Renewable investors scared off but help is at hand

solar

By Phil Kreveld, CT Lab, Stellenbosch, South Africa

Queensland because of its unique role within the NEM, could become the cradle for new, AI based transmission and distribution grid monitoring and control development, and become a world leader in renewable integration technology export.

South Africa’s ESKOM electricity company uses CT Lab OTELLO GPS-based metro distribution and transmission monitoring system as its basis for network control and asset monitoring.

Unanticipated marginal loss factors, changes in connection conditions to remote energy zone links, and weak links subject to congestion are just some factors scaring off new investment and seeing owners of renewable sources looking for buyers of their generation assets. The former chief of the Clean Energy Council, Matthew Warren, writing in the Australian Financial Review of 17 August, states that the ‘watching brief’ agencies; the Energy Security Board, the Australian Energy Market Commission and the Australian Energy Market Operator, have been unable to engineer a consistent plan for the integration of renewables. Meanwhile plans for interstate interconnectors are being made, and the charges of ‘gold plating the networks’ are already heard loud and clear. Individual States, for example, Queensland and New South Wales, are scaling up their renewable plans, in the case of NSW, going to 100 per cent within the next ten years. The plans themselves are worthy goals; the problem is that the National Electricity Market is based on a physical set of interconnected grids subject to the laws of physics. In the simplest of terms this is when demand for electrical power and generation of electrical power don’t match, instability in networks takes place resulting in disconnections of parts of the grid. The larger the renewable fraction of total demand, with an exception for hydro, the more instability is likely to result.

The NEM is becoming a very brave experiment in renewables

We live on an island continent, and the national electricity grid is an ‘island grid’, skinny and long. It bears no resemblance to those of Continental Europe or the USA, whose meshed grids are heavily weighted by conventional and nuclear power generation. The NEM therefore represents a very, very brave experiment because in addition to the physical parameters lending themselves to instability, the lack of central engineering planning, if anything, brings unreliability closer. To run the vast machine that is the NEM properly, physical control is needed—not the one often pictured of technicians in front of control desks bristling with hundreds of meters, recorders and switches, but rather unseen, but far more effective, artificial intelligence (AI) employing dynamic machine learning. It is this form of control that is resilient to the rapid changes caused by power flow subject to renewable, non-dispatchable generation. Two things are needed: a change in mindset of distribution engineering which is mired in twentieth century practices, and an extensive network parameter monitoring system covering transmission and distribution because all control is based on information.

How do we get to that stage?

Information consisting of network parameters is key, but is the first step. The information system needs to be a very close to a real-time one with time-stamped information AND synchronised to a common timebase so that network-wide correlation of events is possible. It needs to be contiguous, covering all major transmission nodes, sub transmission nodes and at the very least substation connection nodes. The information on network parameters needs to be comprehensive including for the HV networks, voltage synchrophasors, sequence components, power and reactive power, preferably on a one-second, GPS-synchronised time basis. When it comes to distribution networks, more extensive parameters are needed including in addition to voltage, power and reactive power, harmonics and flicker, and dominant harmonics.

Substations are useful start

Many network stability problems start at the substation level, therefore necessitating stability control within the distribution grids. Because of the rise and rise of behind-the-meter solar generation, extensive control of solar inverters is needed. In order to have the least impact on solar generation, smart control is required including the use of communication protocols such as IEEE2030.5 that can be employed to control inverter power and reactive voltage support. Extensive distribution grid monitoring including edge of grid is therefore imperative. In networks where some level of monitoring and control already exists, the concentration of monitoring and control should be at OLTC transformer-feeder link-voltage and reactive power controller level. The importance of maintaining inverter synchonisation stability requires that control of substation voltage angle is critical as all small-scale grid-tie inverters use voltage synchronisation in their phase lock loop (PLL) circuits. Without control of voltage angle, oscillation of voltage caused by inverters is not out of the question when behind-the-meter generation services most of day time demand.

Weak links and marginal loss factors

Beyond substations, there are challenges that require more than monitoring and control as no amount of sophistication will solve the problems of weak remote energy zone links other than by upgrades. However, within the limitations of links with high resistance to reactive impedance ratios, monitoring will allow accurate, second-by-second loss calculation and that will help in generally providing better financial return for remote solar and wind farms than the largely arbitrarily set marginal loss factors. Using second-by-second power and reactive power monitoring across the remote area zone links, permits the actual second-by-second calculation of net delivered energy at a NEM delivery point. Furthermore, the data gathered at the solar or wind generation substation can provide insight into the most economical solution to connection problems, for example syncons versus static var compensators and assist in solving voltage oscillation problems as have occurred in Victoria’s North-West corner solar farms.

In considering the NEM of the near future, NEM-wide synchronised monitoring provides the basis for machine learning and ultimately AI control. Obviously, such a system doesn’t come about without very extensive data gathered over a couple of years as basis for trial designs and delegation into subsections, for example, using monitors with edge computation in substations to provide to the largest extent possible voltage and voltage angle control. This is probably the first control step that can be implemented in a short time. Security concerns for the network as a whole will require metallic servers and a high level of encryption, for example AES256.

Making a start

The NEM’s problem lies in the disparate ownerships of electrical assets and the multiple agencies that influence its operation, not to speak too much about political interference as well as ‘blue sky’ projections that appeal to electorates. This has made it nigh on impossible for sensible, contiguous monitoring as the very first step, to get any traction. However, the possibility exists for Queensland in that the State owns its generation transmission and distribution assets. From an investment aspect it is likely that costs for Queensland-wide monitoring as a first step would be small compared to potential future costs for upgrades to transmission and distribution assets that could be avoided through smart grid management. When considering AI, Queensland could become the World’s technology hub because as hard to believe as this might sound, the NEM is unique in the developed world—the most likely to exhibit all the ills of instability first as renewables continue to penetrate toward becoming the largest fraction of power in the national electricity system. Queensland’s technological power of its Universities combined with technologies already available and proven in the networks of South Africa’s ESKOM could be a unique combination and provide an exciting export opportunity to world markets.