Optimal Balancing of Wind Parks with Virtual Power Plants

Vadim Omelčenko,Valery Manokhin

doi:10.3389/fenrg.2021.665295

Abstract

In this paper, we explore the optimization of virtual power plants (VPP), consisting of a portfolio of biogas power plants and a battery whose goal is to balance a wind park while maximizing their revenues. We operate under price and wind production uncertainty and in order to handle it, methods of machine learning are employed. For price modeling, we take into account the latest trends in the field and the most up-to-date events affecting the day-ahead and intra-day prices. The performance of our price models is demonstrated by both statistical methods and improvements in the profits of the virtual power plant. Optimization methods will take price and imbalance forecasts as input and conduct parallelization, decomposition, and splitting methods in order to handle sufficiently large numbers of assets in a VPP. The main focus is on the speed of computing optimal solutions of large-scale mixed-integer linear programming problems, and the best speed-up is in two orders of magnitude enabled by our method which we called Gradual Increase.

Highlights

The optimization of virtual power plants (VPP) is of crucial importance as it enables the more efficient incorporation of distributed energy resources (DER) into the grid and thereby contributes to the achievement of goals associated with ecology
In this paper we have presented optimization and forecast algorithms with the goal of more efficient management of the virtual power plants and the by-product of such algorithms is the facilitation of the integration of Distributed Energy Resources into the grid
One of the ways to profit from owning a DER resource is connecting it to an efficiently optimized virtual power plant

Summary

Introduction

The optimization of virtual power plants (VPP) is of crucial importance as it enables the more efficient incorporation of distributed energy resources (DER) into the grid and thereby contributes to the achievement of goals associated with ecology. We consider the balancing of wind parks by means of pools of biogas (renewable fuel) power plants and pools of batteries and propose ways to accelerate calculations by means of mathematical methods of decomposition and splitting, leveraging the special structure of problems, parallelization, and the brute force power of optimization solvers. In our VPP, state-of-the-art commercial wind forecasts are used in order to nominate the amounts of energy that our wind turbines are able to produce, and the goal of the flexible assets is to handle the aggregate imbalances in both directions: biogas power plants can balance only deficiencies while batteries can balance surpluses.

Objectives

Results

Conclusion