The liberalization of electricity markets and the transformation of electric power systems to include large amounts of variable output generation, has led to a growing interest in flexible demand and demand response. Making demand response available on the wholesale market on a large scale is a challenge. Retailers and aggregators, providing services to individual consumers as well as bringing aggregated flexibility to the wholesale market, is foreseen to play important roles in this respect. This paper presents a aggregator decision support model for demand scheduling, including demand response and purchase bid optimization for day-ahead markets. Income from providing electricity to consumers, and costs related to imbalances, rescheduling and energy not served are also considered. The model includes risk management by applying the conditional value-at-risk risk measure. The feasibility of the developed model is validated through a case study using historical data from the Swedish power system and market.

Trends visible today suggest that a transformation of industrial firms’ use of electricity, and a change in their role in the electricity system, could take place as a part of a long-term transition towards a low-carbon Swedish economy. The shape of these changes remains highly uncertain, but electrification, flexible electricity use, and emerging roles in the electricity system for industrial consumers are interdependent developments and should be investigated from a holistic perspective where possible.

Swedish industry is relatively energy intensive, and has stood for roughly 37% of the country’s electricity use for a decade. The Swedish Energy Agency’s Vivace scenario suggests that this share could expand, despite improved efficiency, to 49% by 2050. The increased use of electricity to reduce greenhouse gas emissions and take advantage of market conditions would play out differently in different sectors, and depending on the development of different technologies. However large-scale opportunities may exist in the long-term, such as using electrolysis to produce hydrogen for replacing coke in the iron and steel industry and as a feedstock in the petrochemical industry.

Smaller-scale but still important options for electrification include electric/hybrid boilers in the pulp and paper industry and a variety of electro-thermal technologies for heating and drying.

Increased use of electricity in industry is likely to go hand-in-hand with increasingly flexible use of electricity. In some cases, such as the production of hydrogen or process media, this flexibility will be in-built since the storable energy carriers create new production planning options. In other cases, new approaches to planning, process design, and the use of automation may allow firms to match electricity use to favourable market conditions.

The expected high penetration of intermittent renewable electricity in the power system may create incentives for this flexibility. These incentives should appear on the wholesale market, in the form of high- and low-price periods. They may also appear via new capacity markets, or through markets for new system services needed to support stability in both transmission and distribution networks. The frameworks and regulations needed to create these markets are not yet in place, and firms will also need to develop technical and management capabilities to take advantage of them.

I och med omställningen till ett energisystem med en större andel förnybar el står elmarknaden inför flera utmaningar. Traditionella kraftslag som kärnkraft är ofta styrbar, men förnybara kraftslag som vindkraft är väderberoende. En ökad mängd förnybar produktion kan därmed innebära ett ökat behov av fysisk handel närmare leveranstimmen. Intradagmarknaden är en marknad för fysisk handel mellan leveranstimmen och dagen före marknaden, där majoriteten av all handel sker. Den planerade expansionen av förnybara kraftslag är en indikation på att intradagmarknadens betydelse kommer att öka. Av den anledningen är det viktigt att de aktörer som direkt eller indirekt kan påverka eller påverkas av intradagmarknaden har en god förståelse för dess funktion. Den här rapporten beskriver intradagmarknadens funktion och roll i elhandelssystemet.

Recent developments in the electric power sector as well as in district heating and cooling systems has led to an increased interest in local energy systems and markets. In the electricity sector, this is driven by the integration of distributed resources such as solar power, electric vehicles and demand response. For district heating, sustainability and energy efficiency targets drives the development to further exploit small-scale heat sources. A closer integration of these energy carriers can also unlock potential flexibility, to the benefit of local as well as overlaying systems. In this respect, there is a need to further explore the possibilities to design local energy markets to facilitate the integration between electricity and district heating, as well as providing adequate instruments enabling flexibility. This paper therefore presents a market clearing design, based on optimization, for local energy markets incorporating multiple energy carriers and bid structures suitable for representing flexibility. The market clearing model is applied in a case study to illustrate and validate key design elements. One conclusion is that even though various elements can be added to the market clearing function, there is a challenge to interpret the results due to an increased complexity of the resulting optimization problem. 

The transition of the electric power system to reach sustainability goals leads to new market conditions with larger uncertainties. This constitutes new challenges and opportunities for new as well as for existing market players such as retailers. In a future more volatile and unpredictable market, financial risk management becomes an important element for such actors in order to achieve viable businesses. Different instruments can be applied for this purpose, where demand response can contribute in the short-term to manage risks related to price variations and imbalance costs. This study contributes to the enhancement of retailer's businesses by presenting a stochastic optimisation model exploring the possibility to apply demand response to control financial risk exposure. The model considers trading and demand response scheduling for different customer clusters, generating optimal trading volumes for day-ahead markets while also considering the possibility to trade intra-day. The optimisation considers uncertainties in prices and loads as well as imbalance settlement costs. Risk management is integrated into the model by applying conditional value-at-risk as risk measures. The developed model has also been applied in a case study with data from the Swedish and Nordic electricity market together with simulated load profiles for different customer clusters. 

RISE Research Institutes of Sweden is a group of research and technology organisations. RISE is a leading innovation partner working global cooperation with academia, enterprise and society to create value, growth and competitiveness through research excellence and innovation.

In the area of Energy, RISE has developed innovation Roadmaps covering:

• Energy Efficient Transport
• Electric Power System
• Energy Efficient and Smart Buildings
• Sustainable Thermal Processes
• Efficient Energy Use in Industry
• Decarbonisation of Basic Industries

These Roadmaps describe development pathways for technologies, non-technical elements (market design, user behaviours, policies, etc.) and key actors that deliver on a plausible, desirable vision for each respective innovation area in 2030. These Roadmaps are intended to support RISE’s strategic planning and development, but should be relevant reading for anyone interested in energy innovation in Sweden.

A decentralization of electricity markets, with an introduction of smaller local marketplaces, is sometimes suggested as a suitable development when a growing share electricity generation comes from distributed sources. This paper presents a stylized model for comparing market outcomes between a decentralized and a centralized market structure, focusing on the effect that forecasting errors have on market outcomes. Using Monte Carlo simulations, it is shown that forecasting errors propagate into somewhat larger scheduling errors under a decentralized market structure.

Deliverable 3.1 i EU-projektet S3C. Se www.S3C-project.eu

Deliverable 3.1 i EU-projektet S3C. Se www.S3C-project.eu