The largest country in Northern Europe, Sweden, is famous for many things, from the beautiful sceneries, historical sites, food, and liberal culture. Remarkably is the environmental consciousness that runs through most of its citizens and residents. The clean streets and green sites say a lot about how well the Swedish know the value of natural resources, and this is evident in their adoption of renewable energy on a large scale.
Renewable energy in Sweden has developed over time, majorly from hydropower and bioenergy. This growth can be linked to the availability of moving water and biomass from its 63% forest cover. The topography also encourages the use of hydropower. In addition, there are 3600 wind turbines scattered all around Sweden capable of powering 30,000 homes. Wind power constitutes 17% of the renewable energy used in Sweden.
As of 2019, the supply of power in Sweden was primarily from hydropower plants in the northern region of Sweden and nuclear power plants in the southern. Southern Sweden is busier and requires more power than their nuclear power plants can provide, so the northern region generates more power for the south.
The Growth of Renewable Energy in Sweden.
Sweden has been making significant efforts to invest in renewable energy and utilize it for day-to-day activities. Currently, up to 54.6% of the energy used in Sweden is from renewable energy sources. In 2016, the world’s first electrified road was opened in Sweden, they also use waste, biomass, solar power, wind power, and hydropower more than most countries.
Sweden was the first country to meet its renewable energy targets set by the European Union (EU) for 2020. This was achieved eight years ahead of time due to the continuous input to renewable energy and efforts to sustain it. The government of Sweden seeks to make the country climate neutral by 2045 and hopes to achieve 100% renewable energy by 2040. While hydropower (45%) and nuclear power plants (30%) take the lead (more than 75%) in the generation of renewable energy-based power, wind turbines come in third, before bioenergy and solar power.
Bioenergy sources have a significant growth in Sweden. They sometimes run out of biowaste and have to import to meet their needs. Power generated from biowaste is usually used for heating, which is a very significant need in Sweden. Up to 93% of residential and 83% of commercial buildings get their heat generated from biofuel and waste through the district heating sector.
Who/What is driving the growth of renewable energy in Sweden? Many factors are associated with the demand for power by industries, supportive policies, and the quick adoption of renewable energy technologies. The industrial sector of Sweden is a large one, needing a lot of power supply continuously. With the availability and development of renewable energy, the Swedish government can do a lot to meet the targets ahead.
Policies Aiding The Growth Of Renewable Energy In Sweden
The high carbon taxes and cheap energy prices are helping the growth of renewable energy in Sweden. However, climate change has been a great concern as many industries in Sweden are capable of carbon emissions. The carbon tax has been an excellent way to address the issues of emissions in Sweden and give incentives and opportunities for renewable energy alternatives. It is levied on all forms of fossil fuel relative to their carbon content.
Also, the Swedish Energy Agency, which has existed since 1998, was recently commissioned to find strategies to include more solar power in the mix to make the 100% renewable energy target for 2040. Furthermore, the Swedish Environmental Protection Agency and the Swedish Energy Agency have been developing national strategies to build sustainable wind power.
Ongoing Renewable Energy Projects in Sweden
Renewable projects continue to spring up in Sweden. An example is a partnership between Uniper Engineering and Fortum eNext in three projects relating to Nordic hydro and physical trading optimization, hydrogen, and wind and solar development. They plan to complete it in 2025 and have gone past planning the coming together to offer services to utilities and energy-intensive companies.
Vattenfall, a government-owned company, also announced in 2019 to upgrade the hydropower plants and increase their capacity to 600 megawatts by 2023. It is very significant to Sweden’s goals for renewable energy, and the output is almost equivalent to that of 100 wind turbines. Currently, up to 20 power plants have been upgraded, and 450MW more have been generated already.
More so, in Ludivika city, 48 apartments have been linked as prosumers forming an energy community. Each has solar photovoltaics, thermal energy storage devices, and heat pumps to constantly use and produce renewable energy. In addition, despite being more of a collection of 1970 houses, they have smart meters which function effectively for an efficient power supply.
Experts’ Predictions on Renewable Energy in Sweden
With the impact of COVID-19 in 2020 and the trends of events, forecasts predict a CAGR of 2% in the Swedish renewable energy market by 2025. This prediction is due to policies and initiatives that are in support of renewable energy. Also, hydropower is likely to dominate the market as more upgrades are being planned and organized. However, experts also feel that the maintenance of renewable energy systems would limit the market.
There may have been concerns on how Sweden would handle the fluctuations in power from renewable energy, but these concerns are now being addressed. Sweden is known for its fast adaptation to technologies, and this has helped them grow. So far, the risks associated with diving into new technologies have been properly managed and implemented in the proper management of renewable energy systems.
With the recent push to integrate renewable energy into the existing energy infrastructures, it is becoming clear that there is a need to adjust its operation mode. This need is apparent because most renewable energy sources depend on the weather and are not easy to predict or plan with. Moreover, the power generated from such sources as wind energy and solar energy is highly stochastic. This situation calls for the application of advanced technologies for renewable energy forecasting and scheduling.
Renewable energy forecasting helps foresee what changes are expected in the amount of energy that will be generated in the future. This prior knowledge is informative for energy suppliers to plan the input they put into generating systems. Renewable energy scheduling also works side-by-side with forecasting because it is mainly determined by the predictions made by the energy forecasting models.
How renewable energy forecasting and scheduling work
Recent advancements in artificial intelligence have improved the job of weather forecasting (done by meteorologists) through machine learning. As a result, grid operators can leverage machine learning techniques to determine the amount of renewable energy that will be used and purchased by consumers at a particular time.
Machine learning (which is used for renewable energy forecasting) works because a software system learns patterns from recent data and develops an improved analysis for the future. In order to achieve this, a forecasting model is designed to fit a particular situation over several days. In addition, the data collected must be valid, accurate, reliable, consistent, and complete to be effective.
What You Should Know About Renewable Energy Forecasting And Scheduling
Here are five important things about renewable energy forecasting and scheduling you should know;
1. Renewable energy forecasting is built around short-term forecasting
Forecasting can be done with different horizons: short, medium, and long-term. Short-term forecasting involves forecasting from a few minutes to a few days ahead. It is used for day-to-day activities, and this time frame applies to renewable energy prediction.
The lead times in short-term forecasting are such that the changes in weather over a short period can be analyzed and used to predict the data to be used the next time. Renewable energy forecasting and scheduling require updated and recent data as frequently as possible, and short-term forecasting achieves that. The amazing part of it all is that there would be little or no human interruption with the presence of technology. Such way, errors would be significantly minimized.
2. Decentralized computing plays a prominent role in renewable energy scheduling.
Decentralized computing involves the allocation of both software and hardware to various points of duty. It is not like centralized computing, where all activities stem from a particular place. This form of computing (decentralized computing) is necessary for renewable energy scheduling because of the nature of locations in renewable energy generation and consumption.
For example, in an energy community, several houses may produce power at a time, and some utilities need power. The allotment of power to different places can be done effectively with decentralized computing technologies like the blockchain. It is effective because control has to happen independently from various locations when forecasting predictions require an adjustment.
3. Smart grids allow for renewable energy forecasting and scheduling.
Smart grids are electrical distribution points that are not like the conventional grid. The difference is that they contain many operation and control systems, advanced metering systems, intelligent circuit breakers and boards, and most importantly, renewable energy sources fit in well. Their operations are more efficient and can be readily evaluated because of the availability of needed information at the click of the finger. It is in such a system that renewable energy forecasting and scheduling can thrive.
Advanced forecasting models can be introduced and used to plan how the plants would run, whether solar photovoltaics or wind turbines. The ease in integration occurs because the smart grid already has smart IoT devices for thermal sensing, smart meters, phasor management networks, and the likes.
4. Grids with renewable energy attain stability easier with forecasting models in place.
Grid stability is of utmost importance for the sake of the life span of grids. Grid operators cannot consistently have variations in input and output in the grid happen repeatedly. With accurate renewable energy forecasting models, proper preparation and scheduling would be done, and there would be less frequent stability problems. Renewable energy forecasting and scheduling cut back most excesses when it comes to grid management.
5. The weather is a significant factor in renewable energy forecasting and scheduling.
Renewable energy forecasts are usually a combination of accurate weather predictions and the availability of plants and systems. The weather is a great factor, as the weather changes cause significant changes in the renewable power generated. For example, the variable speed of the wind is proportional to the amount of power generated by wind turbines. In the same way, the intensity of sun rays and the positioning of clouds play a big role in the fluctuations when it comes to solar power.
What makes renewable energy forecasting and scheduling interesting is that it studies the highly influencing factors of effective power generation. This kind of study is immediately applied, rather than just being carried out for nothing. It turns out that analyzing the weather, as Meteomatics does, has a vital role in the forecasting done by Hive Power’s Forecaster.
Renewable Energy Forecasting and Scheduling Solution – Hive Power
Hive Power’s Forecaster is one of our Flexibility Operator’s modules that performs short-term forecasting in a very accurate manner. It simply considers various factors involved in renewable energy-based power generation and uses them in forecasting. Its machine learning models make predictions on the amount of energy that would be used and generated in the future, based on previous data. This data is real-time data which is very helpful because it is used as soon as it is delivered.
Renewable energy forecasting and scheduling are essential for the effectiveness of renewable energy systems. With more observations in the needs of a renewable energy system, new technologies keep springing up, and it fosters development. Therefore, it is crucial to embrace these technologies as they come, especially when they are practical and efficient like this (in renewable energy forecasting and scheduling).
The existing energy sector has its systems and organization. The grid controls all forms of power distribution and is more like transferring power from a source to different receiving ends. However, with the inclusion of renewable energy, the need for decentralized energy resources cannot be overemphasized, and the NEMoGrid project achieves this.
Renewable energy sources are diverse, making them of various applications, and they have different capacities. Also, the amount of energy produced always needs proper regulation because of fluctuations. The NEMoGrid project aimed to make market designs that fit in, especially for energy communities. This way, optimal integration results occur with renewables on the grid.
The NEMoGrid project rounded off this past year (2020). Also, earlier this year, we conducted some evaluations. An important strategy used in this application is blockchain technology. There are nine (9) partners that synergized to make this project a success. The partners are the University of Applied Sciences and Arts of Southern Switzerland (SUPSI), Centre for Solar Energy and Hydrogen research – Zentrum für Sonnenenergie- und Wasserstoff-Forschung, Baden-Württemberg (ZSW), the professorship Cognitive and Engineering Psychology at the Chemnitz University of Technology (TU Chemnitz), Sustainable Innovation (SUST), Wüstenrot, Ngenic, Sonnen, Upplands Energi and Hive Power.
Problems Solved by NEMoGrid
Some other market models existed before the concept of decentralized energy resources used in the NEMoGrid. They had their limitations, and those particular issues became solved in the NEMoGrid project. Some of these problems include:
- Lack of flexibility in double auction markets – the double auction market is not flexible enough to regulate market participants. It involves a high number of participants who have to provide their energy forecasts and some other information. The double auction market could also easily get manipulated to the advantage of any market actor.
- The possibility of the iterative price discovery mechanism being prone to collusion – this method is highly dependent on initial declarations and capitalizes on flexibility. It is not a mechanism that can easily fish out such culprits because of the information available from the start.
How NEMoGrid Works – Decentralized Energy Resources
There are various actors in the market mechanism used in the NEMoGrid project. They include prosumers, energy communities, distribution system operators, middle actors (aggregators, balance-responsible parties, and virtual power plants), and legislators who work with energy regulators. In addition, NEMoGrid applies the distributed control theory to overcome the challenges of other market methods.
Some things influenced the choice of markets mechanisms, including:
- non-complex nature
- robust price formation
- clearing in pseudo-real-time, say every 15 minutes
Beyond meeting these, the market formulation that NEMoGrid operates considers decentralized energy resources. Its settings involve two factors – allowance for a group of end-users to control alterable loads and an independent system operator with a defined business model. These two factors make for a spread in control.
The end users can always control the usage of some devices and loads. These loads include heat pumps, electric boilers, and the likes. For being this flexible, the end-users get a reward from the distributed capital gain. The business model exploited by the independent system operator is such that it does the redistribution based on how flexible the end-users are.
Hive Power’s Role in NEMoGRid
Energy communities have a naturally decentralized structure. The structure entails the smart meters that collect, process, and store data of prosumers. Hive Power has a solution based on blockchain technology and uses its solution in the NEMoGrid project (to effectively manage this system).
The use of blockchain still encounters some challenges that limit its adoption. These challenges (such as scalability issues and privacy) are all considered in the application by Hive Power. Furthermore, with the creation of local energy communities on the blockchain, the economic and technical points of view come into play with the Hive Platform community manager module since the goal is to optimize all resources.
Milestones and Current Progress on the NEMoGrid Project
Currently, we have completed the NEMoGrid project, and evaluation is going on. You can access the results of the user research on the NEMoGrid website. The three pilots where we evaluated this project across Europe were in:
- Rolle, Switzerland
- Björklinge, Sweden
- Wüstenrot, Germany
The peer-to-peer scenario used in the blockchain market in these energy communities proved profitable and successful when evaluated.
There are seven (7) work packages involved in the NEMoGrid project managing decentralized energy resources. They include project management (WP0), the definition of future scenarios up to 2025 (WP1), market and tariff management design (WP2), the modelling framework (WP3), social acceptance (WP4), scalability and reliability (WP5), and dissemination and reporting (WP6). At this time, we have completed everything.
Also, the project received funds from the joint programming initiative, ERA-Net Smart Energy Systems focus Initiative (Smart Grids Plus), supported by the European Union Horizon 2020 research program (under grant agreement No. 646039). Also, national funding agencies supported the partners in the NEMoGrid project (Swiss, German and Swedish). These brought it to the point of being a success.
What’s Next For NemoGrid?
Adopting the solutions proffered by NEMoGrid can be extended to more applications with increasing energy communities. However, we need the stage to allow these communities to thrive and apply the flexibility of markets. The control algorithms in the NEMoGrid project, when used, will maximize the potential of these self-consumption communities.
The coming steps in the future would involve more implementation of the solutions discovered and improvements. There would always be room for additional extensions or extensive research. At the same time, the project has already put its propositions forward in a reasonable and proven manner. Any further complications or limitations in the course of usage will be recorded and worked on as part of maintenance strategies.
The Netherlands (also known as Holland in some languages, English inclusive) is known for its windmills and tulips. Its capital, Amsterdam, is a place to reckon. However, other things that make the Netherlands popular are heavily reliant on energy. As the second-largest exporter of food and beer, there are many energy-consuming set-ups. Also, there is the need to keep factories and homes up and running.
The energy sector in the Netherlands bases majorly on natural gas and oil. As of 2018, the contributions to energy generation were: 42% from natural gas, 37% from petrol, 11% from coal, 5% from biomass, and the remaining 5% shared among solar, wind, hydropower, geothermal and nuclear sources. The reliability of these sources over time seems to make them seem supposedly sustainable. However, global warming, earthquakes while producing natural gas, and climate change are still of great concern.
How far the Netherlands have come in Renewable Energy
One limiting factor to the progress in adopting renewable energy in the Netherlands is the topography. The Netherlands in its entirety is not below sea level, but a significant part of it is. This geographical situation is not welcoming to the use of hydropower.
Also, many government subsidies to invest in renewable energy existing in other countries like Denmark and Germany are not in the Netherlands. The start-up cost for renewable energy projects is high, so not many Dutch people are encouraged to go into it.
However, the status of renewable energy generation and usage in the Netherlands has recorded some progress. The amount of energy produced from renewable energy sources in the Netherlands increased from 6.6% in 2017 to 7.38% in 2018 and 8.6% in 2019. Nevertheless, the targets are still far off.
Policies Affecting the Growth of RE in the Netherlands
The law in the Netherlands has expressed concern over the light level of greenhouse gas emissions in the country. The Climate Act aims at reducing greenhouse gas emissions in the Netherlands by 49% by 2030 and 95% by 2050. For this to be met, some projects are ongoing, majorly for offshore wind turbine applications. Also, the Dutch government policy on renewable energy includes a plan to close the only nuclear power plant in the Netherlands by 2024.
Lately, countries in Europe have started to work towards meeting the goals for renewable energy development. The Renewable Energy Directive in the European Union was formerly to the end that by 2020, the final energy consumption of countries in the EU would be up to 20% renewable. However, can we confidently say the same motivation pushes the Netherlands?
The target by the European Union in 2018 was to have up to 32% of total energy from renewable sources in all its member state countries by 2030. Unfortunately, the Netherlands has not attained its share. In 2017, the Netherlands produced 6.6% of its total energy from renewable energy sources such as solar and wind turbines. The target at that time was 14%, so the Netherlands failed to meet it.
Ongoing Renewable Energy Projects in the Netherlands
Even though the Netherlands is not on track for its renewable energy goals, it has started making plans to eliminate natural gas production and consumption. These plans favour the development of renewable energy. The most popular projects in the Netherlands are the offshore wind turbine projects, before solar projects. We will discuss some examples below.
- The first large-scale wind farm in the Netherlands is being revamped. Egmond aan Zee offshore wind farm is the wind farm in question. Commissioned 15 years ago (2006), it started with only a capacity of 108 MW as a demonstration project and was the first large-scale wind farm project in the Netherlands. BlackRock Real Assets closed a 4.8 billion dollars investment fund for renewable power early this year, and some of it has sponsored other projects. A part of the fund, as well, would be used to refurbish this wind farm of NoordzeeWind (owned by Shell). Once completed, it has the potential to boost the use of renewable power in the Netherlands.
- Borssele 1 and 2 is Ørsted’s first offshore wind farm in the Netherlands and is located on the Dutch North Sea. It has a capacity of 752 MW and is, therefore, the largest wind farm in the Netherlands. A highlight of this project is that its completion was in 2020, even during the COVID-19 pandemic. According to the CEO of Ørsted, it is an achievement. This project has enough power for 1 million Dutch homes.
- The collaboration between Kronos Solar Projects and Greencells in the Netherlands is currently beginning to expand. The partnership has started a new 14 MW solar project at Voorst in the second quarter of this year (2021). Greencells has been actively working in the Netherlands since 2018. The company has completed up to 332 MW projects individually and with other collaborators. Kronos Solar Projects are also renowned for its investments in solar projects up to 290 MW in more than one country.
Experts’ Projections on RE in the Netherlands
The experts have it that the total share of renewable energy that was 8.7% in 2019 would eventually increase to 25% in 2030. In the same way, experts expect that the 18% share of renewable electricity in 2019 would have increased to 75% by 2030. However, the expectation for the renewable share of energy used for heating should move only from 7% in 2019 to 13% in 2030.
Also, the growth in the renewable energy market has to take a good turn. This is because the prices of renewable energy are steadily decreasing. This decrease is likely to keep the renewable energy market sustained even without the government’s input. For example, biomass used to take up to 60.7% of the renewable energy usage in the Netherlands. However, recent investments and projects by Vattenfall, Siemens, and the likes in wind energy projects should turn things around.
As the Netherlands has shown an increasing dependence on natural gas, it shows that the country needs more and more energy sources. The Netherlands used to be a reliable exporter of natural gas decades ago but has become an importer. As developments begin to increase, the pollution of the atmosphere with emissions is also increasing. Therefore, the Climate Agreement Policies need to be looked into further.
The introduction of demand-side response meets the preferences of the consumer of energy and helps the energy supply systems to remain balanced. Even though business owners and large-scale commercial corporations were the first to take advantage of this development for the sake of profits, it has moved in its application. Consumer demand-side response is now a point of interest as Demand-side response has its advantages to both a residential consumer and a business owner.
Through demand-side response, the use of power is flexible; as the consumer, you can adjust your energy demand according to your needs. When the United States Energy Independence and Security Act in 2007 defined the term demand response, it described it as all activities related to reducing peak demand through smart pricing and metering, as well as enabling technologies. The whole idea of consumer demand-side response benefits the grid by keeping it stable.
The term Demand-side response was known as Demand-side management (DSM) after the energy crisis in 1979. Various governments wanted to effectively manage demand through different programs because of the issues that arose with energy (fossil fuel then) production. These developments happened both in 1973 and 1979. However, the only thing that is helping Demand-side management thrive now is the availability of communication tools and more technology.
How Consumer Demand-Side Response Works
A distribution grid is responsible for the conveyance of power finally to the end-users. There is a frequency at which power comes into the grid; without renewable energy sources, this frequency is easy to keep stable. You don’t need a high level of control since the power is generated using fossil-based energy sources such as natural gas and coal according to the quantity.
However, including renewable energy sources like solar and wind energy, the input rate is unpredictable. Therefore, the grid operators need the consumers’ cooperation to regulate the power flow to the grid for a reward. Based on requirements and current state, the consumer reduces his power usage and avoids wastage whenever notified.
For a large-scale business or an industrial setting, the demand-side response is very significant because the amount of valuable power that could be wasted is high. Despite their relatively small power capacity, residential consumers can also be participants in demand-side response. With the introduction of advanced technologies, operators can coordinate the demand-side response without much human input. These technologies would account for all little grits of power that accumulate to significant power.
Smart-grid applications provide real-time data to producers and consumers that help them participate in the demand-side response. They aid the effective communication between consumers and producers of electricity on how much is needed and when needed. Consumers can fix their thresholds, then adjust their usage to maximize the prices.
Applicability of Consumer Demand-Side Response
In domestic areas, homes usually have loads that use electric power. They could be:
- Base loads, which are fixed and non-adjustable to meet basic needs such as lighting and the likes.
- Schedulable loads, which are used at some points in time, usually once a day.
- Flexible loads, like water heaters and air conditioning units, are only used when needed.
A consumer can apply the demand-side response to the control of flexible loads in their house. Since they are not used all through the day, they act as virtual batteries. This power gets channelled elsewhere when they are not in use. So, for example, when the weather does not encourage the residents of a house to use the water heating system, they can decline the power supply meant for that purpose.
Technologies Aiding Consumer Demand-Side Response
Certain technologies have been developed and would continue to emerge to achieve the goals of consumer demand-side response. Simply put, they are used for various functions and carry out specific roles to balance the grids.
- Current regulators such as fuses, limiters, and breakers are necessary to moderate the current flowing in or out of a system at a time.
- Distributed intelligent load controllers use artificial intelligence techniques to regulate and manage electricity load in a building.
- Meters – conventional and prepaid meters – are used traditionally to monitor power consumption rate, usage, and units for the sake of payment according to usage.
- Improved metering systems with centralized communication provide two-way communication, inform the consumer of how much power has been used, and help them make decisions. These decisions border around how much power to pay for and use.
The Hive Platform Flexibility Manager Module has an intelligent system used for effective consumer demand-side response. As a result, consumers do not have to be concerned with the activities involved in shifting loads because advanced devices with this technology carry them out.
What the Future Holds for Consumer Demand-Side Response
The advantages businesses get while performing the demand-side responses are more than the disadvantages. Homes can also be a part of this without having to use conventional methods. Smart technologies will continue to get developed and improved till almost all homes become partakers in demand-side response.
The same way advanced metering infrastructures are taking over the metering systems, more people would be able to participate in demand-side response when the available technologies are adopted on a large scale by the grid operators. With advanced grids becoming more used soon, it would aid demand-side response. That way, we can eliminate power outages, and renewable energy would be more appreciated.
Engaging consumers of electricity will only be possible with appropriate communication between them and the suppliers of power. Consumers can make their preferences virtually when necessary or at the initial stages of installation. Also, due to the flexibility introduced in the recent technologies, they can make changes at any point in time.
Demand response is really important in grid management, and we are making efforts to make it as flexible as possible. It involves communication between a consumer or prosumer and the supplier of an electric utility. The essence of this communication is to match demand with supply and distribute power with discretion from where it is in excess to where it is needed.
The MuLDeR project is a platform where we are managing demand response. Alongside another project (the NEMoGrid project), the MuLDeR project is a project by the University of Applied Sciences and Arts of Southern Switzerland (SUPSI). While the NEMoGrid project focuses on developing market designs that would allow a smooth integration of renewable energy sources locally, the MuLDeR project uses the Hive Platform community manager module to achieve a multilevel approach to demand response.
What Are The Problems Solved by the MuLDeR Project?
Energy communities have intertwined connections and not just stand-alone ones. Also, each contributor and consumer of power is part of an effective demand response. Therefore, the goal of demand response in this application must be flexible and allow for various power inputs and coordinated responses. Flexibility in demand response applied in the MuLDeR project involves using grid-aware mechanisms to activate demand response.
Even though this project is a research project, it is already being evaluated practically in LIC (a real-life energy community project). The project seeks to solve the problems encountered in power grids at a community level by exploring the multilevel hierarchical scheme. More problems solved by the project include:
- Energy storage problems – as power is being distributed, it can now be stored along the way and allow for flexibility. This is because excesses in power supply would not be wasted but rather converted to profit by the system provided by the MuLDeR project.
- Regulation of power consumption and demand by prosumers – prosumers themselves need to be involved for them to make choices in their power consumption easily and not be restricted in applying them
- Suitability of renewable energy sources (RES) in the market – since the MuLDeR project eliminates the barrier of demand response as applicable to multiple users of renewable energy, it removes the doubt that comes with whether or not to adopt RES
- The use of actuation to achieve flexible demand response – traditional methods of communication between consumers and grid operators, are not effective for demand response. In self-consumption communities, the demand response needs to be flexible and controlled by the system more than by operators. The MuLDeR project achieves this via load actuation.
- Complicated systems from inputs of multiple agents – the MuLDeR project solves complications in self-consumption communities by extending the solution of single-level aggregators to multilevel aggregators. This extension improves the grid management system to a high standard and allows it to follow different objective functions at the different levels of the grid hierarchy.
- Synchronization of stochastic PVs (photovoltaics). The effects of the fluctuations in solar photovoltaic power generation are damaging. They have been solved in the MuLDeR project by load synchronization.
Milestones and Current Progress of the MuLDeR Project
The MuLDeR project has come a long way. A significant step along the way was the creation of a package called Gossipy. This package is infrastructural as it gives room for input from agents in the grid processes to be grouped in chats. Also, the interactions among the agents and outside information are executed according to a message-reaction paradigm.
More so, simulation and implementation in the pilot (the LIC) were already in place by the end of 2020. This simulation was achieved in July 2020 using a systemized interface that avoided any redundancy while getting scripts. It also used a python library – Krangpower – to provide modern interfaces to the necessary simulation functionalities that the project needed.
This project utilized an automated market-making mechanism to carry out pricing during the simulation. The upper hand became evident. Predictions already showed that a better financial outcome would surface even before the simulation. This advantage is because the surplus of an energy community spreads among end-users and the community manager.
Challenges With the MuLDeR Project
The MuLDeR project may have faced some challenges but always met them with effective solutions. A significant challenge was that of grid constraints. Each agent has an objective function, so these grid constraints have some influence on them. A similar limitation imposed on the maximum power at the point of coupling was to tackle this challenge. Despite the limit on power generation, it reduced the peak power of the community as well as the total costs.
Another challenge was the effect of control activities on the grid. Batteries introduced to the grid needed coordination so that they would keep having a good functioning. The project dealt with the issues resulting from control. It was by analyzing the power under control as a function of the PCC (Point of Common Coupling) power.
What Next? – Future Prospects of the MuLDeR Project
As work progresses on the MuLDeR project, it sets the future firmly on the foundation of already established results. The algorithms developed so far are for energy communities working with a market model, and the pilots are already implementing it for proper evaluation. The results of this evaluation would help us approach the problems with a better perspective.
With the solution provided by the MuLDeR project, we expect that the pilots would extend to a larger setting. This extension is such that several energy communities can cooperate and offer services to one another. Services can be offered first to the Distribution Service Operators (DSO) and then to the Transmission Service Operators (TSO). The project aims to apply its solution to a larger group of communities and prosumers.
The synergy of this project and other projects would produce industrial products that would help the energy strategy 2050. There would be more complex applications in the distribution of energy, especially when using photovoltaic systems, as time goes on. More energy communities would emerge, and flexible demand response would need to solve the problems of peak load optimization.
The Forecaster: using machine learning and weather forecasts to more accurately predict energy consumption and generation.
“It’s hard to make predictions – especially about the future.”- Robert Storm Petersen
Predicting the future might well be hard, but it’s often necessary to run the business. Energy forecasting is of primary importance in day-to-day market operations. Short-term forecasting generally involves forecast horizons that range from a few minutes to a few days ahead. Energy Suppliers and Distribution System Operators benefit from accurate predictions of power demand and generation because they can optimally orchestrate their flexible assets to achieve their business goals.
Hive Platform’s Forecaster module computes short-term stochastic forecasts of aggregated energy consumption and PV generation, using the most advanced machine learning methods available. Stochastic means that we not only predict the “shape” of the load curve over time but also calculate confidence intervals around this curve.
Prediction intervals are essential when it comes to risk management applications, such as predicting the daily or monthly peak of consumption and efficiently activating peak shaving mechanisms.
How does it work?
There is no crystal ball (unfortunately). Instead, the Hive Platform’s Forecaster predicts future consumption and generation by learning what happened in the past and using information available from the future. The Forecaster consists of an ensemble of machine learning models trained on and continuously re-informed by a rich dataset.
The data fed into these models includes the power signal itself, numerical weather predictions (temperature, solar radiation, wind speed and direction, humidity, and heaps of other parameters), seasonality information (the time of the day, the day of the week, the month of the year, etc.), public holidays, school holidays, and custom events (lockdowns, white nights, major events, religious events, etc.).
Weather is king
Weather is by far the most important external factor affecting energy consumption and generation. For this reason, Hive Power decided to conduct an internal research study to review and select the most performant numerical weather prediction provider.
One important criterion we considered was the availability of historical weather forecasts. Many weather providers do not archive and store their predictions. However, historical weather forecasts are of crucial importance to train an energy prediction model. To be robust and reliable, a model should be trained on the same type of data that will be used at inference time.
To understand this point, think of the following. If we trained the model on actual weather observations, the model would learn to trust the weather signals to a certain level. When using this model to predict the future, we would need to replace weather observations with weather predictions, which will not be 100% accurate by definition of prediction. Hence the model will give too much weight to the weather predictions and fool itself into error.
Conversely, if we train the model on weather predictions, the model will learn to trust less the weather parameters and commit less error at inference time. Still sceptical? Try out yourself. Some of our most wary scientists did so and found exactly what was expected.
Weather forecast benchmark
We looked at about a dozen different providers, filtered out those that did not tick our boxes, and ended up with five finalists. We then asked them for a sample of their data to build a benchmark. We requested a year’s worth of hourly predictions of ground-level temperature and solar radiation generated for a single location at around midnight and covering from 24 to 48 hours ahead, which is the typical forecast horizon of our energy prediction models. We compared these predictions with actual local observations and were stunned to discover Meteomatics’ superior performance.
In the figures below, we show some results. In Figure 1, we plotted the distribution of the discrepancy between observed and predicted temperature. In Figure 2, we overlay the five distributions for a more convenient comparison. A similar situation was found for the solar radiation parameters. It was then clear to us that Meteomatics numerical weather predictions were the most accurate and well-calibrated.
Figure 1 – Distribution of the discrepancy between observed and predicted ground temperature for five different weather providers. The vertical dashed lines indicate the mean of each distribution (only Meteomatics’ mean error is centred on zero). The Mean Absolute Error (MAE) is reported on each chart (the lower, the better).
Figure 2 – The same error distributions of Figure 1 overlaid (after estimating their kernel density). Meteomatics’ curve is the narrowest and the only one that is zero-centred.
The beginning of a strategic partnership
“We were looking for a one-stop-shop that could provide us with up-to-date and detailed weather data covering Europe, which needed to be conveniently available via a RESTful API. We took quite some time to evaluate several numerical weather prediction providers. It was not an easy choice because of our demanding list of criteria, but Meteomatics checked all the boxes and exceeded our expectations. We were after a provider that covered the whole world, with a focus on Europe and especially the Alps, which are a challenging region when it comes to high-resolution weather forecasting. It was clear from our own forecast benchmarking exercise that Meteomatics was the most accurate weather forecaster, particularly over the short term. We were pleased to discover the rich plethora of standard and advanced weather parameters that Meteomatics’ API offers. We are thrilled to have switched to Meteomatics as our weather data provider of choice, and we foresee a long and fruitful partnership with them.”, said Gianluca Corbellini, Managing Director at Hive Power.
You can read more about this in Meteomatics’ latest press release: https://www.meteomatics.com/en/meteomatics-and-hive-power-agree-strategic-partnership/ .
Stay tuned for an upcoming webinar (26th of October 2021) where Hive Power and Meteomatics will guide you through an in-depth look at how numerical weather predictions inform energy prediction models.
The trend of energy usage from various energy sources in Spain tells that a revolution is growing. Merely looking at how development has moved in Spain, we see clearly that the increased consumption of energy has called for increased power generation over the years. In 2011, only 249.7TWh of 276.8TWh of the energy produced in Spain was consumed, and it was still a large amount.
Spain is currently populated by 47.1 million people, and each citizen relies on energy for their activities. Spain is the sixth-largest energy consumer in Europe and mostly has to import fuel. This is a result of the lack of abundant petroleum resources.
Generally, fossil fuel, wind, solar, nuclear, and hydroelectric energy sources are actively utilized in Spain. However, Spain is one of the countries that has started working actively to reduce reliance on fossil fuels. Right from the early 2000s, Spain has been making efforts to focus more on renewable energy. While this is major because of the adverse effects of fossil fuels on the environment, it has also brought advancements in energy management and proper utilization.
The Growth of Renewable Energy in Spain.
To date, Spain keeps making progress in the production and use of renewable energy. For a country that used to import a lot of coal and release subsidies for the cause, the new changes have a great impact on the economy. Some highlights in the trend of events relating to renewable energy in Spain are listed below.
- The global recession in 2008 significantly reduced the power generation rate in Spain by 11%, yet the market keeps bouncing back.
- Significant progress has been made in the generation of power from renewable energy. On barely comparing 2016 and last year, we see the difference is clear. Despite the COVID-19 outbreak, renewable energy generation in 2020 was 43.6% of gross electricity generation, which is an improvement from the 39% produced in 2016. In the newsletter by the Spanish grid operator – Red Electrica de Espana – it was recorded that this was the highest recorded so far.
- Wind energy has become a major part of the renewable energy sector, but solar photovoltaics are still coming up, despite the vastness of solar resources. Last year (2020), the reduction in overall power demand did not stop renewable energy sources from flourishing.
The Challenges Facing Renewable Energy Policies in Spain
Spain had set a target in 2014 to be met for renewable energy by 2020: 42.6% of total electricity generated. Moreover, in 2018, the goal has been increased to 70% by 2030. Consequently, the renewable energy regulations in Spain also say that emissions must be reduced by 20%.
Even with all of these bright sides, a major challenge to the effective use and implementation of renewable energy in Spain is the lack of resources, successive change in governments, and so much reliance on government as regards renewable energy. As governments change, policies have changed.
Despite the situation, the European Union approved a support scheme earlier this year to support energy-intensive companies in Spain. This scheme, which is set to run till December 2022, is a great investment. Their government would carry out more projects, and renewable energy will be of great benefit to the energy status of Spain. This was done under EU state aid, and it is truly of great help.
Ongoing Renewable Energy Projects and Initiatives in Spain.
These projects reflect a deep commitment to development and sustainability. Solar and wind power generation have the highest percentage of renewable energy in Spain. Some examples of projects and initiatives on each (solar and wind power) are highlighted below.
1. Total Solar Project in Spain
Total Energies is planning to thrive on the promising solar market in Spain. Total is currently planning to enter the solar market via partnerships. Two partners have agreed on the two gigawatts (2GW) solar projects – Powertis and Solarbay Renewable Energy. This project would make a great impact on the renewable energy sector of Spain.
The partnership between Total Solar International and Powertis is a 65%-35% one that would need Powertis to bring a pipeline of 800MW. This project started last year. Also, Total is obtaining all 1.2GW portfolio of projects by Solarbay. The projects are all to end by the latest 2023.
2. Wind Power Generation by Various Companies – Enel Green Power’s Wind Farm
Certain suppliers of wind energy in Spain (Gamesa Eólica, Alstom Wind, Acciona Energy, Iberdrolla, MTorres, and the rest) are still going strong in their operations. As of 2015, Spain became the fifth biggest wind power producer in the world. Producing up to 48,118 GWh of power from wind turbines that year, which formed 19% of the total power generated.
Enel Green Power is currently building a wind farm in Spain with an investment of €181 million ($220 million). This project would feature 43 wind turbines and can generate up to 471GWh of clean energy. The project aims to meet one of the major goals of renewable energy development – reducing carbon emissions. Consequently, when this project comes fully up by next year as we expect, it will offset up to 385,505 tonnes of carbon emissions. This is a big one for the progress of renewable energy in Spain.
For a study period of 2020-2026, experts have it that the CAGR of the renewable energy market in Spain would be more than 6%. This is a result of encouraging government policies and the need to reduce climate-damaging emissions.
Solar power installations are projected to be up to 30GW by 2030. This would be significant in moving renewable energy in Spain forward. Also, the market of offshore wind power has remained untapped and would give opportunities in the next ten years.
Optimistically, another projection for Spain is the tendency to outdo the predictions for renewable energy additions. Argus’ monitoring of proposed wind projects envisions a higher level of wind power generation in a few years.
Spain has come a long way and can fight through its challenges for the sake of improving renewable energy. From the generation of power to utilization, the energy stakeholders in Spain need to maximize available resources and smart grid technologies to meet up with the bright future catching up with the rest of the world.
Meteomatics and Hive Power Agree Strategic Partnership: Bringing machine learning to more accurately predict energy consumption and generation.
Meteomatics AG is a private weather business, making a rich database of weather information (>7 Petabytes) and weather insights available to users across the globe. Meteomatics provides incredible detail and accuracy with weather forecasts downscaled to 90 meters and up to 5 minutes temporal resolution, globally. All through an easy-to-use RESTful API endpoint.
Providing downscaled forecasts at 90-meter resolution and up to 5-minute temporal resolution for anywhere on the planet, were very important reasons why Hive Power chose to switch to Meteomatics.
Hive Power is a smart grid analytics company with a strong focus on creating innovative solutions to improve grid operations for energy suppliers and grid operators through data-driven artificial intelligence. One of their innovations is the Hive Power Forecaster which computes stochastic energy forecasts to simplify how energy retailers and grid operators manage the aggregated energy production and consumption.
“We were looking for a one-stop-shop that could provide us with up to date and detailed weather data covering Europe, which needed to be conveniently available via a RESTful API. Hence why we were very excited about partnering with Meteomatics, and the commercial possibilities Meteomatics’ API could generate for Hive Power. We took quite some time to evaluate several numerical weather prediction providers. It was not an easy choice because of our demanding list of criteria, but Meteomatics checked all the boxes and exceeded our expectations. We were after a provider that covered the whole world, with a focus on Europe and especially the Alps, which are a challenging region when it comes to high-resolution weather forecasting. It was clear from our own forecast benchmarking exercise that Meteomatics was the most accurate weather forecaster, particularly over the short term. We were pleased to discover the rich plethora of standard and advanced weather parameters that Meteomatics’ API offers. Moreover, Meteomatics was one of the few providers that easily allowed the retrieval of archived historical weather forecasts, which are of critical importance to correctly train our machine learning models. We are thrilled to have switched to Meteomatics as our weather data provider of choice, and we foresee a long and fruitful partnership with them.’’, said Gianluca Corbellini Managing Director at Hive Power.
Meteomatics Weather API allows Hive Power to inform and enrich their proprietary energy consumption and production forecasting models. Powered by the latest and most advanced machine learning techniques, Hive Power’s Forecaster computes short-term probabilistic predictions to simplify how energy retailers and grid operators manage the aggregated energy production and consumption. Accurate energy predictions are crucial for effective peak-shaving, performant energy trading, robust grid stability and avoidance of congestions.
Meteomatics unique approach to forecast downscaling allows Meteomatics’ API to resolve the challenges local topography can bring to weather, enabling Meteomatics to achieve a very high degree of forecast accuracy. Plus, the breadth of Meteomatics’ weather database covering all forecast timescales: historical data (from 1979), nowcasts, forecasts, probabilistic and seasonal, allows agricultural businesses to improve operational efficiencies and forecast yields.