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Role of consumers in a renewable power system

Are you willing to support the integration of renewable energy? But are you willing to pay a higher electricity price for that? If you are willing to contribute to a greener energy supply, but not on the cost of your personal economy, then there may be yet another chance for you to help make a chance towards a greener tomorrow.

FoES forskningsprojekt - Flexibla el-kunders roll i ett framtida förnybart kraftsystem

We all know that we should shift towards a society of decreasing carbon dioxide emissions. By far the largest source of greenhouse gas emissions is found in the power generation sector. The industry has historically been based on fossil fuels (coal, lignite, oil and natural gas) that offer many short-term benefits such as a high energy density, good predictability and controllability.

The goal of the project

The goal is to use the given resources more efficiently in order to integrate renewable energy without increasing the cost for us as individuals. If we want to facilitate a renewable driven power system, the primary goal must be to synchronize generation and consumption at all times. Our research provides insights into the time dependent elasticity of consumers. We investigate both the willingness (behavioral economics) and the capability (technical) of consumers to react to incentives from the system operator, and thus help to integrate renewable energy.

Project results

Power systems with increasing shares of renewable energy sources require sufficient flexibility sources. One source of flexibility for future power systems is constituted by flexible electric loads. The concept of demand response captures the utilization of demand side flexibility to provide services to the power system.

For this purpose, actors on the market, such as retailers, distribution system operators, and aggregators, have to evaluate how to interact or develop their current interaction with electricity customers. This development is studied from a current or near future perspective, as well as from the long-term perspective, to be able to investigate the actors’ strategic options.

For a demand response provider, the most economic means of providing flexibility in wholesale electricity markets is to participate in several markets simultaneously and thereby provide multiple services. With a focus on the Nordic electricity markets, the simultaneous provision of energy arbitrage and frequency reserves poses as the most economic market portfolio for a demand response provider with storage type assets. Specifically, the methods developed in the first part of this project model a risk-averse demand response provider that aims to maximize its profit on the day-ahead by placing bids on the energy and frequency reserve markets. Furthermore, the second part of this project investigates customer attitudes and expectations with a mixed methods approach, to understand how the actors’ strategic options may affect different customers’ flexibility.

The operational business of a demand response provider is illustrated by stochastic optimization of day-ahead bids under uncertainty from prices, temperatures, behavior, and model error. A general virtual battery model for simultaneous bidding in multiple day-ahead markets is developed for three applications; thermostatically controlled loads, electric vehicles, and a pulp and paper mill. Through application of the models to power system, price, temperature, and load data, the power and energy flexibility of the three studied load types are quantified. This research provides decision support tools for demand response providers that participate in energy and frequency reserve (FCRN) markets. The main focus of the developed algorithms is to facilitate optimal day ahead bids for a risk-averse demand response provider under various sources of uncertainty. Additionally, the sensitivity to market timing, such as lead time and contract period, is investigated.

Actors interacting with electricity customers may have a challenge in managing the future interaction with customers that have very different ideas on how their flexible electricity use will be tapped into. With households and electricityintensive companies being the extremes among customers, the actors’ management of the interaction with the two types is not very different today. At least not when compared to the future scenarios for how interaction with electricity customers may develop. The interaction is complicated by the actors’ need to implement dynamic elements in their offers and their need to integrate with electricity customers over new information and communications technology. For electricity-intensive companies, integrity may be a limit to their flexibility, while integrity may be a temporary obstacle for the integration of technology with other customers.

Read Final Report here

Publications

Doctoral thesis

Lars Herre (2020). Demand Flexibility for the Simultaneous Provision of Multiple Services: Tapping the Potential of Controllable Electric Loads for Frequency Reserves and Energy Arbitrage.

Journal Articles

L. Herre, J. L. Mathieu and L. Söder, "Impact of Market Timing on the Profit of a Risk-Averse Load Aggregator," IEEE Transactions on Power Systems, 2020.

L. Herre, S. Kazemi and L. Söder, "Quantifying Flexibility of Load Aggregations: Impact of Communication Constraints on Reserve Capacity," IET Generation, Transmission & Distribution, 2020.

L. Herre, F. Tomasini, K. Paridari, L. Söder and L. Nordström, "Simplified Model of Integrated Paper Mill for Optimal Bidding in Energy and Reserve Markets," in Applied Energy, 2020.

L. Herre, B. Nourozi, M. R. Hesamzadeh, L. Söder and Q. Wang, "Provision of Multiple Services with Controllable Loads as Multi-Area Thermal Energy Storage," under review in IEEE Transactions on Power Systems.

L. Haglund, T. Kovala, and C. Lindh, “Managing complexity through business relationships: the case of the Swedish electricity market”, Int. J. Management and Decision Making, vol. 18, no. 2, pp. 209–227, 2019.

L. Herre, T. Matusevicius, J. Olausson, L. Söder, "Exploring Wind Power Prognosis Data on Nord Pool: The Case of Sweden and Denmark," IET Renewable Power Generation, 2019.

I. Dimoulkas, P. Mazidi and L. Herre, “GEFCom 2017: A simple neural network based approach to long-term probabilistic load forecasting," International Journal on Forecasting, 2018.

T. Kovala, F. Wallin and A. Hallin. “Factors influencing industrial excess heat collaborations”, Energy Procedia, 2016, 88: 595-599.

Conference Papers

L. Herre, "Impact of Imbalance Settlement System Design on Risk-Averse Energy Storage," (in 17th International Conference on European Energy Market, 2020, pp. 1-6.

Khodadadi, L. Herre, P. Shinde, R. Eriksson, L. Söder and M. Amelin, "Nordic Balancing Markets: Overview of Market Rules," in 17th International Conference on European Energy Market, 2020, pp. 1-6.

L. Herre, "Risk-Averse Aggregator of Controllable Loads as Virtual Battery Providing Multiple Services," in 17th International Conference on European Energy Market, 2020, pp. 1-6.

L. Herre, F. Tomasini and K. Paridari, "Optimal Day-Ahead Bidding of a Risk-Averse Pulp and Paper Mill in the Energy and Reserve Market," in 16th International Conference on European Energy Market (EEM), Ljubljana, 2019.

L. Herre, J. Dalton and L. Söder, "Optimal Day-Ahead Energy and Reserve Bidding Strategy of a Risk-Averse Electric Vehicle Aggregator in the Nordic Market," in 13th IEEE PowerTech 2019, 23-27 June, Milano, Italy, 2019.

J. Dalton, L. Herre, L. Söder, "Exploring the Business Case of a Risk-Averse Electric Vehicle Aggregator in the Nordic Markets," in 2nd e-Mobility Integration Symposium, Stockholm, 2018.

L. Herre, J. Mathieu, L. Söder, "The Flexibility of Thermostatically Controlled Loads as a Function of Price Notice Time," in 20th IEEE Power System Computation Conference (PSCC), Dublin, 2018.

I. Dimoulkas, L. Herre, E. Nycander and M. Amelin, "A hybrid model based on symbolic regression and neural networks for electricity load forecasting," in International Conference on the European Energy Market, EEM, 2018

L. Herre, T. Matusevicius and L. Söder, "Swedish Wind Power Forecasts: Procedure, Error Distribution and Spacio-Temporal Correlation," in 16th International Workshop on Large-Scale Integration of Wind Power into Power Systems as well as on Transmission Networks for Offshore Wind Power Plants, Berlin, 2017. (Best Paper Award)

L. Herre and L. Söder, "Enhancing market access of demand response through generation forecast updates," in 12th IEEE PowerTech, Manchester, 2017.

I. Dimoulkas, P. Mazidi and L. Herre, "EEM 2017 Forecast Competition: Wind power generation prediction using autoregressive models," in 14th International Conference on the European Energy Market (EEM), Dresden, 2017.

T. Kovala, ”This electricity price is too high for my household: Why are some households sensitive to the electricity price, when others barely are sensitive at all?” [POSTER], in IMIT PhD candidate poster competition @ 5th annual conference of ScAIEM 2017, Trondheim, 2017.

L. Herre, T. Kovala, L. Söder, C. Papahristodoulou, "A Study on the Flexibility of Electricity Consumers for the Swedish Context: Modelling, Quantification and Analysis of Notice Time," in Swedish Association for Energy Economics Conference 2016, Luleå, 2016.

L. Herre and L. Söder, "On the flexibility of electricity consumers: Introducing notice time," in 13th International Conference on the European Energy Market (EEM), Porto, 2016.

T. Kovala, “Flexibla elkunders roll i ett framtida förnyelsebart kraftsystem – Hur kommer framtidens elkunder besluta om sin elanvändning?” [POSTER], in HUB 2016, Västerås, 2016.

T. Kovala, ”Deciding about electricity usage: A thesis on market incentives to steal focus from electricity consumers”, in Arctic PhD workshop at the 4th annual conference of ScAIEM 2016, Luleå, 2016.

F. Wallin, D Torstensson, T. Kovala, A. Sandberg, “Using an energy intervention framework to evaluate end-user willingness to participate in demand-response activities”, in IEEE Power and Energy Society (PES) General Meeting 2016, Boston, 2016.

T. Kovala, F. Wallin and A. Hallin, “Factors influencing industrial excess heat collaborations”, in Applied Energy Symposium and Summit 2015 (CUE2015), Fuzhou, 2015.

People in the project

Head of Research

Lennart Söder

Project participants

  • Lars Herre, PhD student, KTH, has defended his thesis
  • Cecilia Lindh, Senior Lecturer, Mälardalen University
  • Emilia Rovira Nordman, Senior Lecturer, Mälardalen University
  • Christos Papahristodoulou, Senior Lecturer, Mälardalen University
  • Fredrik Wallin, Senior Lecturer, Mälardalen University
  • Tommy Kovala, PhD Student, Mälardalen University

Project partners

  • Mälardalen University
  • KTH Royal Institute of Technology

Starting point

We all know that we should shift towards a society of decreasing carbon dioxide emissions. By far the largest source of greenhouse gas emissions is found in the power generation sector. The industry has historically been based on fossil fuels (coal, lignite, oil and natural gas) that offer many short-term benefits such as a high energy density, good predictability and controllability.

The goal of the project

The goal is to use the given resources more efficiently in order to integrate renewable energy without increasing the cost for us as individuals. If we want to facilitate a renewable driven power system, the primary goal must be to synchronize generation and consumption at all times.

How can we as individuals support this goal?

There are several household appliances that consume a significant amount of energy, and that can be shifted to different times without impacting our comfort. Examples are dishwashers, laundry machines, tumble dryers, electric heating or heat pumps and in the future, electric vehicles. Several suppliers are already today labelling these devices with “Smart Grid ready”. That means that when the market will be in place, these devices are able to exploit their inherent flexibility and shift consumption to a more favorable time in order to promote renewable energy integration.

How would this work in practice?

Let us suppose you are leaving for work in the morning, around 8.00 h and get back home around 17.00 h. After breakfast, you fill the dishwasher and set it up to run. Instead of starting immediately, the dishwasher would decide by itself when it is most favorable to run, given that it needs to be finished by 17.00 h. This simple change would not impact our personal comfort, and yet have a major impact on power system operation when accumulating all available devices.

There are further appliances that offer even more potential than dishwashers: Residential electric heating alone can be changed by 7.4 GW, which amounts to roughly one third of the total Swedish power consumption.

In order to reach the point where we, as individuals, can contribute to balancing to renewable power system, and help mitigate carbon dioxide emission, we need to have a functioning market. This market is being shaped right now and we need more information about flexibility so that this market can operate optimally, like e.g.:

  • How much consumption can you shift to a later or earlier time?
  • How much financial compensation do you need to shift your consumption? Is this different for night and daytime? (time dependent elasticity)
  • When do you want your dishwasher, laundry machine, dryer, etc. to be finished?
  • If you don’t know, then: When will you know when you will need it?
  • When will you use your electric vehicle next?
  • What is your temperature comfort zone at home?
Our research provides insights into the time dependent elasticity of consumers. We investigate both the willingness (behavioral economics) and the capability (technical) of consumers to react to incentives from the system operator, and thus help to integrate renewable energy.

Read more about FoES

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Graduate School in Energy Systems

Graduate School in Energy Systems purpose is to increase understanding of how energy system depends on the interaction between technology and society's regulatory framework, policy development and operators interests and behavior.

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