By Gordon Dromey, Ph.D. and Ian Dromey M.A.Sc.
There is a global trend towards deregulation in the electrical distribution industry. A change from a regulated cost recovery based market to a deregulated market requires a dramatic change in both thinking and in business practice. As a supplier of engineering analysis software to the electrical industry, we have had the opportunity to see some of these changes. This article identifies some of the trends that occur in planning and operations as this transition unfolds and explains why software plays an increasingly important role in it.
There are four key trends we would like to discuss:
Developing an Efficient Distribution System
It has always been desirable to plan and run a reliable distribution system in an efficient manner. Now deregulation has increased this emphasis because of the potential for cost savings. For a distribution company in the wires business, reducing power losses can make the difference between a financial loss and a profit. Planning software must enable the engineer to develop the most efficient system possible.
Since the 1970's, software has been available to model distribution systems and to compute voltages and currents. Most of the software used to date is an adaptation of transmission system planning tools. This software is limited in flexibility and model size and permits, at most, the investigation of a limited number of planning and operation options. The likelihood of finding a 'best' solution for a distribution system with hundreds of potential switching locations and millions of possible configurations is negligible. Software is needed that can automatically identify the best configuration of a system, or the optimum location of new equipment. Mathematical optimization techniques have been used increasingly in the world of scheduling, routing and shipping, but only relatively recently have they been applied in distribution analysis software.
There is a range of types of optimization that is relevant to distribution systems. (See Table 1).
Capacitor optimization is the process of identifying the optimum location for capacitor banks. Many utilities have avoided capacitors because of uncertainty in locating them and to avoid voltage problems during low load conditions. Software-assisted optimization solves both these problems, especially if switched capacitors are considered.
Phase load balancing can free up feeder capacity while improving the quality of supply to 3-phase customers by producing more balanced supply voltages. True optimization is critical so that a minimum number of changes are made to achieve the maximum effect.
Configuration optimization is the most effective way to quickly and cheaply reduce system losses. The analysis involves reassigning open points in a radial distribution system to reduce overall losses while avoiding local overloads. We have noticed that both small and large utilities can use this type of analysis to save money with little or no capital investment. The following case studies are for utilities using our DESS analysis software.
A small utility (60 MW peak) achieved a reduction of losses worth $75,000 per annum simply by applying recommendations to open one switch and close another to maintain the radiality of the network. No cost was involved.
For the same recommendations for another small utility, the annual value of loss reduction was $26,000. However, other significant benefits arose from reallocating load taken from three supplies, one of which was originally overloaded in winter. After optimization it became possible to pick up load in the event of the loss of either of the other supplies. In addition, the voltage profile throughout the system was improved, with the greatest voltage drops reduced to acceptable levels.
For large systems, the number of open points can be substantial and the value of a complete system optimization becomes greater. One analysis on a 450 MW peak demand system resulted in recommendations valued at almost $250,000 per year in savings due to loss reduction, besides improving the feeder utilization.
Transformer size optimization can identify those transformers in danger of failure due to high loading and also identify transformers with low load utilization. Typically, loss improvements are not great but capital cost savings can be large. By identifying optimum transformer sizes for each location, transformer inventory management is improved.
A cost analysis is used to determine the costs associated with a section of feeder. When planning a new feeder or upgrading an existing feeder, usually only capital cost is considered; the cost of losses is almost invariably excluded. Over the life cycle of the system, the cumulative cost of losses becomes a significant factor which should be accounted for. Cost analysis determines the lifecycle cost, including losses, and is the most appropriate for comparing alternative schemes.
Load management is used by some utilities to reduce system peaks. An analysis tool which lets the planner model and experiment with load management options can identify potential cost savings and the extent of load management capabilities.
The types of optimization that have been described can be used to identify the most efficient way to plan and operate a distribution system with a minimum of engineering effort and can have a profound impact on the profit margin of a distribution utility.
Merging Economic and Engineering Analyses
Traditionally, engineering planning departments have had limited involvement with business aspects such as capital budgets and revenue forecasting. Planning was based on technical requirements of load capacity, reliability, and expansion capability with limited attention to economics. In a deregulated market, a closer relationship between engineering and economics becomes mandatory. To become more useful, engineering software must incorporate economic factors and have the ability to search out the most economic solutions that are technically acceptable. This type of information will improve the economic performance of utilities.
Deregulation brings the potential for wheeling power across a distribution system. The cost to the transporting utility depends on existing loading levels on the network and thus on an engineering analysis of the system. The cost required to supply a new customer is likewise dependent on the existing conditions on the system.
Another area of convergence bet-ween engineering and economics is in designing rate structures. Energy retailers and distribution utilities have an interest in the ability to modify consumer rate structures to minimize risk in revenue recovery levels or to fairly share the cost of losses. The potential arises also of reducing system load peaks and thus making more efficient use of the distribution infrastructure. If retailers are to offer a mix of rate structures, then tools are required to design these and model their impact on revenue.
Until now, most planning software has been designed to take a snapshot of system conditions, such as peak conditions, or 'normal' conditions. This is not adequate for use with an economic analysis. To compute the cost to supply a customer for instance, the software needs to consider the varying cost and system conditions throughout a 24-hour period, from weekday to weekend, and even across seasons. This requires the use of load profiles to extrapolate how loads vary according to time.
Consider the case of supplying a new industrial load. For a given energy usage, an industry that spreads its load over 3 shifts will have a very different impact on system usage from an industry that only works a single shift. Effective software should be able to quantify how different types of load affect the system around the clock.
Deregulation brings a whole range of questions and possibilities. Should the utility change its rate structure? Would load management help? How much does it cost to supply a given load or wheel power? Finding answers to these questions requires software tools that can couple economics with sound engineering analysis.
Responding to Change
Deregulation of the electrical market is still a fairly new concept worldwide. Many regulatory agencies are still struggling to establish the best controls to ensure a cheap and reliable supply for the consumer and a stable business model for both the distributor and retailer of energy. It is most important to realize that, for the foreseeable future, any regulatory framework is subject to change. It is not and will not be unusual for the regulator to redefine the performance criteria for a distribution company or retailer or otherwise 'change the rules'. In a changeable environment, software must be equally flexible to accommodate these changes.
Reporting, analysis features and data access must all be flexible enough to allow the user to modify the software as necessary without recourse to the supplier. For instance, with DESS, we chose the add-in concept to provide flexibility, much as in Microsoft Office, where customized functionality can be added to the software through add-in modules. The benefit of this type of approach is that utilities can add functionality specific to their needs at very modest cost without requiring us to change our base software and without any intervention on the part of us, the software supplier.
Discovering and Combining Information
Deregulation brings with it an insatiable demand for more information, information about customers and their loads, about costs, about reliability, etc. Sometimes this information is formally required by the regulator, sometimes by retailers selling over the distribution system, and also by the distribution utility itself for planning and operations. The surprising thing is that many utilities are already sitting on top of a wealth of information but don't realize it.
In the past, utilities had islands of information. The GIS people had a nice map of the system, but it was only used as a paper map by line crews. The customer service people collected billing information but only used it to invoice customers. The SCADA system collected reams of information that was used only by operations. Likewise, if the engineering department had analysis software, they probably entered the data for it independently.
The trend in utility software, as in the rest of the software industry, is to gain the maximum value from information that already exists. The current buzzword for this is 'data mining', where existing databases are analyzed to extract useful data. Billing systems contain large volumes of information about consumption patterns among different types of customers, trends in load growth, etc. By combining this information with engineering analysis, planners can extract loading conditions for more accurate analyses and can even forecast load growth by region or by customer type.
Another trend is towards open systems. Customers are demanding that software suppliers provide the ability for different databases to talk to each other. If GIS data already contains information about the configuration of the system and details about the plant, this information should be used as a basis for engineering analysis. The engineering department should not have to populate a complete system model when one already exists. Likewise, SCADA measurements can be used to supplement the data used in analysis software.
Deregulation creates the demand for answers to a wide variety of economic and technical questions. Utilities need to be aware of this so they can implement workable software solutions. A key factor in successful information systems implementation is the ability to link together the traditionally separate databases used by different groups inside a utility.
Summary
Moving to a deregulated market requires a fundamental change by utilities in both practice and attitude. Those that make preparations early will find themselves in a better position than those that sit back and wait for change to be forced on them. Critical decisions require that suitable tools and information be in place as soon as possible in order to make a successful transition to a deregulated environment. Utilities not prepared for such an environment are vulnerable to being undervalued and subject to acquisition by more flexible organizations.
The changes introduced by deregulation require much more from utility planning and operations software than previously. Engineering and economic factors must be considered together. Utilities must also plan how to integrate the different islands of information they maintain so they are able to answer the new technical and economic questions they will surely encounter. Planning for future software and information needs can reduce the stress and disruption inherent in a change to a deregulated distribution industry.
Gordon Dromey, Ph.D. and Ian Dromey M.A.Sc. are the principals in Dromey Design Inc., a company specializing in distribution analysis software. ET