Iterative sizing of solar-assisted mixed district heating network and local electrical grid integrating demand-side management

Gronier, Timothé; Fitó, Jaume; Franquet, Erwin; Gibout, Stéphane; Ramousse, Julien

doi:10.1016/j.energy.2021.121517

Cited by 13 publications

(8 citation statements)

References 45 publications

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“…As illustrated by [6], according to a latest survey, the residential sector's total energy consumption is nearly 20 -30 % of the world's total energy requirement.…”

Section: Figure 1: Merits Of Dsm Techniquesmentioning

confidence: 99%

“…Presently there are numerous demand response schemes which could be classified broadly either into price-based or incentive-based DR schemes. Few of these DR schemes could be called with different names [5,6,7,8] like economic and emergencybased DR schemes, marked led and system led DR schemes, indirect and direct DR schemes.…”

Section: Characteristics Of the Energy Demand Of Residential Sectormentioning

confidence: 99%

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Demand Side Management and Demand Response for Optimal Energy Usage: An Overview

Paul

Siddiqui

Kirmani³

2022

PIJR

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Being more than a decade old idea, the Demand-side management (DSM) is among the most vital part of the modern smart grid. DSM enables the utilities to minimize the gap between the supply and the demand by optimizing their pattern of user loads. At the same time, it helps them in achieving economic and energy efficient systems by reducing the peak to average (PAR). The implementation of DSM programs by the utilities could help them in improving their reliability, power quality, energy, and system efficiency. On the other hand, customers could be use it to improve their load profile, reduce the peak demands, save energy, and motivate them use more and more renewable energy. Thus, both the utilities and the consumers get benefitted by the implementation of DSM program in the smart grid. This study tries to understand the application of energy efficient policies and the demand response techniques with various DSM strategies. The study mainly focuses on the various characteristics that would lead to effective implementation of DSM programs with particular attention of the residential energy demand. Also, there will be a focus on enhancement of energy efficiency leading to more effective policy responses. The researchers could find this study very helpful as it could be employed to maximize the utility profits, the total load factor, peak demand and also minimize the consumer usage bills.

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“…As illustrated by [6], according to a latest survey, the residential sector's total energy consumption is nearly 20 -30 % of the world's total energy requirement.…”

Section: Figure 1: Merits Of Dsm Techniquesmentioning

confidence: 99%

Section: Characteristics Of the Energy Demand Of Residential Sectormentioning

confidence: 99%

Demand Side Management and Demand Response for Optimal Energy Usage: An Overview

Paul

Siddiqui

Kirmani³

2022

PIJR

View full text Add to dashboard Cite

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“…The optimal scheduling of integrated electricity-heat-gas systems has been discussed in [25], investigating the effect of multi-carrier energy storage systems. An optimal probabilistic sizing framework has been developed for integrated electrical and heating networks comprising photovoltaic and solar thermal energy sources in [26]. A robust decentralized approach has been developed in [27] for energy and reserve co-optimization in integrated electrical and heating networks.…”

Section: Introductionmentioning

confidence: 99%

“…Moreover, refs. [22][23][24][25][26][27][28][29][30] have studied the cooperation between the electrical and heating networks. However, these references did not model the TS.…”

Section: Introductionmentioning

confidence: 99%

Coordinated multi‐stage expansion planning of transmission system and integrated electrical, heating, and cooling distribution systems

Allahvirdizadeh

Shayanfar

Moghaddam

2022

IET Renewable Power Gen

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The rapid development of different energy production and conversion technologies at the distribution system (DS) level facilitates the integration of electrical, heating, and cooling DSs. The planning and operation of integrated DSs will affect the asset management of the transmission system (TS), which in turn will change the electrical energy prices and investment decisions at the DS level. This paper addresses a tri-level multistage approach for coordinated expansion planning of TS and integrated electrical, heating and cooling DSs. The photo voltaic panels (PVs), wind turbines (WTs), combined heat and power generation (CHP) units, boilers, and electrical and absorption chillers are considered investment candidates for coupling the DSs. Moreover, the expansion planning of TS lines, electrical feeders,and heating and cooling pipelines are integrated into the proposed model. The discussed model is tested on the modified 6-bus, 30-bus, and 118 bus IEEE TS comprising electrical, heating, and cooling DSs. The numerical study proves that the distribution system operators (DSOs), connected to different nodes of the TS, reduce their operation and emissioncosts by investing in the energy resources. Moreover, the proposed scheme successfully reduces the total expected cost of the transmission system operator (TSO) and successfully postpones the expansion of the TS.

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“…However, the classic load shifting methods only consider total loads, instead of the possible demand reductions. To investigate the relationship between the capacity of generation sources and possible demand reductions, Gronier et al [14] propose an iterative method with demand-side management to determine the sizing selection of photovoltaic panels and solar thermal collectors. Most of existing studies generally set the incentive price according to individual users' energy data and other more information, which is not easy to obtain or unrealistic.…”

Section: Introductionmentioning

confidence: 99%

Stochastic Gradient-based Fast Distributed Multi-Energy Management for an Industrial Park with Temporally-Coupled Constraints

Zhu¹,

Yang²,

Ma³

et al. 2022

Preprint

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Contemporary industrial parks are challenged by the growing concerns about high cost and low efficiency of energy supply. Moreover, in the case of uncertain supply/demand, how to mobilize delay-tolerant elastic loads and compensate real-time inelastic loads to match multi-energy generation/storage and minimize energy cost is a key issue. Since energy management is hardly to be implemented offline without knowing statistical information of random variables, this paper presents a systematic online energy cost minimization framework to fulfill the complementary utilization of multi-energy with time-varying generation, demand and price. Specifically to achieve charging/discharging constraints due to storage and short-term energy balancing, a fast distributed algorithm based on stochastic gradient with two-timescale implementation is proposed to ensure online implementation. To reduce the peak loads, an incentive mechanism is implemented by estimating users' willingness to shift. Analytical results on parameter setting are also given to guarantee feasibility and optimality of the

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Iterative sizing of solar-assisted mixed district heating network and local electrical grid integrating demand-side management

Cited by 13 publications

References 45 publications

Demand Side Management and Demand Response for Optimal Energy Usage: An Overview

Demand Side Management and Demand Response for Optimal Energy Usage: An Overview

Coordinated multi‐stage expansion planning of transmission system and integrated electrical, heating, and cooling distribution systems

Stochastic Gradient-based Fast Distributed Multi-Energy Management for an Industrial Park with Temporally-Coupled Constraints

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