search.noResults

search.searching

dataCollection.invalidEmail
note.createNoteMessage

search.noResults

search.searching

orderForm.title

orderForm.productCode
orderForm.description
orderForm.quantity
orderForm.itemPrice
orderForm.price
orderForm.totalPrice
orderForm.deliveryDetails.billingAddress
orderForm.deliveryDetails.deliveryAddress
orderForm.noItems
FEATURE RENEWABLE TECHNOLOGY Technology making Britain go green


According to the Centre for Alternative Technology (CAT), Britain is capable of generating 100 per cent of its energy supply from clean sources or carbon neutral back-ups. In an environment increasingly reliant on renewables, Martyn Williams, managing director of industrial software provider COPA-DATA UK, explains how energy managers can adopt new technologies to better manage and monitor these volatile generation sites


that’s network operators, end customers and investors in renewable energy. Forecasts, due to their limitations, are not used in the daily operations of energy sites. By employing more accurate


forecasting however, operators could better manage supply and demand. New technology is already beginning to improve the exactness of predictions by using advanced computer models. However, it is recommended that this is used in combination with real-time system monitoring. Smart grid control software, like


D


uring 2018, coal was responsible for just one per cent of Britain’s total


energy electricity generation. This resulted in the country’s coal-fired power stations remaining entirely unused for twelve days in June - a longer period than in 2016 and 2017 combined. With renewables taking an increasingly


greater share of the country’s energy consumption, Britain is on course to meet its renewable targets of 30 per cent renewable generation by 2020. However, transitioning to this form of power supply is not without challenges.


TRANSITIONING TO SMART GRIDS Even today, cost is one of the biggest barriers to the adoption of renewable energy. Developed countries like the UK have a mature fossil-fuel infrastructure that’s been around for over a hundred years. Transitioning to a renewable alternative is, in many cases, more expensive and requires much higher initial investment. The same is true for developing countries where renewable technology is even more cost prohibitive. Over the next few decades, billions of


pounds will be spent on Britain’s energy network. While some of this is required to maintain the existing system and replace ageing equipment, the creation of smart grids will also require investment in new technologies. In fact, this requirement has encouraged


a pledge by Britain’s leading electricity network operators, including SSE Networks and UK Power Networks, which promises to deliver £17bn of smart grid infrastructure by 2050.


26 WINTER 2019 | ENERGY MANAGEMENT


MANAGING UNCERTAINTY The volatility of renewable energy sources can also create problematic surplus situations. Let’s say wind speeds were to dramatically increase. If unprepared, the grid may not be able to handle the sudden surge in power from a wind power farm and this could cause power outages. In fact, there have been instances of operators resorting to paying customers to use excess electricity to balance this unmanageable surplus. Reserve power flow, or back feeding, is


one method of managing this excess energy. However, back feeding isn’t exclusively for renewable sources and occurs regularly on small-scale power grids, usually during the middle of the day when people are out of their homes. As residential energy demand during these periods is low, some of the generated electricity can be fed back to a transformer through the network. Traditionally though, distributed systems


did require back feeding. Most of the generation came from large-scale fossil fuel sources which were located on the main network, therefore the power would flow predictably onto smaller systems. However, increasing renewable energy


sites, as well as microgeneration sites, means energy volatility is increasing, causing more occurrences of back feeding, as well as a new need for energy storage.


FORECASTING GENERATION Improved forecasting could be used to alleviate this challenge. However, it is argued that forecasts are often provided solely as a comfort to decision makers -


COPA-DATA’s zenon, allows operators to actively manage grid behaviour in real-time. Therefore, the operator can react appropriately should the site begin to generate more or less power than expected. This real-time insight doesn’t lessen


the volatility of renewable generation, but it can improve awareness of a system’s conditions. For instance, the software could immediately alert an operator when wind speeds increase. By correlating this data with information from the wider network, the software could provide a warning that a surplus of energy will occur, and back feeding is required. Back feeding isn’t always a feasible


option, however. In some instances, excess energy must be stored. Research by market analyst Aurora Energy Research suggests that to meet its renewable energy targets, Britain requires an additional 13GW of energy storage in order to successfully balance the grid. Transitioning from a traditional energy


network to a fully functioning smart grid is incredibly complex. Britain’s ageing infrastructure means that costs maintaining and repairing these facilities are essential, but investments in new technology cannot be overlooked. Britain may be capable of generating 100


per cent of its energy supply from clean sources, but until the nation has adopted technologies to efficiently manage, store and distribute this energy, this goal will not come to fruition.


COPA-DATA UK copadata.com 


Page 1  |  Page 2  |  Page 3  |  Page 4  |  Page 5  |  Page 6  |  Page 7  |  Page 8  |  Page 9  |  Page 10  |  Page 11  |  Page 12  |  Page 13  |  Page 14  |  Page 15  |  Page 16  |  Page 17  |  Page 18  |  Page 19  |  Page 20  |  Page 21  |  Page 22  |  Page 23  |  Page 24  |  Page 25  |  Page 26  |  Page 27  |  Page 28  |  Page 29  |  Page 30  |  Page 31  |  Page 32  |  Page 33  |  Page 34  |  Page 35  |  Page 36