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Multistage Stochastic Demand-side Management for Price-Making Major Consumers of Electricity

Mahbubeh Habibian(mhab735***at***aucklanduni.ac.nz)
Anthony Downward(a.downward***at***auckland.ac.nz)
Golbon Zakeri(g.zakeri***at***auckland.ac.nz)

Abstract: In this paper we take a heuristic dynamic programming approach to solve a multistage stochastic optimization of energy consumption for a large manufacturer who is a price-making major consumer of electricity. We introduce a mixed-integer program that co-optimizes consumption bids and interruptible load reserve (ILR) offers for such a major consumer over a finite time horizon. By utilizing Lagrangian methods, we decompose our model by approximately pricing the constraints that link the stages together. We construct look-up tables in the form of consumption-utility curves, which our model uses to determine optimal consumption levels. We also present heuristics, in order to tackle the non-convexities within our model, and improve the accuracy of our policies. In the second part of the paper, we present stochastic solution methods for our model, with both stage-wise dependent and independent uncertainty. In addition, we reduce the size of our model's scenario tree by utilizing a tailor-made scenario clustering method. Furthermore, we conduct an experiment for a major consumer in the New Zealand Electricity Market and present numerical results.

Keywords: Multistage optimization, Lagrangian relaxation, Mixed-integer programming

Category 1: Applications -- OR and Management Sciences

Category 2: Applications -- Science and Engineering (Smart Grids )

Category 3: Integer Programming ((Mixed) Integer Linear Programming )

Citation: University of Auckland, July 2018

Download: [PDF]

Entry Submitted: 07/10/2018
Entry Accepted: 07/10/2018
Entry Last Modified: 07/10/2018

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