engineering and operations staff to plan and execute this project. The project implementation plan was first to conduct a site survey to gather data on current performance and perform preliminary step testing to understand the process dynamics of this unit.

Next the team would design functional, detailed and acceptance test specifications for review, iteration, and acceptance by the refinery project staff. After this design phase was completed, next would come the build phase where the advanced process controllers (APC), steps tests of manipulated variables (MV) / disturbance variables (DV), and models would be developed.

The final commissioning step would be to commission the controllers, train the engineering and operations staff, and conduct the site acceptance test per the test specifications. An important final step was to benchmark the process' performance, compare against the original process data collected, and calculate the return on investment for this optimization project.

Model predictive control (MPC) embedded in the refinery's DeltaV control system was employed because the process had large interactions. These interactions made single and cascade loop control strategies difficult to implement and maintain over time. The process had a number of disturbances for which the model needed to account. It also took a long time for the process to reach steady state conditions. The solution was to create five APC controllers--one for each fired heater, one for the atmospheric tower, reflux drum, and stripping towers, and one for the vacuum tower.

One of the key constraints in the process was the product compositions of the gas, naphtha, kerosene, light diesel, diesel, atmospheric gas oil (AGO), low-vacuum gas oil (LVGO), and high-vacuum gas oil (HVGO) produced. The traditional method had been manual measurements that were drawn and sent to the lab once per day.

Chibuike's team developed regression-based inferential sensors or virtual analyzers, built with neural networks, to predict the product compositions in real time. An example of a virtual analyzer was one to predict the diesel pour point. These virtual analyzers perform inferential analysis using a regression based on product flow rates and distillation column temperatures. The predicted values are updated daily against the laboratory results to help keep the neural network models virtual analyzers tuned and making accurate predictions. The model predictive controllers use these predicted values as constraint variables to keep the products within specification limits.

Upon installation and post-audit, the throughput was increased to a level where the downstream units actually became the bottleneck. The quantifiable results were a payback within three months. This came from increasing production of more valuable products while reducing product giveaway and improving heater efficiency. The non-quantified benefits were reduced operator actions to maintain steady-state operations and improved response to disturbances such as crude oil composition changes.

Over the past several years, the controllers and virtual analyzers have been in continuous use. The refiner and Chibuike's team have ongoing service agreements should immediate help or tweaks to the models need to be made. The models are robust and tolerant of inaccuracies to a certain degree and so long as no major process modifications are made, the models have not required refitting to the process dynamics.

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Update: I wanted to give a note of clarification that the neural networks initially used were replaced by regression-based inferential analyzers due to insufficient historical data in the historian to properly train the neural networks. I've updated the text in the original story above.

Chibuike shared with me that the in country Emerson office provides the day-to-day ongoing support as required to keep this optimization project successful.

OK, I confess to being an engineer in my core when I was explaining to my son the other day how the heart is a reciprocating pump. The systolic and diastolic pressures are the high and low-pressure peaks based on the heart's expansion/contraction cycle. Blood pressure is one diagnostic indicator on the health of the heart and circulatory system.

What prompted me to remember all this was a presentation I'm looking at by Emerson's Tim Olsen. You may recall Tim from his successful election to the position of 2nd Vice Chair for the AIChE Fuels & Petrochemicals Division (FPD). The subject of the presentation is pump health monitoring.

Thankfully, Tim did not take this heart analogy path we find ourselves on in this post. Typically, a process pump failure will cause a process upset and loss of production. If the pump is pumping flammable or hazardous substances and has a seal failure, safety, health, and environmental issues may occur. Having a spare in-line pump does not prevent unexpected failures that may result in conditions requiring prompt operator attention.

Without monitoring, pump seal failures often appear to be sudden and indicated by spills, vapor clouds, or fires. Today, for most process pumps, warnings come from periodic manual vibration measurement. Tim shares that most refiners monitor their critical pumps, perhaps 5% of all the pumps. The definition of what is critical is likely similar across refiners, but there will be differences.

Both safety and economic reasons are considered when identifying critical pumps. Every pump, critical or not, can cause pains such as process upsets and increased maintenance costs. For this reason, pump health monitoring may be warranted on many "non-critical" pumps. In the case of refiners, Tim cites a pump failure example, which can lead to insufficient fractionator reflux causing column overhead system over-pressuring. This in turn leads to the lifting of a relief valve to flare.

Tim recommends adding wireless measurements in places where existing diagnostic instrumentation is not present. He has observed three key areas that refiners are looking at pump monitoring capabilities: alkylation units, critical workhorse units like the crude unit, fluid catalytic cracking (FCC), and hydrocracker, as well as those applications with a history of unexpected pump failures.

Continuous vibration monitoring is important to identify and prevent root causes of seal failure from occurring. Some causes of this vibration include poor shaft alignment, worn bearings, loose pump mounts, broken foundation mounting bolts, cracked foundation, cracked or damaged impeller, and cavitation. This excessive vibration increases the wear on the pump's mechanical seal leading to failure.

Replacing the field operator or maintenance technician's manual spot measurements with continuous measurements provides the information to predict when failures will likely occur to allow maintenance to be performed before a failure occurs. This information can be historized and trended and made available in real-time to both console operators and maintenance departments. Wireless vibration transmitters form the heart of a health monitoring solution that is secure and easy to implement.

Tim makes the point that that having pump health monitoring is like adding sets of eyes continuously focused on these pumps, providing operators the opportunity to take corrective action before the pump failure. This early warning can help avoid the associated health, safety, and environmental impacts.

Pump health monitoring as part of an overall predictive maintenance program can deliver financial returns. In a Chemical Processing article, More-intelligent devices help plants get smarter, Emerson's Doug White noted:

Actual implementations of predictive maintenance have led to significant gains... Potential production from existing equipment typically increases 1-3% because of fewer unscheduled shutdowns, while unplanned maintenance costs decrease 10-30%. The return on investment can be among the highest of any possible plant expenditure...

Although this may admittedly be a stretch, the cost of pump health monitoring is perhaps like the cost of good nutrition and exercise for maintaining a healthy heart.

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A recent Wall Street Journal article, U.S. Expects Steady Climb in Energy Prices opens:

Energy prices are undergoing a long, slow march higher as major economies shake off the effects of last year's recession, the U.S. Energy Information Administration said Tuesday in its monthly outlook.

This outlook has many process manufacturers in energy-intensive industries again looking for opportunities to increase their energy efficiency. Emerson's Dr. Douglas C. White has written a great article, Save Energy through Automation, in the January 2010 edition of AIChE's Chemical Engineering Progress magazine.

Doug takes a reference Olefin plant with a naphtha feed that produces 500K tons/year of ethylene, total energy usage of 30MMBtu/ton ethylene, and total steam usage of 11MMBtu/ton ethylene. You can see the other process parameters on page 2 of the article.

He provides very specific energy saving examples and business result quantification based on the reference plant. I'll highlight only a few specific examples but you'll want to read the full 8-page article if energy efficiency improvements are part of your 2010 plans. Doug notes:

Advanced control and optimization systems can have a large impact on energy usage. However, their general functionality and energy impacts have been covered previously [Nasi, M. et al Experience with ethylene plant computer control, Hydrocarbon Processing, V62, N6, June, 1983, p. 74] and will not be discussed further here.

It's important to make sure the key plant variables are being measured accurately, "in terms of location, frequency, accuracy, and number." Deadtime can be introduced if the measurement device is physically located some distance away from a more appropriate location. Doug shares that this deadtime reduction can have a greater impact on loop performance than any tuning or algorithm change.

Many petrochemical plants measure fuel gas by volume instead of mass and density. If a plant has variations in fuel gas composition, flowmeters which measure mass and gas density will reduce the variability in cracking furnace combustion control. He cites an example naphtha plant:

...this improvement might be 0.2% in furnace efficiency, which is worth approximately $200,000/yr...

Market conditions, feedstock availability, furnace decoking, and process equipment availability impacts the load/throughput at which a plant operates. Effective anti-surge control on the cracked gas and refrigeration compressors is important since these units are major energy consumers within the plant. Doug writes:

The recycle valve needs to open very quickly and accurately to recirculate gas from the stage discharge to the suction. The ability to stably and safely operate the compressor closer to the surge limit saves energy, and the required operating constraint margin depends on the response characteristics of the anti-surge valve.

These anti-surge recycle valves can go from open to close and close to open in under two seconds. Doug quantifies:

If the plant is in low-throughput conditions 25% of the time, the value of the reduced recycle would be $125,000/yr for the reference plant.

Other energy saving examples Doug describes include stack gas CO measurements for improved combustion efficiency, key control loop dynamic analysis and tuning, and energy management and information systems (EMIS).

He closes the article with the importance of having a, "...structured program to assess, implement, and sustain energy savings achieved through automation..." This includes and energy study block diagram showing this structured approach to identify the top priorities.

There is a wealth of wisdom of practical ways that you can reduce the energy consumption of your process operations. Give the article a read if this imperative is part of your 2010 plans.

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I managed to get my hands on a great paper, Olefin Plant Energy Savings through Enhanced Automation, written by Emerson's Dr. Douglas C. White, whom you may recall from earlier posts. Doug is a principal consultant who leads the Process Improvement and Optimization Consulting team.

He presented this paper at the AIChE Spring National Meeting as part of the Ethylene Plant Technology - Energy Consumption and Optimization track. The abstract:

Energy is the single largest controllable cost for olefin plants and the recent rise in prices has caused most plants to look even more closely at their usage. Automation and advanced automation can significantly reduce usage across all areas of the plant. Some of these savings can be achieved with no investment, only changes in normal operating procedures. In other cases improvements to on-line analyses, measurements and control action are justified but generally require relatively modest investments. The management of the utilities at a major olefin site can be difficult with many daily operating decisions that must balance competing economic and production issues. Real time modeling of process and utility equipment and monitoring of the energy usage in plants permits allocation decisions to be made much more frequently and accurately, often resulting in substantial savings.

Doug describes the economics that Olefin producers face:

Olefin plants are large energy consumers with energy the largest variable operating cost after feedstocks. Using energy efficiently has been and remains a primary goal for olefin producers.

Natural gas is the marginal fuel consumed and its price has been a source of volatility over the past several years. Doug describes surveys where there is at least a 40% spread in energy usage between the most and least efficient plants. The source of this variation is due to the age and efficiency of the equipment and the heat integration.

Doug provides an energy investment opportunity matrix of high, medium, and low potential energy savings versus capital cost/time to implement. An example of a potentially high energy saving opportunity, but coming at a high capital cost is and integrated turbine. At the other end (low savings / low investment) are things like increased insulation and heat exchanger maintenance.

He describes two ways to reduce energy costs--either by reducing supply costs or reducing process energy demand. On the supply-cost side, the focus is to increase internal utility production efficiency and reduce external purchase costs. Advanced control and optimization on the furnaces, quench/fractionators, compressors, and distillation columns are a few examples cited on the process energy demand reduction side.

The paper describes areas to find energy savings. These include: control loop performance improvements, more accurate measurement of process variables, measurement additions via WirelessHART technology, valve performance improvements to handle the various olefin plant load conditions, loop dynamic analysis and tuning, and steam system management and control. The paper provides further thoughts in each of these areas.

Doug recommends developing an automation energy savings program and beginning with a full assessment of current operating conditions. This not only helps with the justification, but also provides the benchmark to compare improvements against to provide return on investment. He counsels that a part of this assessment is to identify the control and advanced control loops that have a major impact on energy usage. He has another matrix of energy loss consequences versus historical frequency for monitoring and maintenance. This analysis helps prioritize financial impact and focus the justification efforts.

Whether or not you're an Olefins producer, you'll gain some insight in how to find and plan a path to energy savings.

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As I mentioned in an earlier "itchy publish button" post, it's always dangerous to include a blogger on your email distributions for upcoming items. I saw an advanced copy of a 2009 American Control Conference paper prepared by Rose-Hulman Institute of Technology's Atanas Serbezov and Ronald Artigue and Emerson local business partner, Cornerstone Control's Ron Knecht. The abstract for this paper, Bridging the Gap between Academia and Industry is:

This presentation describes the deployment of an industrial Process Automation System (PAS), in the Chemical Engineering Unit Operations (UO) laboratory at Rose-Hulman Institute of Technology and its incorporation in the undergraduate curriculum. The UO laboratory has over a dozen of pilot-scale process units (skids) and creates an environment very similar to a typical chemical, petrochemical or pharmaceutical plant. Students learn how to maintain their process under control, take it safely from one operating condition to another, collect and analyze data using a process historian, respond to process alarms and remotely troubleshoot their experiments with limited process information.

Rose Hulman's Chemical Engineering department's UO lab is 6500 square feet, includes process operations such as heat exchangers, pumps, a distillation column, chemical reactors filtration units, and a fermentor. The DeltaV system on which the students learn process control is physically separated from the campus local area network. The students do have remote access to the engineering stations and operator stations and wireless access within the Chemical Engineering building.

The units are outfitted with various measurement technologies. For example, flow is measured with Coriolis, vortex shedding, and orifice/differential pressure technology. Level is measured with ultrasonic and differential pressure instruments.

Three upper division courses are available which teach process control through experiment, data analysis, report writing, and oral presentations. Here's an example of one of the experiments described in the paper:

...in the tubular reactor experiment, the control system can maintain the flow rate through the reactor at set point very well, but the process will become unstable if a set point change from laminar to turbulent regime is executed in automatic mode. In this situation students have to switch from automatic to manual mode and move the system manually towards the new operating conditions.

The paper describes the professors' work with the collaboration of many industrial partners, including Cornerstone Controls and Emerson. In addition to equipment, they received technical advice from the control system architecture to the design of experiments and its associated documentation. Additional work is being looked at to bring virtual plant capabilities into the curriculum.

I was very impressed with the paper and what's being done at Rose-Hulman Institute of Technology to prepare the next generation of process control and automation engineers. The paper will be presented June 10-12, 2009 in St. Louis, Missouri, USA.

I heard a few weeks back that Emerson's Dr. Doug White, was going to be honored by the American Institute of Chemical Engineers (AIChE). I was sworn to secrecy, which is not an easy thing for someone with an itchy finger on the "publish" button. Since the press release is now out, it's safe to talk about Doug.

He is a Principal Consultant for the Process Systems and Solutions business and has held positions such as Vice President APC Services for Emerson, President of MDC Technology, President of Profitpoint Solutions, Senior Vice President for Automation Technology for Aspen Technology, and President and Chairman of Setpoint; all leading companies in the development of modern process plant advanced automation applications.

At this week's 2009 AIChE Spring National Meeting, Doug receives the:

AIChE Fuels and Petrochemicals Division (FPD) award, one of two FPD annual awards, for his outstanding technological contributions to the advancement of these industries.

The Fuels and Petrochemicals Division describes this award:

Recognizes individuals who have made substantial technological contributions to the advancement of the fuels and petrochemicals industries. Selection criteria includes: 1. Long and recognized record in the nominee's areas of achievement. 2. A chemical engineer and preferably an AIChE member. 3. Awardees are selected based on a combination of technical achievement, management skills, business acumen, academic leadership and general service to the profession. 4. Selection shall be balanced between the fuels and petrochemicals industries.

We have featured Doug several times on this blog, including stories of saving energy with advanced automation, justifying capital projects, and assessing energy reduction opportunities. The common thread is that Doug helps quantify the solution with the business objective. He helps engineers speak the language of finance to get the capital or expense budget required to do the project and quantify the results.

I thought in addition to Doug's wisdom shared over the years that I'd give you a little of his background. He has a BSChE from the University of Florida, an MSChE from California Institute of Technology, and an MA and PhD in ChE from Princeton. He's been a member of AIChE for more than forty years.

Doug has applied the fruits of this education and work in the field of process manufacturing and has developed special expertise in the field of advanced manufacturing automation. He has more than thirty years experience designing, developing, managing and implementing advanced automation and optimization systems in oil refineries and chemical plants around the world. He has authored or co-authored more than fifty technical papers on these subjects, many documenting first-of-a-kind system installations.

At this week's AIChE conference Doug will present, The Digital Plant: Progress and Promise. Doug discusses the current state-of-the-art in process plant sensors, automation, and information technologies and offers some projections on future developments. He shares the areas of plant operation that have seen the largest effects to date and the areas in which he expects to see the greatest impact in the future. I guess there's no time to rest on one's laurels when there is wisdom to share.

Congratulations on this well-deserved award, Doug!

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Let's close the week with a short post about energy saving opportunities. The pain of higher energy costs is fresh on my mind with an unexpected trip by car from Austin to Houston and back with gasoline prices now just shy of $4/gallon USD.

Back in May, I wrote about an AIChE paper Emerson's Doug White presented, How to Save Energy through Advanced Automation. Doug is a principal consultant and vice president for advanced process control (APC) services, and has many years of experience justifying, designing, installing and commissioning APC applications for process manufacturers.

If you didn't get a chance to hear Doug present this at the AIChE Spring meeting, or read the PDF of the presentation, you may have a chance to see him live in your area to get your energy-saving questions answered. He's teaming with Scott Pettigrew, an Emerson senior energy consultant.

This seminar series will begin in the Houston area, in La Porte, and will be jointly hosted by Emerson and its local business partner, Puffer Sweiven.

From the seminar flyer, here's what it covers:

Survey the root causes of excessive plant energy usage and how automation can reduce consumption. Review a systematic approach to identifying potentially high payback improvement areas and solutions. Opportunities can originate in the process, measurement devices, valves, or controllers. Learn basic principles and key concepts to understand the nature of challenges and options. Actual plant case studies will be presented. Specific operational improvements in the following areas due to enhanced automation performance will be addressed: reduced fuel costs, reduced electricity usage, reduced steam costs, increased equipment availability, reduced compressor costs, improved boiler efficiency.

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The date is August 21^st from 7:30 to 1pm U.S. Central time at the Puffer Sweiven La Porte office. Send an email to RSVP a spot.

Rumor has it that they'll be another session further East along the Gulf Coast, and possibly other locations. I'll update this post as I hear more.

If you have interest in your area, send me an email and I'll pass it on to Doug, Scott and the team.

Emerson's Doug White sent me his presentations from the recent AIChE spring meeting. Doug is a principal consultant and vice president for advanced process control (APC) services, and has many years of experience justifying, designing, installing and commissioning APC applications for process manufacturers.

Given rapid rising energy costs, his presentation, How to Save Energy through Advanced Automation, caught my attention. He starts by showing an upward trend in natural gas prices (in one word--ouch!) Doug makes the point that process energy usage is often the largest controllable cost in most plants.

Doug shows energy flows for process manufacturers in different industries including chemicals, pulp and paper and oil refining. He also gives some typical percentages of the energy flow inputs and outputs. For example, a typical refinery's sources of energy include 1% purchased steam, 25% purchased fuel, 64% raw materials consumed as fuel and 10% purchased power. This energy is used in steam production and central power production in the power plant. In the process and offsites areas, the energy is mainly consumed in the process-fired equipment, direct fuel usage and electric motor drives. Energy not consumed in the process is exported as steam, fuel and power.

Applying better automation and APC can help improve efficiencies around individual equipment like boilers, heaters and kilns (links are to earlier posts where equipment efficiency stories have been chronicled.) Savings can also be achieved at a unit, multi-unit and site level by finding opportunities in optimization, waste heat recovery, and off-spec/waste minimization.

As the earlier percentages indicate, you may have a control loop heavily involved in your plant's energy usage. It may well be worth improving the measurement, control valve performance and loop control performance to reduce variability and energy consumption. Also, your process may have bypasses around production equipment that may be compensating for poor control through the equipment. Optimized control can eliminate the need for these bypasses.

The presentation is loaded with specific examples including stem systems, combustion control, heaters, distillation controls, plant utility systems, facility optimizers, boiler load allocation and site energy balances. Some examples like power boilers include return on investment (ROI) calculations that may assist you in your project justification efforts.

I wanted to highlight some key points Doug makes around heater optimization. If there is resistance in improving heater controls because the damper control is are not reliable, then he recommends adding positioners to the dampers. Bring the feedback to the control system and then analyze and fix any controller problems. If the next objection is on-line analyzers don't exist or are not maintainable, Doug notes that analyzers are cheaper and more reliable, especially mass flow meters. With today's higher fuel costs, these analyzers should be well justified.

There are likely many areas to look for energy savings. Doug recommends a disciplined approach to evaluation and analysis to prioritize the opportunities. Given the increasing costs of energy and the fact that this is often the largest controllable cost in a process manufacturing plant, it may make sense to establish a program around saving energy and apply focused efforts in prioritized projects to reduce overall energy consumption.

As reported in the DeltaV News RSS feed recently, Automation World magazine's C. Kenna Amos wrote an article, Getting Projects Approved. I know from my days as a systems engineer, that financially justifying a capital project was not nearly as fun as executing the project. Most engineers enjoy the action of seeing their work come to life more than convincing others to approve the capital to get the project going. They also are not typically versed in the language of financial analysis.

The article captures the wisdom of Emerson's Doug White, a vice president of advanced automation services. Doug and his team often assist process manufacturers in ways to help quantify return on investment for automation and advanced automation projects.

In the article, Doug notes:

The project has to be very attractive to be funded, because it will compete with others. The project has to show a clear and compelling return on investment.

Easy enough, but the trick is how to do this. Doug recommends that engineers work with the financial group to understand their selection criteria for capital projects. Basics for most projects include cash outflow analysis and when the return on investment begins. This is the basis for the payback calculations. Also, the capital proposal should include key non-quantifiable benefits often found in health, safety, and environmental (HSE) considerations.

The closer you can tie your proposal to key organizational initiatives, the more the proposal will be noticed more than others will. When it comes to presenting your proposal:

Begin by first defining the problem, then telling them why your project is important and giving reasons why it needs to be done, he emphasizes. Then--and only then--go into financials, beginning with the most likely scenario.

Doug has captured much of his experience in a whitepaper, Calculating ROI for Automation Projects. It comprehensively goes through the components of return on invested capital and how to calculate each component. Give this whitepaper a thorough review and you will be better prepared to have that conversation with the financial group.

For those of you going to the Emerson Exchange next week in Dallas, make sure to catch Doug's short course, How To Find The Economics For Process Automation Investments that will be held Tuesday at 2:15pm and repeated Wednesday at 8am. Here's the abstract for this presentation:

This session presents realistic approaches to automation project economic analysis and justification. The viewpoint is that of the business financial analyst. Specific areas where automation affects the business results are identified and quantified.

You don't have to look too hard to find news stories (here, here, here) of rising oil prices and their impact on process manufacturers around the globe.

Refineries and petrochemical manufacturing processes can especially require vast amounts of energy to process the feedstocks into intermediate or final products.

I spoke recently with Doug White, who leads our advanced automation services consultants for Emerson Process Management. Some of the folks I've written about like James, Eric, and Lou are senior consultants in Doug's organization.

Doug mentioned that one of the units at which refiners and petrochemical manufacturers should take a close look is the fired heater which provides the required heat for the distillation process. In many plants, these units were built 10-15 years ago or more. Most were built in times when natural gas was extremely inexpensive. There was little need for energy efficient designs--so even today they consume energy at higher rates than they could.

He sees these units as a quick way for manufacturers to save costs and improve their bottom lines.

Doug described these opportunities and gives very practical advice on how to get the project assessed, implemented, and sustained in an Oil & Gas Journal article entitled: Advanced automation technology reduces refinery energy costs. Some steps Doug recommends from the assessment phase:

1. Data gathering. Compile information about existing systems.
2. Interviews with plant staff. Find current energy-use problem areas, understand current operational procedures, and stimulate ideas on possible changes.
3. Evaluation of plant energy economics. Understand what are the major users and their costs of operation.

If you are one of the manufacturers struggling with higher energy costs, this article is well worth the read to develop a plan to reduce these high energy costs.

Update: Repaired broken hyperlinks.