This dataset was collected to understand how Norwegian households responded to the electricity price shock due to the European energy crisis. It consists of consumer characteristics and their ...self-reported responses to the extraordinarily high electricity prices which were collected with a survey of 4,446 consumers. The consumer characteristics contain socio-demographic information, such as income, age, education, number of residents, residence type, residence size, and how conscious the respondents were about their electricity consumption. Furthermore, major electricity-consuming appliances were identified, such as whether the residents had an electric vehicle and how they heated their homes, and if they had a dynamic electricity price contract. In addition, the dataset includes hourly metered electricity consumption data covering October 2020 to March 2022 from a subset of 1,136 residential consumers of the surveyed households, the total hourly residential electricity consumption per Norwegian bidding area from July 2019 to July 2022, and the hourly day-ahead electricity prices. These data are interesting to researchers that aim to gain insight into the electricity consumption behaviour of the residential sector and the impact of different socio-demographic variables.
In recent years, power systems have undergone changes in technology and definition of the associated stakeholders. With the increase in distributed renewable generation and small- to medium-sized ...consumers starting to actively participate on the supply side, a suitable incorporation of decentralized agents into the power system is required. A promising scheme to support this shift is given by local electricity markets. These provide an opportunity to extend the liberal wholesale markets for electrical power found in Europe and the United States to the communal level. Compared to these more established markets, local electricity markets, however, neither have few practical implementations nor standardized frameworks. In order to fill this research gap and classify the types of local electricity markets, the presented paper therefore starts with the challenges that these markets attempt to solve. This is then extended to an analysis of the theoretical and practical background with a focus on these derived challenges. The theoretical background is provided in the form of an introduction to state-of-the-art models and the associated literature, whereas the practical background is provided in form of a summary of ongoing and recent projects on local electricity markets. As a result, this paper presents a foundation for future research and projects attempting to approach the here presented challenges in distribution of generation, integration of demand response, decentralization of markets and legal and social issues via local electricity markets.
While volume-based grid tariffs have been the norm for residential consumers, capacity-based tariffs will become more relevant with the increasing electrification of society. A further development is ...capacity subscription, where consumers are financially penalised for exceeding their subscribed capacity, or alternatively their demand is limited to the subscribed level. The penalty or limitation can either be static (always active) or dynamic, meaning that it is only activated when there are active grid constraints. We investigate the cost impact for static and dynamic capacity subscription tariffs, for 84 consumers based on six years of historical load data. We use several approaches for finding the optimal subscription level ex ante. The results show that annual costs remain both stable and similar for most consumers, with a few exceptions for those that have high peak demand. In the case of a physical limitation, it is important to use a stochastic approach for the optimal subscription level to avoid excessive demand limitations. Facing increased peak loads due to electrification, regulators should consider a move to capacity-based tariffs in order to reduce cross-subsidisation between consumers and increase cost reflectivity without impacting the DSO cost recovery.
•Capacity subscription grid tariff: consumers subscribe to a certain level of capacity.•Dynamic capacity subscription: demand is limited when there is grid congestion.•A stochastic approach is proposed to find the optimal subscription level.•Economic impact small for most consumers, higher for those with high coincidental peak.
There is an ongoing transition in the power system towards an increasing amount of flexible resources and generation technologies at the distribution system level. An appealing alternative to ...facilitate efficient utilization of such decentralized energy resources is to coordinate the power at the neighbourhood level. This paper proposes a game-theoretic framework to analyze a local trading mechanism and its feedback effect on grid tariffs under cost recovery conditions for the distribution system operator. The novelty of the proposed framework is to consider both long-term and short-term aspects to evaluate the socio-economic value of establishing a local trading mechanism. Under our assumptions, the main finding is that the establishment of local electricity markets can decrease the total costs by facilitating coordination of resources and thus create higher socio-economic value than the uncoordinated solution. Furthermore, a sensitivity analysis on the tariff levels reveals that there are two equilibrium solutions, one where the grid costs are exactly balanced by tariff income and one where the neighbourhood decides to disconnect from the larger power system. These results indicate that although a local trading mechanism can reduce the need for grid capacity, it may not be cost optimal for neighbourhoods to become completely self-sufficient.
•Presents a game-theoretic framework for grid tariff design under local market mechanisms.•The socio-economic value of a local trading mechanism is investigated.•A local trading mechanism pareto-dominates the situation without local trading.•Neighbourhood electricity trading can reduce the need for grid capacity.
Local energy communities and electricity markets have emerged as possibilities for interaction among prosumers. A substantial effort has been invested into creating efficient pricing mechanisms for ...various market arrangements, all of which take into consideration distinct characteristics of local electricity trading. However, since they are all evaluated in terms of various systems and market conditions, it is challenging to directly compare the mechanisms. In this research, three well-established pricing mechanisms from the literature are systematically compared and evaluated under identical settings on their influence on welfare distribution across various market participant groups, privacy protection, transparency and complexity level. According to the findings, the supply–demand ratio pricing system leads to the lowest costs for consumers and is also the most privacy compliant and transparent. Furthermore, prosumers obtain the highest cost-savings through the consensus alternating direction method of multipliers pricing mechanism, whereas the equilibrium pricing mechanism performs best regarding economic fairness. The aim of this article is to provide insight into the performance of different pricing mechanisms to energy regulators and local electricity market facilitators. The comparative analysis should aid in making informed decisions on the implementation of local electricity markets.
•A comparison of three pricing mechanisms for local electricity markets.•Assessment of welfare distribution and economic fairness among households.•A qualitative analysis of the impact on privacy, transparency, and complexity.•Supply–demand ratio mechanism excels in privacy and transparency.•Equilibrium-based mechanism has the best economic efficiency.
•Data and simulation analysis on a real and large-scale distribution power grid.•Introduction of three charging scenario to analyse the impact of EV.•20 % EV penetration with uncoordinated charging ...causes congestion.
With the considerable increase of Distributed Energy Resources (DER), reliable and cost-effective operation of distribution grids becomes challenging. The efficient operation relies on computationally dependable and tractable optimisation solvers, which may handle: 1) non-linear AC power flow constraints, and 2) time-linking variables and constraints and objectives of DER, over the operational horizon. In this paper, we introduce an application of a high-performance MultiPeriod AC Optimal Power Flow (MPOPF) solver, called “BATTPOWER”, to simulate active distribution grids for a near-future scenario. A large-scale Norwegian distribution grid along with a large population of Electric Vehicles (EV) are here taken as the case-study. We suggest and analyse three operational strategies (in terms of control of charge scheduling fleet of EV) for the Distribution System Operator (DSO): (a) uncoordinated charge scheduling, (b) coordinated charge scheduling with the objective of energy cost-minimisation without operational constraints of the grid, and (c) coordinated charge scheduling with the objective of energy cost-minimisation along with the operational constraints of the grid. The results demonstrate that the uncoordinated charging would lead to: 1) overloading of lines and transformers when the share of EVs is above 20%, and 2) higher operational costs than the proposed control strategies of (b) and (c). In strategy (b) operational line/transformer limits are violated when the populations of EVs are growing above 36%. This implies that current market design must be altered to allow active control of a large proportion of DERs within grid operational limits to achieve cost minimization at system level. To our knowledge, the work presented in this paper is the first ever attempt to do a comprehensive analysis of the impact of EV charging demand on a real Norwegian distribution grid. Moreover, the inference of the analysis says that the Norwegian distribution networks are more prone to congestion problems than the voltage problems for the EV demand which includes a smart charging scheme accounting for grid conditions.
Abstract
Neighborhoods are responsible for considerable amounts of the total energy demand in Europe, and increased shares of variable renewable energy sources will require energy balancing services. ...Local flexibility resources in neighborhoods can help provide this. However, there is a lack of insight into the economic incentives and operational consequences for property owners to adopt prosumer qualities. Using a linear program that minimizes total electricity costs, this paper evaluates annual cost savings for a Norwegian university campus when value stacking the following flexibility services: responding to electricity spot prices, grid tariffs, and provision of fast frequency reserve (FFR). Several flexibility resources are addressed in this study, including a stationary battery, electric vehicle charging stations, and a vehicle-to-grid charging station. The results found an average 6.8% yearly cost decrease by FFR participation, supporting the notion that there is a significant economic potential in applying flexible resources from prosumers in fast frequency reserve markets, without significant conflicts with other flexibility services.
The recent deployment of distributed battery units in prosumer premises offer new opportunities for providing aggregated flexibility services to both distribution system operators and balance ...responsible parties. The optimization problem presented in this paper is formulated with an objective of cost minimization which includes energy and battery degradation cost to provide flexibility services. A decomposed solution approach with the alternating direction method of multipliers (ADMM) is used instead of commonly adopted centralised optimization to reduce the computational burden and time, and then reduce scalability limitations. In this work we apply a modified version of ADMM that includes two new features with respect to the original algorithm: first, the primal variables are updated concurrently, which reduces significantly the computational cost when we have a large number of involved prosumers; second, it includes a regularization term named Proximal Jacobian (PJ) that ensures the stability of the solution. A case study is presented for optimal battery operation of 100 prosumer sites with real-life data. The proposed method finds a solution which is equivalent to the centralised optimization problem and is computed between 5 and 12 times faster. Thus, aggregators or large-scale energy communities can use this scalable algorithm to provide flexibility services.
The increasing amount of flexible load in the energy system represents both a challenge and an opportunity. One primary source of load growth is the electrification of the transport sector and the ...subsequent charging of electric vehicles, which is a load type that can potentially adjust their load profiles. However, to activate the full potential of end-user flexibility, it is necessary to develop pricing mechanisms that can promote efficient load responses on a larger scale. In this paper, a trading mechanism is proposed and analysed within a capacity-based grid tariff scheme by formulating a game-theoretic framework that includes decentralized decision-making by self-interest pursuing end-users. The model is applied to a real-world case in Norway, and it is demonstrated how electrification of vehicles can be achieved with the existing infrastructure. It is found that capacity-based grid tariffs have a limited ability to reduce the coincident peak load in the system since they mainly incentivize individual peak load reductions. However, by including a capacity trading mechanism within the capacity-based tariff structure, we demonstrate that it is possible to increase the value of flexibility since the flexible end-users are incentivized to coordinate their flexibility dispatch with other stakeholders.
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The electricity grid is expected to require vast investments due to the decarbonization-by-electrification trend, calling for a change in grid tariff design which provides proper incentives for ...reducing peak loads. However, price signals from grid tariffs could be "distorted" from electricity spot prices which also represents a significant of the total consumer electricity bill. This paper attempts to identify whether there is a price signal conflict between grid tariffs and spot prices. Four different grid tariff designs are compared, using a generic demand response model as part of a cost-minimizing linear program to simulate the reduction in peak load. The method is applied to metered electricity demand from 3608 consumers in Oslo, Norway. Results show that new grid tariff designs reduce peak loads by 1-4%, and that reduction in peak load is smaller when consumers are subject to electricity spot prices.
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