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Solving the fair electric load shedding problem in developing countries

Solving the fair electric load shedding problem in developing countries
Solving the fair electric load shedding problem in developing countries
Often because of limitations in generation capacity of power stations, many developing countries frequently resort to disconnecting large parts of the power grid from supply, a process termed load shedding. This leaves households in disconnected parts without electricity, causing them inconvenience and discomfort. Without fairness being taken into due consideration during load shedding, some households may suffer more than others. In this paper, we solve the fair load shedding problem (FLSP) by creating solutions which connect households to supply based on some fairness criteria (i.e., to fairly connect homes to supply in terms of duration, their electricity needs, and their demand), which we model as their utilities. First, we briefly describe some state-of-art household-level load shedding heuristics which meet the first criteria. Second, we model the FLSP as a resource allocation problem, which we formulate into two Mixed Integer Programming (MIP) problems based on the Multiple Knapsack Problem. In so doing, we use the utilitarian, egalitarian and envy-freeness social welfare metrics to develop objectives and constraints that ensure our FLSP solutions results in fair allocations that consider the utilities of agents. Then, we solve the FLSP and show that our MIP models maximize the groupwise and individual utilities of agents, and minimize the differences between their pairwise utilities under a number of experiments. When taken together, our endeavour establishes a set of benchmarks for fair load shedding schemes, and provide insights for designing fair allocation solutions for other scarce resources.
Constrained optimization, Fairness, Load shedding
1387-2532
Oluwasuji, Olabambo Ifeoluwa
b20f623c-d5cd-4db9-905c-5d00b9d95459
Malik, Obaid
16899d3c-005e-48f1-b7c0-8040449de79e
Zhang, Jie
6bad4e75-40e0-4ea3-866d-58c8018b225a
Ramchurn, Sarvapali
1d62ae2a-a498-444e-912d-a6082d3aaea3
Oluwasuji, Olabambo Ifeoluwa
b20f623c-d5cd-4db9-905c-5d00b9d95459
Malik, Obaid
16899d3c-005e-48f1-b7c0-8040449de79e
Zhang, Jie
6bad4e75-40e0-4ea3-866d-58c8018b225a
Ramchurn, Sarvapali
1d62ae2a-a498-444e-912d-a6082d3aaea3

Oluwasuji, Olabambo Ifeoluwa, Malik, Obaid, Zhang, Jie and Ramchurn, Sarvapali (2020) Solving the fair electric load shedding problem in developing countries. Autonomous Agents and Multi-Agent Systems, 34 (1), [12]. (doi:10.1007/s10458-019-09428-8).

Record type: Article

Abstract

Often because of limitations in generation capacity of power stations, many developing countries frequently resort to disconnecting large parts of the power grid from supply, a process termed load shedding. This leaves households in disconnected parts without electricity, causing them inconvenience and discomfort. Without fairness being taken into due consideration during load shedding, some households may suffer more than others. In this paper, we solve the fair load shedding problem (FLSP) by creating solutions which connect households to supply based on some fairness criteria (i.e., to fairly connect homes to supply in terms of duration, their electricity needs, and their demand), which we model as their utilities. First, we briefly describe some state-of-art household-level load shedding heuristics which meet the first criteria. Second, we model the FLSP as a resource allocation problem, which we formulate into two Mixed Integer Programming (MIP) problems based on the Multiple Knapsack Problem. In so doing, we use the utilitarian, egalitarian and envy-freeness social welfare metrics to develop objectives and constraints that ensure our FLSP solutions results in fair allocations that consider the utilities of agents. Then, we solve the FLSP and show that our MIP models maximize the groupwise and individual utilities of agents, and minimize the differences between their pairwise utilities under a number of experiments. When taken together, our endeavour establishes a set of benchmarks for fair load shedding schemes, and provide insights for designing fair allocation solutions for other scarce resources.

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Accepted/In Press date: 11 October 2019
e-pub ahead of print date: 11 December 2019
Published date: 1 April 2020
Additional Information: Publisher Copyright: © 2019, The Author(s).
Keywords: Constrained optimization, Fairness, Load shedding

Identifiers

Local EPrints ID: 435798
URI: http://eprints.soton.ac.uk/id/eprint/435798
ISSN: 1387-2532
PURE UUID: c69b1f19-56ce-4e37-92bd-3e2da9ae3403
ORCID for Obaid Malik: ORCID iD orcid.org/0000-0001-9014-2675
ORCID for Sarvapali Ramchurn: ORCID iD orcid.org/0000-0001-9686-4302

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Date deposited: 20 Nov 2019 17:30
Last modified: 17 Mar 2024 03:01

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Contributors

Author: Olabambo Ifeoluwa Oluwasuji
Author: Obaid Malik ORCID iD
Author: Jie Zhang
Author: Sarvapali Ramchurn ORCID iD

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