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Horizon Power has undertaken long range modelling and forecasting of each of its microgrid networks. The new LCOE where determined based on a Greenfields site to determine lowest cost of a supply solution overlaying the cost curves Challenges still on fixed cost and the discrepancy between flat variable tariff and a new structure that appropriately reflects the fixed cost recovery 2
We hear a lot of talk about the volution of the electricity industry but what does that mean for us: • We have seen distributed generation will growing to become the largest generator on the network and completely change network load profiles as we have known them for the last 100 years • Distributed energy storage will grow and completely change network load profiles as we know them today. • The bulk of energy dispatch on the network will come from non-industrial standard consumer electronics • This dispatch will not be secured by a 10 year power purchase agreement with all the certainty we have built our businesses on • No long term security • No step in rights • No liquidated damages • No dispatch profile guarantee • No spinning reserve limits • No SCADA visibility or control • How do we address these challenges? • How do we embrace the uncertainty and still preserve power quality and reliability • What methods can we use to de-risk this future state We will not find the answer to these questions in the way we have done business over the last century 3
Rooftop Solar is cheap but creates a new set of load management, technical and intermittency challenges We need visibility and control of DER to manage the potential for very high penetration DER and reduced costs Feed-in Management will release more hosting capacity 4
We have signed up 82 customers in data gathering phase of the trials - Wattwatchers (IoT) Customers have been gifted a Wattwatchers device and a three years subscription to the solar analytics service, plus free installation Customers can use the smart device app to monitor their PV system performance This is a new experience for many who have quite old systems and have never had visibility of its performance through the day. We hope that the insights they receive through the Solar Analytics app will help them to think about the most efficient use of their solar energy Separately metering solar PV from load on 82 premises is revealing true load which has been masked by PV for the last decade. High quality data that is showing the effect of cloud events on individual system and en-mass across the network How do cloud events effect the operation of the network and power station? 5
You can see from this slide the location of the Wattwatchers installations The green dots show where most of the residential population of the town is concentrated We have achieved a good geographic spread from East to West We have achieved the best possible geographic spread from South to North , which is the path of the prevailing winds on most days 110 properties have an existing PV system, 106 letters sent out to customers 59 applications received 2 expressed interest but did not apply 23 no interest at all (followed-up) 16 not eligible 6 contacted up to 5 times but didn’t convert to an application Eventually managed to sign up 82 participants 6
The weather station is capturing Temperature and humidity, wind speed and direction, barometric pressure and sky camera images of cloud movement High quality data that starts to build a very detailed picture of how weather affects renewable energy generation, customer load and power system operation The slide shows how the data is collected into our database in Bentley, Perth where it is blended with advanced (smart) meter data and SCADA data from the power station we have payed particular attention to the accuracy of time stamping to create a coincident data set that can be used for detailed analysis 7
We are supporting Solcast through their ARENA funded research project Solcast are a start-up forecasting service from the Australian National University They use the Himiwari-8 weather satellite to create a forecasting service for solar PV We have provided Solcast with a network asset plan for Carnarvon in Geographic Information System (GIS) format and details of the longitude and latitude of each LV transformer and how much solar PV is aggregated to each transformer. Solcast provide us with a forecasting service that estimated the impact on PV generation of cloud movements across the town We are learning how to integrate such a forecasting service into a DER control system We are also trying to understand the value of a forecasting service in managing high penetration PV on a microgrid network 8
We are investigating the use of the public internet to manage the visibility and control of DER It is a new idea to place control of network connected generation assets into the hands of a third party cloud based service that uses the public internet as a communications channel. We are using the Reposit Power product to provide a feed-in Management product, and have worked with them to develop new features for their existing product. Feed-in Management is used to curtail the amount of renewable energy flowing into the network as key times of the day and mitigate the risk of pushing power station generation into reverse power and tripping. The aim is to limit the amount of energy exported from managed systems onto the network but not limit the ability of customers to meet their own energy requirements. It is possible to turn selected loads on and off with the Reposit product. We will investigate the usefulness of this function as a Feed-in management tool We will also be using the Reposit product to assist in the development of our own Market Mechanism The hypothesis is that we will be able to achieve a great level of network/system optimisation using DER if it is combined with a market mechanism where a dynamic price for buying and selling energy incentivises customers to, and duly rewarded for investing PV and energy storage. The market mechanism will also price and reward for provision of ancillary services i.e. contributions to 9
power factor correction, frequency and voltage from those DER systems equipped to do so (mostly newer inverters) 9
We have installed 10 new solar PV/Battery systems and upgraded 6 existing PV systems with a battery and battery inverter. We are collecting performance data from two commercial customers and a commercial solar farm. We will also be using the Reposit product to assist in the testing of a Market Mechanism by using a price signal as a proxy for battery discharge control The hypothesis is that we will be able to achieve a great level of network/system optimisation using DER if it is combined with a market mechanism where a dynamic price for buying and selling energy incentivises customers to, and duly rewarded for investing PV and energy storage. The future hope is that a market mechanism will be able to price and reward for provision of ancillary services i.e. contributions to power factor correction, frequency and voltage from those DER systems equipped to do so (mostly newer inverters) 10
We have built a DER Monitor and Control software stack especially for the trials, which we call DMCS 11
We have built a Distributed Energy Resource (DER) control solution to provide real-time visibility and management of DER to respond to changing grid conditions and network requirements. The area shown within the red box has been built and tested and it being used in the trials The modules outside of the red box are described in the architecture but have not been developed yet The concept is a suite of applications (including voltage & frequency control, islanding management, phase synchronization and black start) to enable diesel off and resilient network operation in remote microgrids. An IoT metering solution that collects and transmits electrical generation and load data in real time that is fit for purpose, reliable, secure and minimises data cleaning to maximise potential data insights. To enable the application of advanced analytics, machine learning techniques and predictive forecasting to support Tech-Co The ability to create and send different trading signals to the power grid to influence the supply or demand of energy. To provide the data and systems required by customer facing interfaces for tasks such as billing, records and account management. 12
The core services is a fendemental component used to run the DER trials It consists of a relational database that combines the diverse data sets into a coincident set with relationships mapped to GIS This is a fundamental basis for modelling the impact of weather on DER and the power system as a whole, and foundational to a dynamic hosting capacity engine. 13
Machine learning – making intelligent decisions to manage DER The machine learning is detecting patterns in the way PV systems respond to cloud events It is learning patterns of production over the day and identifies recurring events on individual systems such as shading by a tree. As a homogeneous set it is learning how much PV production is available from the PV systems and how much they can be relied upon to contribute both with cloud and without cloud. 14
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