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.
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.
Increased power demand is a growing problem for distribution system operators (DSO) capable of causing unwanted and expensive grid upgrades. Descending prices for flexible
The Norwegian regulator has proposed a new grid tariff, based on capacity subscription, where the consumer pays an excess fee whenever he exceeds the subscribed level. We compare this tariff with a variant of capacity subscription where demand is physcially limited to the subscribed level, but where the limitation is activated only when there is grid congestion. The results show that this can be an attractive option if demand can be flexibly controlled to stay below the subscribed limit, which is increasingly possible. Use of a battery is also attractive, but the investment costs are still much too high.
As the higher penetration of distributed generation (DG) and electrical energy storage (EES) is emerging, end-users are taking a more active role in the power grid. With an increased amount of DG and EES available, opportunities for cooperation in the operation of power exchange arises. In cooperative game theory, for all players in a game cooperate under joint benefits. Preliminary studies show such cooperation among prosumers and consumers provides reduced annual electricity cost compared to independent operation. Focusing on cost allocation among endusers equipped with rooftop PV and batteries, we want to evaluate two solution concepts from game theory; the nucleolus and the Shapley value. By changing parameters that increase the value of the battery system in terms of reduced cost, this paper aims to examine whether the deviation between the cost allocations proposed by the methods increases as the value of the battery system is changed. The simulated case is based on data from private residences in Norway. Results from our case show that both nucleolus and Shapley provide stable cost allocations under minor deviations. However, results also imply that the deviation between the methods increases with an increased battery system value.
This paper investigates the relationship between grid tariffs and investment in Zero Emission Neighborhoods (ZEN) energy system, and how the grid exchanges are affected. Different grid tariffs (energy based, time of use (ToU), subscribed capacity and dynamic) are implemented in an optimization model that minimizes the cost of investing and operating a ZEN during its lifetime. The analysis is conducted in two cases: non-constrained exports and exports limited to 100kWh/h. The results suggest that in the case with no limit on export, the grid tariff has little influence, but ToU is economically advantageous for both the ZEN and the DSO. When exports are limited, the subscribed capacity scheme allows to maintain DSO revenue, while the others cut them by half. This tariff also offers the lowest maximum peak and a good duration curve. The dynamic tariff creates new potentially problematic peak imports despite its benefits in other peak hours.
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