An optimized energy system planning and operation on distribution grid level—The Decentralized Market Agent as a novel approach

Thomsen, Jessica; Hussein, Noha Saad; Senkpiel, Charlotte; Hartmann, Niklas; Schlegl, Thomas

doi:10.1016/j.segan.2017.09.001

Cited by 22 publications

(10 citation statements)

References 40 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In the market, the broker determines a transaction price p(t) to maximize profit considering the market commission ω tr (widely used in the practical market. see, e.g., [25]- [27]) and the DR incentive p dr while maintaining a balance between the energy demand and the supply in the off-grid system. As a set of market participants, we define I and J as the set of buyers and sellers, respectively.…”

Section: System Modelmentioning

confidence: 99%

Joint Demand Response and Energy Trading for Electric Vehicles in Off-Grid System

2020

View full text Add to dashboard Cite

This paper proposes a joint demand response and energy trading for electric vehicles in an off-grid system. We consider isolated microgrid in a region where, at a given time, some renewable energy generators have superflous energy for sale or to keep in storage facilities, whereas some electric vehicles wish to buy additional energy to meet their deficiency. In our system model, broker lead the market by determining the optimal transaction price by considering a trade-off between commission revenue and power reliability. Buyers and sellers follow the broker's decision by independently submitting a transaction price to the broker. Correspondingly transaction energy is allocated to the buyers in the proportion to their payment, whereas the revenue is allocated to the sellers in proportion to their sales. We investigated the economic benefits of such a joint demand response and energy trading by analyzing its hierarchical decision-making scheme as a single-leader-heterogeneous multi-follower Stackelberg game. With demonstrating an existence of a unique Stackelberg equilibrium, we show that the transaction price in the proposed market model is up to 25.8% cheaper than the existing power market. In addition, we compare the power reliability results with other algorithm to show the suitability of proposed algorithm in the isolated microgrid environment.

show abstract

Section: System Modelmentioning

confidence: 99%

Joint Demand Response and Energy Trading for Electric Vehicles in Off-Grid System

2020

View full text Add to dashboard Cite

show abstract

“…Over the past few years, there has been an increased interest in pilot projects of the deployment of smart grids [46,54], smart meters and communication infrastructure [9,54], renewable energies [55], and alternative vehicle integration [56]. Planning for smart grids in cities is a task that must consider a large number of components in a system acting and interacting in time and space.…”

Section: Smart Grid Scenariosmentioning

confidence: 99%

“…However, the share of energy supply in such a decentralized system requires an effective approach to energy flow management, making full use of smart grids and technologies [8,9].…”

Section: Introductionmentioning

confidence: 99%

A Cellular Approach to Net-Zero Energy Cities

et al. 2017

View full text Add to dashboard Cite

Abstract:Recent growth in the use of photovoltaic technology and a rapid reduction in its cost confirms the potential of solar power on a large scale. In this context, planning for the deployment of smart grids is among the most important challenges to support the increased penetration of solar energy in urban areas and to ensure the resilience of the electricity system. As part this effort, the present paper describes a cellular approach to a Net-Zero energy concept, based on the balance between the potential solar energy supply and the existing consumption patterns at the urban unit scale. To do that, the Geographical Urban Units Delimitation model (GUUD) has been developed and tested on a case study. By applying the GUUD model, which combines Geographic Information Systems (GIS), parametric modelling, and solar dynamic analysis, the whole area of the city was divided into urban cells, categorized as solar producers and energy consumers. The discussion around three theoretical scenarios permits us to explore how smart grids can be approached and promoted from an urban planning perspective. The paper provides insights into how urban planning can be a driver to optimize and manage energy balance across the city if the deployment of smart grids is correctly integrated in its operative process.

show abstract

“…Such peer-to-peer (P2P) energy trading has been demonstrated in various forms in the United States, United Kingdom, Netherlands, and Germany [5][6][7]. P2P energy trading is beneficial because it reduces the need for expensive and inefficient energy transportation with substantial losses [8], thus improving the reliability of energy supply [9] and alleviating transmission and distribution congestion problems [10]. Forecasting solar insolation in advance is essential in the management of the PV system's generated output in a distributed grid.…”

Section: Introductionmentioning

confidence: 99%

Estimating Solar Insolation and Power Generation of Photovoltaic Systems Using Previous Day Weather Data

Chung

2020

Advances in Civil Engineering

View full text Add to dashboard Cite

Day-ahead predictions of solar insolation are useful for forecasting the energy production of photovoltaic (PV) systems attached to buildings, and accurate forecasts are essential for operational efficiency and trading markets. In this study, a multilayer feed-forward neural network-based model that predicts the next day’s solar insolation by taking into consideration the weather conditions of the present day was proposed. The proposed insolation model was employed to estimate the energy production of a real PV system located in South Korea. Validation research was performed by comparing the model’s estimated energy production with the measured energy production data collected during the PV system operation. The accuracy indices for the optimal model, which included the root mean squared error, mean bias error, and mean absolute error, were 1.43 kWh/m2/day, −0.09 kWh/m2/day, and 1.15 kWh/m2/day, respectively. These values indicate that the proposed model is capable of producing reasonable insolation predictions; however, additional work is needed to achieve accurate estimates for energy trading.

show abstract

An optimized energy system planning and operation on distribution grid level—The Decentralized Market Agent as a novel approach

Cited by 22 publications

References 40 publications

Joint Demand Response and Energy Trading for Electric Vehicles in Off-Grid System

Joint Demand Response and Energy Trading for Electric Vehicles in Off-Grid System

A Cellular Approach to Net-Zero Energy Cities

Estimating Solar Insolation and Power Generation of Photovoltaic Systems Using Previous Day Weather Data

Contact Info

Product

Resources

About