Optimization Approach for the Aggregation of Flexible Consumers

Abstract

In an electric distribution system, the management of peak demands is becoming increasingly difficult. Every method we have to flatten the consumption curve greatly reduces the energy generation costs, CO2 emissions, and congestion in the 15 generation, transmission, and distribution systems. Therefore, we can act on consumers’ consumption, especially when we know that some consumers can be interested in reducing their consumption levels for monetary compensations. This can be done by reporting a part of consumption or shifting it. For this, a new profession called aggregation is born to manage the flexible consumers and meet the network requirements. To maximize their revenues, aggregators need to own an intelligent system to manage their portfolio of flexible consumers. They should optimize the way they modify the load curve of their flexible assets by respecting the system requirements and a set of consumer constraints. In this article, we address this task by proposing a Mixed Integer Linear Programming (MILP) formulation for two different modes: The economic mode (Evaluation of the potential of the portfolio to generate benefits. The aggregator uses this mode to make bids on the energy market) and the dispatch mode (to be used in an operational situation to respect the bids already submitted). Experimentation studies on real and random in-stances (>1000 instances) demonstrate the effectiveness of the proposed MILP.

Virtual Power Plant Optimization in Smart Grids: A Narrative Review

“…Digital twins of energy assets 13 [9][10][11][12][13][14][15][16][17][18][19][20][21] Energy forecasting 14 [1,[22][23][24][25][26][27][28][29][30][31][32][33][34] Optimization and coordination 18 [35][36][37][38][39][40][41][42][43][44][45][46][47][48][49][50][51][52] VPP applications in smart grids Energy services delivery 31 [4,5,22,35,38, Local energy autonomy 21 [5,…”

“…Others are using games theory to achieve a certain degree of decentralization while reducing the uncertainty impact on VPP optimization [46]. The optimal virtual aggregation of energy assets aims to achieve a state of equilibrium among coordinated energy assets while optimizing the service to the DSO [47].…”

Assessment of Energy Customer Perception, Willingness, and Acceptance to Participate in Smart Grids—A Portuguese Survey

“…In [13], the real-time transactive energy model proposed considers the household's preferences. In [14], it is demonstrated how aggregators can solve the flexibility aggregation issue to enable the balance of the grid using a mixed integer linear programming model considering load curves. To address the privacy issues related to the sharing of energy data, in [15], a privacy-preserving data aggregation algorithm is proposed to reduce communication overhead.…”