by Komoneed | Jul 25, 2024
Connecting Indonesia’s First Large-Scale Floating Solar Plant to the Power Grid
jschoshinski
Tue, 07/23/2024 – 17:47
The Government of Indonesia is transitioning towards low-carbon energy resources while modernizing its electric power systems, as evidenced by the launch of the highly anticipated 192 Megawatt peak (MWp) Cirata floating solar plant. Located 62 miles southeast of Jakarta on the Citarum River in West Java province, Circatais the largest floating solar plant in Southeast Asia and the third largest in the world. Circata was launched by President Joko Widodo in November 2023, moving Indonesia one step closer to its target of reaching net-zero emissions by 2060 or sooner. However, for variable renewable energy (VRE) like solar to be successfully integrated into the Java-Madura-Bali (Jamali) power grid system (Indonesia’s largest electricity network), state-owned power utility PLN needs to make important adjustments.
Renewable energy sources such as solar are considered VRE because they are intermittent and dependent on the weather. This variability can create instability on the grid if not managed properly. PLN has had limited ability to add VRE, resulting in significant changes to the capacity and timing of resource additions and the cancellation of procurements mid-process.
Image
Aerial view of the 200-hectare Cirata floating solar plant.
Photo Credit: PLN Nusantara Power
Through the USAID Sustainable Energy for Indonesia’s Advancing Resilience (SINAR) project, USAID supported PLN to integrate higher shares of VRE into the power grid while maintaining grid stability. Modernizing utility planning practices and operations will enable PLN to strategically integrate a higher share of renewable energy.
Experts provided technical assistance and training to PLN to assess and manage the system and operational impacts of connecting large renewable energy projects, such as Cirata, to the grid. SINAR hosted workshops on VRE system operation, dispatching, and planning; modern electricity systems; and control center dispatch functions. In addition, a study tour to Thailand’s 45 MW floating solar system in the Sirindhorn Dam exposed PLN representatives to best practices, methods, and tools.
To ensure system models reflect actual system operation, SINAR helped PLN update power system data and models on the Jamali grid. Accurate system models are important because they allow engineers and planners to predict how the power grid will behave under different conditions. By running simulations, PLN can identify potential problems before they happen and develop solutions to keep the power grid running smoothly.
PLN’s power grid was able to successfully integrate 192 MWp of installed capacity from the floating solar plant, powering 50,000 homes and providing electricity access to nearly 326,000 people. The floating solar plant is expected to reduce 3.1 million tons of carbon dioxide equivalent through 2035, which is comparable to preventing the burning of 3.4 billion pounds of coal.
“This energy transition is very important for Indonesia to maintain the momentum of rapid economic development, accelerate growth, build national capacity, create more jobs, and at the same time, protect the environment,” said PLN President Director Darmawan Prasodjo.
Teaser Text
The Government of Indonesia is transitioning towards low-carbon energy resources while modernizing its electric power systems, as evidenced by its 192 Megawatt peak Cirata floating solar plant.
Publish Date
Tue, 07/23/2024 – 12:00
Author(s)
Syofvi Roekman
Hero Image
SINAR_Climatelinks_IMG1.jpg
Blog Type
Blog Post
Strategic Objective
Adaptation
Mitigation
Region
Asia
Topic
Emissions
Energy
Energy Efficiency
Grid Integration
Infrastructure
Resilience
Country
Indonesia
Sectors
Adaptation
Energy
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Australian organisations face mandatory sustainability reporting requirements from the start of next year, pending passage of related legislation. As is the case in other geographies, such as the EU, extra time is being afforded to smaller organisations.
The government’s most recent guidance suggests that climate disclosure standards will be drafted by the Australian Accounting Standards Board (AASB) as early as August, “prior to the commencement of reporting requirements”.
But the government has also previously positioned its rules as a bare minimum — with a clear expectation that organisations do more with sustainability data than only what’s necessary. It wants to “encourage high-ambition approaches by firms, institutions and entities, including where these go beyond baseline standards established by regulation and policy”.
The policy shift in Australia reflects a global increase in demand for environmental, social and governance (ESG) metrics and reporting.
The change isn’t anything new for listed companies, which must already produce sustainability reports “as a condition for access to capital”. But the 2300-odd ASX-listed companies represent a small fraction of Australian organisations to which mandatory rules will apply.
Some Australian organisations have also previously reported voluntarily. These efforts are commendable but lack standardisation in formatting and disclosures, so will likely have to change to meet more stringent requirements.
Any change in ESG reporting and disclosure requirements on organisations will be felt acutely at the data level. It is necessary to collect and analyse a large amount of data to populate and produce sustainability reporting, yet many current methods are unlikely to scale to meet the increased reporting requirements that Australian organisations face.
Collecting and modelling sustainability data has traditionally been time-consuming and complex. For organisations, it’s not just about measuring their own direct CO2 emissions, but also those generated in the upstream and downstream supply chain. Not every organisation in that chain has the same level of capability or data integrity to be able to do that accurately. Some of the estimates produced as part of voluntary efforts are imprecise and unlikely to meet audit standards.
Some industries, such as banking and finance, face more specific types of scrutiny than others around what businesses they invest in, and how that investment profile exposes them to emissions-related risks.
Given uncertainty about when and in what form enabling legislation may pass parliament, there may be a temptation for organisations to put off ESG data-related works until later in the year. However, this approach may place the organisation in an unnecessary time crunch. Since it’s not a case of if but when for mandatory ESG reporting requirements to be imposed, it makes sense to take action today to set up data reporting and modelling capabilities to meet tomorrow’s reporting and corporate responsibility requirements.
Managing a revamped ESG reporting process
Leading organisations in the space are looking to a combination of graph database technology and a digital twin to manage the complexity of the entire ESG reporting process.
In recent years, databases based on graph technology have established themselves as the solution when it comes to storing and retrieving vast amounts of data and analysing their complex relationships. This is mainly due to the fact that graph databases completely link the stored data with each other. They consider the relationships between data points (edges) to be just as important as the data points themselves (nodes).
To understand how this works, think of a graph database as a metro map: the nodes are the stops and the edges represent the tracks between stops. An algorithm runs through these nodes and edges, just like a train travelling from stop to stop. This allows the graph to understand what connects entities.
The system of edges and nodes makes graph databases transparent, dynamic and almost infinitely scalable. New data can be added and queried in real time. This allows organisations to realistically model large volumes of heterogeneous data. Simple knowledge databases with flat structures and static content can hardly achieve this.
In order to utilise graph technology comprehensively for ESG reporting, it’s worth using it as a framework for a digital twin. This allows organisations to model huge real systems in real time and map reality as accurately as possible. In this way, many different parameters such as CO2 emissions, workforce diversity or investments can be monitored.
A graph-based digital twin can also be used to map the entire value chain with all its data. This results in a fully contextualised view of each unit in the value chain. With just a few clicks, it is therefore possible to recognise the extent to which unit X contributes to emissions, whether regulations are being complied with or whether there are critical dependencies. Paths with the lowest CO2 emissions, potential sources of error or the causes of excessive emissions can also be identified.
In practice, the combination of graph technology and digital twin can be used to analyse both direct and indirect emissions. Furthermore, the technology provides the ideal basis for simulations of various ESG-relevant scenarios and for a semantics-based recommendation system for ESG documents.
All of this can save businesses valuable time, helping to ensure compliance with all legal and high-ambition ESG requirements, securing an enterprise’s own future and, more importantly, the planet too.
Peter Philipp, General Manager – ANZ at Neo4j.
Top image caption: iStock.com/Eoneren
