Optimal demand charge reduction for commercial buildings through a combination of efficiency and flexibility measures

Zhang, Yuna; Augenbroe, Godfried

doi:10.1016/j.apenergy.2018.03.150

Cited by 20 publications

(8 citation statements)

References 34 publications

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“…The objective function ( 1) is to minimize the total cost of industrial park over one month, including the electricity consumption cost and the natural gas consumption cost. Under the TPT policy, the electricity consumption cost consists of two parts, i. e., the electricity energy charge denoted by the first term in (1), and the peak demand charge denoted by the second term in (1). The natural gas consumption cost includes the gas consumption charge of all CHP units, as shown in the third term of (1).…”

Section: A Demand Management Of Industrial Park With Chp Unitsmentioning

confidence: 99%

“…I NDUSTRIAL park (or industrial estate) is an area planned for industrial development, which is usually associated with significant energy demands, especially electricity and natural gas. In terms of electric energy consumption, industrial park in many countries such as China and the United States is usually charged by a two-part tariff (TPT) policy [1], [2]. In the TPT policy, the electricity bill consists of two components, i. e., the peak demand charge and the energy charge [3].…”

Section: Introductionmentioning

confidence: 99%

“…Indeed, for some large-scale industrial parks, the peak demand charge is usually higher than the energy charge, which can reach up to 50%-70% of the monthly electricity bill [1], [7]. Thus, effective demand management approaches for industrial park to lower the peak electricity demand have attracted a lot of attentions in recent years, which can not only help enhance economic gains, but also promote the sustainable development of industrial park.…”

Section: Introductionmentioning

confidence: 99%

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Decentralized Demand Management Based on Alternating Direction Method of Multipliers Algorithm for Industrial Park with CHP Units and Thermal Storage

Wei

Zhang

Wang

et al. 2022

Journal of Modern Power Systems and Clean Energy

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This paper proposes a decentralized demand management approach to reduce the energy bill of industrial park and improve its economic gains. A demand management model for industrial park considering the integrated demand response of combined heat and power (CHP) units and thermal storage is firstly proposed. Specifically, by increasing the electricity outputs of CHP units during peak-load periods, not only the peak demand charge but also the energy charge can be reduced. The thermal storage can efficiently utilize the waste heat provided by CHP units and further increase the flexibility of CHP units. The heat dissipation of thermal storage, thermal delay effect, and heat losses of heat pipelines are considered for ensuring reliable solutions to the industrial park. The proposed model is formulated as a multi-period alternating current (AC) optimal power flow problem via the second-order conic programming formulation. The alternating direction method of multipliers (ADMM) algorithm is used to compute the proposed demand management model in a distributed manner, which can protect private data of all participants while achieving solutions with high quality. Numerical case studies validate the effectiveness of the proposed demand management approach in reducing peak demand charge, and the performance of the ADMM-based decentralized computation algorithm in deriving the same optimal results of demand management as the centralized approach is also validated. Index Terms--Alternating direction method of multipliers (ADMM), combined heat and power (CHP) unit, demand management, industrial park, integrated demand response (IDR), thermal storage.

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Section: A Demand Management Of Industrial Park With Chp Unitsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Decentralized Demand Management Based on Alternating Direction Method of Multipliers Algorithm for Industrial Park with CHP Units and Thermal Storage

Wei

Zhang

Wang

et al. 2022

Journal of Modern Power Systems and Clean Energy

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“…Historically, users with capacity charge tariffs, especially commercial buildings, have managed their critical demands through efficiency and flexibility measures [19]. In recent years, energy storage has been attracting interests from peak-users to provide them with flexibility in their demand management.…”

Section: Rollover Network Capacity Chargementioning

confidence: 99%

Network capacity charge for sustainability and energy equity: A model-based analysis

Khalilpour

Lusis

2020

Applied Energy

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It is long known that the afternoon peak demand accounts for over-investment in the electricity network assets. This results in a high price of delivered electricity which does not fairly differentiate between peak and non-peak users. Energy tariff is proven to be one of the best demand-side management (DSM) tools for shaping consumers' behaviour. While electricity pricing models, such as inclining block and time-of-use tariffs, have received decent attention as successful mechanisms, there are little discussions about another efficient tariff known as a rollover network capacity charge. It is a penalty for the highest recorded power usage over the previous reading cycle (or year) which is introduced to commercial users in some jurisdictions. With recent price reduction in distributed generation and storage (DGS) systems, the interest has increased in devising policies for directing the household and commercial consumers' behaviour towards using DGS systems in line with DSM objectives. In this paper, we have integrated the rollover network capacity charge into DGS systems investment analysis. The results from a few case studies show the positive impact of capacity charge in directing the peak-consumers' investment decisions towards DSM tools (e.g., energy storage) to curb their peak demands. This not only improves the resilience of the network but also promises as an effective mechanism in energy-justice nexus by avoiding the transfer of the associated costs of peak demand to all users.

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“…Peak load charges are typically based on the highest electric load (in kW) observed during a billing period, typically a month, and are charged in $/kW 5,6 . These peak load charges can amount to up to 70% of an electric bill in the case of consumers in the United States of America 6–8 . Many commercial and residential buildings around the world are billed under this type of dynamic pricing scheme.…”

Section: Introductionmentioning

confidence: 99%

Peak electric load days forecasting for energy cost reduction with and without behind the meter renewable electricity generation

Aponte

McConky

2021

Int J Energy Res

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Summary Many electricity consumers around the world are billed electric peak load charges. In the United States, these demand charges can contribute up to 70% of a consumer's electricity bill. Research has shown that the financial impact of these charges to the consumers can be reduced by acting on the intelligence provided by peak electric load day (PELD) forecasts. Unfortunately, published research detailing PELDs forecasting methodologies for facilities adopting behind the meter renewable electricity generation (BTMREG) is non‐existent. This paper contributes: (a) a PELD forecasting methodology applicable to consumers with BTMREG. A case study demonstrates the methodology's ability to achieve 93% of the potential savings in kW, translating to demand charge reductions of approximately US$ 142 129 per year. (b) The first side‐by‐side performance comparisons of electric load and PELD forecasting models for scenarios with and without BTMREG. (c) The first PELD forecasting model savings comparison for scenarios with and without BTMREG. Experimental results suggest that counterintuitively, BTMREG adoption can translate into higher peak load savings for electricity consumers.

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Optimal demand charge reduction for commercial buildings through a combination of efficiency and flexibility measures

Cited by 20 publications

References 34 publications

Decentralized Demand Management Based on Alternating Direction Method of Multipliers Algorithm for Industrial Park with CHP Units and Thermal Storage

Decentralized Demand Management Based on Alternating Direction Method of Multipliers Algorithm for Industrial Park with CHP Units and Thermal Storage

Network capacity charge for sustainability and energy equity: A model-based analysis

Peak electric load days forecasting for energy cost reduction with and without behind the meter renewable electricity generation

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