Demand response and other demand side management techniques for district heating: A review

The integration of renewable energy resources (RES) (such as wind and photovoltaic (PV)) on large or small scales, in addition to small generation units, and individual producers, has led to a large variation in energy production, adding uncertainty to power systems (PS) due to the inherent stochasticity of natural resources. The implementation of demand-side management (DSM) in distribution grids (DGs), enabled by intelligent electrical devices and advanced communication infrastructures, ensures safer and more economical operation, giving more flexibility to the intelligent smart grid (SG), and consequently reducing pollutant emissions. Consumers play an active and key role in modern SG as small producers, using RES or through participation in demand response (DR) programs. In this work, the proposed DSM model follows a two-stage stochastic approach to deal with uncertainties associated with RES (wind and PV) together with demand response aggregators (DRA). Three types of DR strategies offered to consumers are compared. Nine test cases are modeled, simulated, and compared in order to analyze the effects of the different DR strategies. The purpose of this work is to minimize DG operating costs from the Distribution System Operator (DSO) point-of-view, through the analysis of different levels of DRA presence, DR strategies, and price variations.

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A Framework for Demand-Side Management With Demand Response Input

10.1115/1.0000486v ◽

2021 ◽

Author(s):

Miguel Peinado-Guerrero ◽

Jesus Rene Villalobos ◽

Patrick Phelan ◽

Nicolas Campbell

Keyword(s):

Demand Response ◽

Demand Side Management ◽

Demand Side

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Implementation of a Demand-Side Management Solution for South Korea’s Demand Response Program

Applied Sciences ◽

10.3390/app10051751 ◽

2020 ◽

Vol 10 (5) ◽

pp. 1751 ◽

Cited By ~ 1

Author(s):

Wonsuk Ko ◽

Hamsakutty Vettikalladi ◽

Seung-Ho Song ◽

Hyeong-Jin Choi

Keyword(s):

South Korea ◽

Real Time ◽

Demand Response ◽

Mean Squared Error ◽

Demand Side Management ◽

Demand Side ◽

Root Mean Squared Error ◽

Squared Error ◽

Demand Response Program ◽

Relative Root

In this paper, we show the development of a demand-side management solution (DSMS) for demand response (DR) aggregator and actual demand response operation cases in South Korea. To show an experience, Korea’s demand response market outline, functions of DSMS, real contracted capacity, and payment between consumer and load aggregator and DR operation cases are revealed. The DSMS computes the customer baseline load (CBL), relative root mean squared error (RRMSE), and payments of the customers in real time. The case of 10 MW contracted customers shows 108.03% delivery rate and a benefit of 854,900,394 KRW for two years. The results illustrate that an integrated demand-side management solution contributes by participating in a DR market and gives a benefit and satisfaction to the consumer.

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City Scale Demand Side Management in Three Different-Sized District Heating Systems

Energies ◽

10.3390/en11123370 ◽

2018 ◽

Vol 11 (12) ◽

pp. 3370 ◽

Cited By ~ 17

Author(s):

Kaisa Kontu ◽

Jussi Vimpari ◽

Petri Penttinen ◽

Seppo Junnila

Keyword(s):

Control Strategies ◽

District Heating ◽

Cost Savings ◽

Demand Side Management ◽

Management Control ◽

Demand Side ◽

Demand Model ◽

Management Scenarios ◽

Annual Peak ◽

Heat Demand

Demand side management can add flexibility to a district heating (DH) system by balancing the customer’s hourly fluctuating heat demand. The aim of this study is to analyze how different demand side management control strategies, implemented into different customer segments, impact DH production. A city scale heat demand model is constructed from the hourly heat consumption data of different customer segments. This model is used to build several demand side management scenarios to examine the effect of them on both, the heat producer, and the customers. The simulations are run for three different-sized DH systems, representing typical DH systems in Finland, in order to understand how the demand side management implementations affect the production. The findings imply that the demand side management strategy must be built individually for each specific DH system; the changing consumption profiles of different customer segments should be taken into consideration. The results show that the value of demand side management for a DH companies remains low (less than 2% in cost savings), having an effect mostly upon the medium loads without any significant decrease in annual peak heat loads. Also, the findings reflect that the DH pricing models should be developed to make demand side management more attractive to DH customers.

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