Abstract

The increasing adoption of renewable energy sources increases the need of balancing power. The security concerns of the distribution system operators are increasing due to fast adoption of distributed energy resources (DERs). So far, various operational models are proposed to manage the DERs for economic benefit. However, there is lack of an efficient operational model that balances the security, market, and uncertainty management. With the focus on the aggregator's operation, this paper has developed an operational model for continuous operation of aggregators interactively with the grid operators. A rolling optimization model is developed to manage the uncertainties from prediction errors. The network security is ensured continuously through an iterative price negotiation process between the distribution network operator and the aggregators. The optimality of the solution is guaranteed by convexification of the mixed integer formulation.

Highlights

  • The Paris agreement underlines the urgency of decarbonizing the current energy sector [1]

  • The technical improvement in comparison to the previous work is fourfold: 1) RWO method is applied for optimizing the operational strategy of each aggregator to reduce the impacts of electricity price prediction errors; 2) The battery operating cost is modeled and considered in the optimization problem formulation; 3) Taking the option of vehicle to grid (V2G) into account, a new bi-linear optimization model for electric vehicle (EV) aggregator (EVA) is proposed which can be applied both for day-ahead market (DAM) as well as BM; 4) A convexification method is developed to ensure the convexity of the formulation

  • Assumptions are adopted as follows: 1) EVAs can receive information of energy needs, prediction of the market prices for the DAM and BM participation. This can be guaranteed with the current market transparency and the registered information of the public and private chargers; 2) The up and down regulation power supplied by EVA will be taken by TSO and fully activated by the TSO within one hour; 3) Distribution line capacity is not considered, and the power factor of the load is 1

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Summary

INTRODUCTION

The Paris agreement underlines the urgency of decarbonizing the current energy sector [1]. Considering the above mentioned work, this paper further develops the network constrained transactive energy (NCTE) concept [15], [16], [21] by taking the advantage of RWO in uncertainty handling for real-time operation and convexification of the aggregators’ model to ensure optimality. The technical improvement in comparison to the previous work is fourfold: 1) RWO method is applied for optimizing the operational strategy of each aggregator to reduce the impacts of electricity price prediction errors; 2) The battery operating cost is modeled and considered in the optimization problem formulation; 3) Taking the option of vehicle to grid (V2G) into account, a new bi-linear optimization model for EVA is proposed which can be applied both for DAM as well as BM; 4) A convexification method is developed to ensure the convexity of the formulation.

MARKET PARTICIPATION PROCEDURE FOR EVA
OPTIMIZATION IN THE DAM
RWO IN BALANCING POWER MARKET
EVA’s OPTIMAL SCHEDULE
TARGET OF DSO
DISTRIBUTED ALGORITHM FOR TE REALIZATION IN THE DISTRIBUTION SYSTEM
CASE STUDY
PARAMETER SETTINGS
Findings
CONCLUSION
Full Text
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