Active residential customer in a flexible energy system — a methodology to determine the customer behaviour in a multi-objective environment
Belonogova, Nadezda (2018-12-05)
Väitöskirja
Belonogova, Nadezda
05.12.2018
Lappeenranta University of Technology
Acta Universitatis Lappeenrantaensis
School of Energy Systems
School of Energy Systems, Sähkötekniikka
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Julkaisun pysyvä osoite on
https://urn.fi/URN:ISBN:978-952-335-307-7
https://urn.fi/URN:ISBN:978-952-335-307-7
Tiivistelmä
The transformation from passive into active end customers in modern energy systems has already started in many European countries, and it is a long process. The first step to engage residential customers to be active actors is to demonstrate the benefits that active participation in demand response in electricity markets can provide.
The operating environment of electric power systems and markets is evolving. The value and need for flexibility is increasing as the climate change is pushing intermittent renewables into the electricity grid at all voltage levels. At the same time, requirements regarding the security and reliability of power supply, along with cost-efficient and sustainable solutions, are tightening. One way to cope with these pressures is to adjust the electricity consumption to the variable generation. That is why the role of a single residential customer will be invaluable in the future energy system. Flexibility is required in electricity markets and ancillary services of many kinds. These will be referred to as demand response marketplaces.
Active customers located in the changing operating environment face challenging decisions: what flexibility options do they have now and what should they have in the near future? When, at which price, and in which time should these flexibility resources be offered to the smart grid environment so that the customers will benefit most?
Here, the role of the regulatory framework is crucial to channel the residential demand response in a predicted way; to be specific, how to direct the active customer behavior in a way that satisfies the interests of the customers and the involved stakeholders of the energy system.
To address the above questions, this doctoral dissertation aims to solve the complex decision-making problem of an active customer in the evolving operating environment. The main contribution of the work is the established methodology that can be implemented to any type of residential customer located in any operating environment. The proposed methodology is divided into two stages. The first stage determines the most promising demand response marketplaces for the end customer from a list of marketplaces. The second stage aims at defining the optimal operating strategy in the selected marketplaces. Thus, the methodology provides tools to solve the complex decision-making problem of a single customer in the environment of multiple demand response marketplaces.
Another contribution of the dissertation is the simulation tool created on the basis of the methodology. The input data used in the simulations consisted of the automatic meter reading (AMR) data of 10 000 residential customers located in the Nordic electricity market environment. The results of the simulation tool give indications of the customer behaviour in the near future. This, in turn, is an important input for regulatory and decision-making entities to provide the customers with demand response services that
both meet their interests and satisfy the interests of the energy system and electricity market operators.
The operating environment of electric power systems and markets is evolving. The value and need for flexibility is increasing as the climate change is pushing intermittent renewables into the electricity grid at all voltage levels. At the same time, requirements regarding the security and reliability of power supply, along with cost-efficient and sustainable solutions, are tightening. One way to cope with these pressures is to adjust the electricity consumption to the variable generation. That is why the role of a single residential customer will be invaluable in the future energy system. Flexibility is required in electricity markets and ancillary services of many kinds. These will be referred to as demand response marketplaces.
Active customers located in the changing operating environment face challenging decisions: what flexibility options do they have now and what should they have in the near future? When, at which price, and in which time should these flexibility resources be offered to the smart grid environment so that the customers will benefit most?
Here, the role of the regulatory framework is crucial to channel the residential demand response in a predicted way; to be specific, how to direct the active customer behavior in a way that satisfies the interests of the customers and the involved stakeholders of the energy system.
To address the above questions, this doctoral dissertation aims to solve the complex decision-making problem of an active customer in the evolving operating environment. The main contribution of the work is the established methodology that can be implemented to any type of residential customer located in any operating environment. The proposed methodology is divided into two stages. The first stage determines the most promising demand response marketplaces for the end customer from a list of marketplaces. The second stage aims at defining the optimal operating strategy in the selected marketplaces. Thus, the methodology provides tools to solve the complex decision-making problem of a single customer in the environment of multiple demand response marketplaces.
Another contribution of the dissertation is the simulation tool created on the basis of the methodology. The input data used in the simulations consisted of the automatic meter reading (AMR) data of 10 000 residential customers located in the Nordic electricity market environment. The results of the simulation tool give indications of the customer behaviour in the near future. This, in turn, is an important input for regulatory and decision-making entities to provide the customers with demand response services that
both meet their interests and satisfy the interests of the energy system and electricity market operators.
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