Energy Management & Savings

LCA Energy Management Solutions ( http://www.energyreporting.com/ ) announces the release of their “LCA Demand Response Software”, a fully automated Software Package for Ontario’s Demand Response Participants that allows participants to track their curtailment activity in the DR programs on a real time basis.

The Windows based Software provides an easy to use interface giving access to all critical data needed to participate in all Ontairo DR programs. It can also notify key staff members when load reduction is necessary and when a curtailment period has been scheduled. Curtailment activity data, including Kilowatt/Megawatt load, 3 hour price and baseline values, are stored for historical reporting and evaluation purposes.

Demand Response Participants receive financial compensation in return for reducing their electrical load during high energy price periods. The reporting side of the LCA Package allows managers to quickly and easily quantify the revenue generated by each Demand Response event.

The Demand Response package adds to LCA’s product line, which includes IESO Dispatch and bidding functions, Price/Peak Load Control software, and custom developed software for industrial power users.

For more information please contact:
info@energyreporting.com  or visit http://www.energyreporting.com
LCA Energy Management Solutions 1-866-364-7042

One of the greatest challenges facing companies today is organizing and making sense of vast amounts of collected electrical metering data.  This task would be difficult enough if the data was all consistent and in a single data base, but for most companies this is not the case.  For most companies, the data sits in a variety of meters, in different locations around the state or across the country with bits and pieces in a database somewhere and perhaps even some with 3rd party consultants or utility companies.  Perhaps a number of reports are prepared by others and presented to the Company at regular scheduled intervals long after the electricity has been used.

The ideal Energy information scenario for today’s companies would be to have each electrical meter interconnected over the company WAN so that information can be retrieved from the meters and centralized in a single data base.  From there the data could be distributed on demand to the people in the company that need the information, either on a historical (review) basis or on a real time (minute by minute basis).
Imagine having access to electrical usage information from any of your Utility Meters on any computer over your Wide Area Network.  Not only could you view historical consumption data, but also real time (minute by minute) electrical loads for individual meters or groups of meters by facility, geographical location or corporate wide.  With access to this information, your ability to manage electricity usage and identify waste would be extremely effective.

Many companies have opportunities to achieve savings and reduce electricity waste by taking an active roll in how electricity is used in the facility.  The first step in actively managing the electricity usage is to create a strategy for curtailing electrical load when it is beneficial to do so.  The curtailment strategy must be unobtrusive to the manufacturing process and be worthwhile in terms of economic benefits to the company.  Although this sounds difficult to achieve, it has been our experience that companies can quickly identify significant loads which can be curtailed when necessary.  It sometimes proves more difficult to get employees to embrace the strategy as resistance to change can sometimes be an issue when internally “selling” the concept of automatic load control.  It if for this reason that upper management must drive the deployment of the strategies and educate employees regarding all the economic and environmental benefits that managing the use of electricity will bring to the company.

It has been our experience that curtailment of electrical load must be fully automatic.  Over the years, some companies have attempted to curtail load by turning on various lights, buzzers and even pagers.  This is not a reliable way to curtail electrical load because the failure to curtail just once can have a detrimental effect on the goal of saving money or reducing waste.  This is especially true if the curtailment is to avoid setting excessive peak demand.

Most utilities calculate peak demand on a monthly or annual one time occurrence basis, for example if your utility calculates peak kW based on the highest reading in any 15 minute or 30 minute time period throughout the month, failing to curtail during any single time period when your electrical load is high would set a new peak.  By automatically curtailing the electrical load this risk is avoided.

Historically, companies had load curtailment strategies on a facility by facility basis. Today there are more opportunities to aggregate loads by facility, region or on a corporate basis.  The ability to aggregate can be beneficial from a load curtailment point of view as it allows for a strategy which can be spread across a greater number of electrical loads and allows for flexibility in the scheduling of various equipment that can be curtailed, this will lesson the potential for an detrimental effect to production.  For example, a company that aggregated 6 facilities with a load curtailment target of 2 megawatts could control a smaller number loads in each facility to achieve the total reduction at any given time.

Being able to quantify the savings is also important. By centralizing the data and allowing access to it by any authorized users across the corporate WAN, user friendly reports can be generated for individual meters, aggregated loads and on a corporate basis.  Many companies have found it beneficial to also gather information from sub-meters in order to facilitate the allocation of electricity costs by department or “cost center” within the facilities.

Although the deployment of such an energy management solution would seem very expensive and complicated, for LCA it is actually quite straight forward and affordable.  With over 30 years of experience in deploying proven solutions we can assure you that our experience and expertise is second to none and we look forward to the opportunity to discuss your energy management goals.

info@energyreporting.com

QUESTION:

I’m trying to figure out the best way to estimate generation output of a power plant. For example I’m looking at a 100MW plant and I estimate an 80% availability how can I translate this into GWh injected into a national grid. The specific plant I’m reviewing is called Kiambere in Kenya and its stats are (2006) capacity – 144MW (hydro), availability 96.20, load factor 68.25, auxiliary consumption 2.39GWh, transformer & line loses 6.04GWh. How can I use these stats to arrive at the electricity units injected into the grid – 852GWh.

Thanks, Robert

Answer is as follows :-

(a) A 144 MW generator produces 144 MWh each hour it is running at full load.
This equates to 0.144 GWh per hour or 0.144 * 24 * 365 = 1261.44 GWh / year

(b) Factor in the load factor:
then the annual GWh that is needed to be produced is 1261.44 * .6825=  860.93 GWh

(c) Factor in generator aux requirements:
 then actual GWh leaving the generating station is 860.93 - 2.39 = 858.54 GWh

(d) Factor in line losses:
then actual annual GWH available at load point is 858.54 - 6.04 = 852.5 GWh

In arriving at the total GWh number it was assumed that the load factor number that was given had already taken into account the generator availability of 96.2%

Send your questions to:  info@energyreporting.com

When developing a strategy to minimize peak electricity demand, there are several key elements of consider.

1) Gathering electricity meter data

Today’s utility meters typically have a variety of information available to the user, however getting at that information can be a bit tricky, especially when you need it in real time to make decisions regarding peak demand.  Lets look at some different ways of getting information out of your main incoming utility meters.

a) Communication port

Many modern meters have communication ports that allow customers to “talk” to the meter in real time.  Data within the meter is held in registers and can be retreived by software that uses the right “protocol” to talk to the meter and request the right information.  Registers within the meter can contain kW, kWh, kVAh, KVA, kVarPower Factor, volts, amps, current, and other data relating to harmonics.  For peak demand calculations, we’re interested in the kW and kVa registers primarily.  By accessing data from these registers on a minute by minute basis, we can calculate the peak demand based on kW or kVA load.

b) Reading Pulse Outputs

Some meters only have pulses available and don’t have a way to “talk” to the meter.  In this case the pulses need to be collected in an accumulator that can then talk to the compute software.  Each pulse from the meter is equal to a pre-determined amount of electricity consumed. By taking the pulses and multiplying them by the meter multiplier, you can calculate the kW demand, kWh consumption and where kVA pulses are available, you can calculate the reactive load demand.  The computer software typically reads data in the accumulator every minute and then turns the number of pulses received in that minute into a real energy consumption number.

2) Time is of the essence

Your utility calculates peak demand charges based on energy used over specific periods of time.  In accordance with approved billing methods and alogithms.  Some utilities calculate peak demand over a 15 minute window, while others use 30 or 60 minutes.  In some rare cases, some utilities use sliding windows in their peak demand calculations, for example a utility may calculate demand over 30 minutes with a 5 minute rolling window, thereby always calculating the highest 30 minute window ever 5 minutes.  The peak demand control software you choose to use to minimize your demand must be configurable to allow for a variety of different billing scenarios.  The software must also be able to stay in sync with the utilities time window, in other words, the software must know when the 15 or 30 minute period ends to calculate demand correctly.  Even being off by a minute can lead to unnacceptable inaccuracies and make controlling demand accurately impossible.

3) Real Time Information

The demand control software must collect data from the utility meters on a minute by minute basis and have the ability to predict the peak demand at the end of the current time window.  For example if your utility calculates demand on a 15 minute window and you are 5 minutes into that window, the software must be calculating (based on 1 minute data) where you will end up as a peak at the end of the the 15 minutes. By calculating this on a ongoing basis the software can then determine when load needs to be shed to meet the desired peak demand target.

4)  Setting a Target

The peak demand control software must have the ability to set a DEMAND TARGET either based on kW demand or kVA.  Many utilities bill for peak demand based on Kilowatts, however some bill based on kVA or a percentage of kVA.  Ideally, your demand control system should be configurable for either type of scenario.

5)  Load Shedding Strategy

Once you have the ability to get the metering data into the software and predict the demand, you’ll need to know exactly what you’re going to shed when you need to reduce the load.  How and what you decide to control will be based on whether individual equipment has variable power supplies or must be ON or OFF.  The ideal strategy is to select some smaller loads for the first level of shedding and then add larger loads to the second and third levels.  You can then configure the software to shed each level based on a percentage of the peak demand target.  For example, you’re strategy could be that at 90% of the demand target, you’ll turn off 3 selected loads that can be turned off at any time.  Should the demand prediction get to 95% of the demand target you could then turn off the next “bank” of load(s) that would be a bit more of an aggressive cut.  Should you still need more shedding and the load reaches say 98% of the target, you could then shed additional loads and be very aggresive in doing so to ensure a significant cut to the overall demand.  The end result is that you only need to shed what is necessary to achieve the target and can therefore assign more critical loads to higher levels and thereby shed them less often.

Ideal loads for peak demand control include heaters, induction furnaces, arc furnaces, variable voltage power supplies and other non-essential loads.  Furnaces and heaters are excellent because they can usually be backed off in various degrees and have a thermal curve that makes controlling them for a short period of time relatively unnoticable.

What type of savings can be expected from implementing advanced demand control software?  Typically 15-25% of the demand portion of the electricity bill.  However the side benefit is that you will be now running the facility to a management set target level of load and when you start doing this, you become more aware of waste and inefficiencies that can be corrected to deliver addtional savings.

Lastly, we are often asked the question of what to set the peak demand target at initially.  This requires a bit of knowledge about your loads and the peak demand that you currently are hitting on your bills.  If you have a peak of 2mw and you only go to 2mw 3 times a month, then you will need to determine the next lowest peak and how often you hit that.  For example you may hit 2mw 3 times a month, 1.9mw 12 times a month and 1.7mw 15 times a month, but most of the time your facility runs at 1.5 mw.  You could then set a peak demand of say 1.6megawatts and then reduce the target slightly each month based on reports from the peak control software.

For more information regarding your own specific needs, please feel free to email us at  info@energyreporting.com

Electricity Peak demand is a component of your electricity bill which is based on usage over time.  Utilities calculate peak demand in a variety of ways based on the type of customer they are supplying electricty to.  A large industrial electricity user’s demand may be calculated over a 15, 30 or 60 minute window and in some cases the highest average of several “windows” may be used.

Because the demand is based on the highest number of kWh consumed over a specific period of time, the way to reduce demand is to know how much electricity you are using minute by minute throughout the day, once you have this information you can not only know what your maximum demand is, but you can also predict when you are in danger of setting a new peak demand and then take action to reduce your consumption during that time.

There are many different types of Peak demand controllers out there from PC programs to PLCs, however most are basic in nature and cap the peak without taking into account many other conditions which can optimize the ability to produce product while effectively controlling the peak.  The real trick is to be able to predict the electrical demand to the end of the current time period so that you know when action must be taken.

The action that you take to reduce the peak demand when you need to can be manual, such as shutting down various equipment, or the peak demand controller can be connected to various loads to automatically reduce loads in a step by step fashion to bring the consumption for the window in at the desired level.

Remember, every new time “window” is a new opportunity to set a new peak, so the peak demand controller must be running and watching the facility load all the time to ensure a new peak isn’t set.  A good demand controller (such as the one provided by energyreporting.com) allows the facility management to set targets based on kW or kWh over time and supports a variety of time window configurations including 5,15,30,60 minute windows with or without averaging.

Lastly,  some utilities have on/off peaks and perhaps even other times during the day when seperate peak demands may be calculated, therefore the demand control solution you choose should be configurable to a wide variety of billing algorithms and structures.

For more information on Peak Demand Control, please feel free to email us with your questions at  info@energyreporting.com

Do you have an Energy Management related question?

We invite you to submit your questions to  EnergyReporting.com and we’ll answer them right here in our blog!   So whether you want to know what Power Factor or Load Factor is, or how to calculate Peak Demand, whatever your question, we’re here to help!

Submit your questions to   info@energyreporting.com

EnergyReporting.com is a leading provider of Energy Management Solutions including Strategic Planning, multi-vendor system integration, Energy Management Software, Peak Demand Control Systems, Stategic Planning and subscriber based information services.

We are currently seeking representatives in Australia, UK, India and Malaysia that have an interest in providing proven solutions and strategies to companies that seek to reduce Electricity Costs.  If your company is currently involved in bringing Energy Management Solutions to your customers, we’d like to hear from you.  If interested, please email info@energyreporting.com with the subject REP INTEREST

In many electricity markets the price of electricity is no longer a static billing item, but rather a dynamic and in some case volatile part of the electricity billing equasion. In Ontario, Canada, the IESO runs the electricity pricing show and prices change every 5 minutes.  At the end of each hour, and HOEP price is posted (end of hour price) and that is the price for all kWh used during that hour. 

There are several types of electricity customers in Ontario including non-interval metered, imbedded and market participant.  Any company that has an interval meter will feel the effects of the changing prices. In the USA, PJM is the largest centrally dispatched control area in North America and  coordinates the movement of electricity in all or parts Delaware, Illinois, Indiana, Kentucky, Maryland, Michigan, New Jersey, Ohio, Pennsylvania, Tennessee, Virginia, West Virginia and the District of Columbia. Electricity users who purchase electricity from PJM Members may be exposed to hourly variable prices and could experience excessive and potentially unnecessary costs should the price of electricity go up significantly.