Operational scheduling of responsive prosumer farms for day‐ahead peak shaving by agricultural demand response aggregators

2020 ◽  
Vol 45 (1) ◽  
pp. 938-960
Author(s):  
Hessam Golmohamadi
Keyword(s):  
Demand Response ◽  
Peak Shaving ◽  
Agricultural Demand

scholarly journals Impact of demand response on BIPV and district multi-energy systems design in Singapore and Switzerland

2021 ◽  
Vol 2042 (1) ◽  
pp. 012096
Author(s):  
Christoph Waibel ◽  
Shanshan Hsieh ◽  
Arno Schlüter
Keyword(s):  
Demand Response ◽  
Programming Model ◽  
Systems Design ◽  
Energy Systems ◽  
Mixed Integer ◽  
Peak Shaving ◽  
Climate Conditions ◽  
Building Integrated Photovoltaics ◽  
Energy Hub ◽  
The Impact

Abstract This paper demonstrates the impact of demand response (DR) on optimal multi-energy systems (MES) design with building integrated photovoltaics (BIPV) on roofs and façades. Building loads and solar potentials are assessed using bottom-up models; the MES design is determined using a Mixed-Integer Linear Programming model (energy hub). A mixed-use district of 170,000 m2 floor area including office, residential, retail, education, etc. is studied under current and future climate conditions in Switzerland and Singapore. Our findings are consistent with previous studies, which indicate that DR generally leads to smaller system capacities due to peak shaving. We further show that in both the Swiss and Singapore context, cost and emissions of the MES can be reduced significantly with DR. Applying DR, the optimal area for BIPV placement increases only marginally for Singapore (~1%), whereas for Switzerland, the area is even reduced by 2-8%, depending on the carbon target. In conclusion, depending on the context, DR can have a noticeable impact on optimal MES and BIPV capacities and should thus be considered in the design of future, energy efficient districts.

scholarly journals Research on joint optimal scheduling of air conditioning load and electric vehicle under demand response

2021 ◽  
Vol 257 ◽  
pp. 01058
Author(s):  
Haiyu Huang ◽  
Chunming Wang ◽  
Shaolian Xia ◽  
Huaqiang Xiong ◽  
Baofeng Jiang ◽  
...  
Keyword(s):  
Electric Vehicles ◽  
Demand Response ◽  
Air Conditioning ◽  
Power Grid ◽  
Peak Load ◽  
Optimal Scheduling ◽  
Peak Shaving ◽  
Energy Internet ◽  
Direct Load Control ◽  
Scheduling Model

As an important part of energy Internet carrier, demand side resources can participate in many interactions with power grid. In order to reduce the peak to valley load difference of power grid, from the perspective of tapping the combined peak shaving potential of air conditioning load and electric vehicles, guided by TOU price and direct load control, this paper proposes an optimal scheduling model with the minimum load difference and the maximum total revenue of users as the objective function. The results show that the joint optimal scheduling strategy can reduce the peak load and eliminate the “secondary peak load” caused by disorderly charging of electric vehicles.

Research on Demand Side Response System of Electricity Price Under Electricity Market Incentive Mechanism

2021 ◽  
Author(s):  
Fu Xianyu ◽  
Zhou Hongmei ◽  
Qi-jie Jiang ◽  
Ke Fan
Keyword(s):  
Power System ◽  
Demand Response ◽  
Electricity Market ◽  
Incentive Mechanism ◽  
Operating Cost ◽  
Electricity Price ◽  
Demand Side ◽  
Peak Shaving ◽  
Optimal Dispatch ◽  
Grid Operation

Aiming at the traditional day-ahead dispatching scheme of power generation, the paper proposes a power system security optimization dispatching model that considers the demand response of electricity prices under the electricity market incentive mechanism. Based on the peak and valley time-of-use electricity price, the paper establishes an incentive compensation mechanism to encourage users to be active. Participating in demand-side resource scheduling makes the effect of “peak shaving and valley filling” more pronounced. Simultaneously, to rationally configure the reserve capacity of grid operation, the system incorporates the expected power outage loss into the proposed model to ensure the grid operation safety. The analysis of calculation examples based on IEEE24 nodes shows that the power optimal dispatch model proposed in the paper considering demand response and expected outage loss can reduce the operating cost of the power grid under the premise of ensuring a certain level of reliability and realize the economy of the power system in the market environment and safe operation.

scholarly journals Assessing the Demand Side Management Potential and the Energy Flexibility of Heat Pumps in Buildings

Energies ◽  
2018 ◽  
Vol 11 (7) ◽  
pp. 1846 ◽  
Author(s):  
Alessia Arteconi ◽  
Fabio Polonara
Keyword(s):  
Energy Storage ◽  
Demand Response ◽  
Energy Efficient ◽  
Storage Systems ◽  
Heat Pumps ◽  
Demand Side ◽  
Energy Storage Systems ◽  
Peak Shaving ◽  
Load Shifting ◽  
Demand Response Programs

The energy demand in buildings represents a considerable share of the overall energy use. Given the significance and acknowledged flexibility of thermostatically controlled loads, they represent an interesting option for the implementation of demand side management (DSM) strategies. In this paper, an overview of the possible DSM applications in the field of air conditioning and heat pumps is provided. In particular, the focus is on the heat pump sector. Three case studies are analyzed in order to assess the energy flexibility provided by DSM technologies classified as energy efficient devices, energy storage systems, and demand response programs. The load shifting potential, in terms of power and time, is evaluated by varying the system configuration. Main findings show that energy efficient devices perform strategic conservation and peak shaving strategies, energy storage systems perform load shifting, while demand response programs perform peak shaving and valley filling strategies.

scholarly journals Smart Demand Response Based on Smart Homes

2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
Jingang Lai ◽  
Hong Zhou ◽  
Wenshan Hu ◽  
Dongguo Zhou ◽  
Liang Zhong
Keyword(s):  
Smart Grid ◽  
Energy Saving ◽  
Demand Response ◽  
Energy Savings ◽  
Supply And Demand ◽  
Smart Homes ◽  
Electricity Supply ◽  
Power Cable ◽  
Peak Shaving ◽  
Energy Feedback

Smart homes (SHs) are crucial parts for demand response management (DRM) of smart grid (SG). The aim of SHs based demand response (DR) is to provide a flexible two-way energy feedback whilst (or shortly after) the consumption occurs. It can potentially persuade end-users to achieve energy saving and cooperate with the electricity producer or supplier to maintain balance between the electricity supply and demand through the method of peak shaving and valley filling. However, existing solutions are challenged by the lack of consideration between the wide application of fiber power cable to the home (FPCTTH) and related users’ behaviors. Based on the new network infrastructure, the design and development of smart DR systems based on SHs are related with not only functionalities as security, convenience, and comfort, but also energy savings. A new multirouting protocol based on Kruskal’s algorithm is designed for the reliability and safety of the SHs distribution network. The benefits of FPCTTH-based SHs are summarized at the end of the paper.

scholarly journals Multiobjective Optimization Model considering Demand Response and Uncertainty of Generation Side of Microgrid

2020 ◽  
Vol 2020 ◽  
pp. 1-14
Author(s):  
Hanfang Li ◽  
Huaqing Wang ◽  
Jinghan Zhou ◽  
Zhongfu Tan ◽  
Jiacheng Yang ◽  
...  
Keyword(s):  
Demand Response ◽  
Optimization Model ◽  
Peak Shaving ◽  
Response Models ◽  
Scenario Reduction ◽  
Renewable Power ◽  
Output Uncertainty ◽  
Single Target ◽  
Renewable Power Generation ◽  
The Impact

To make better use of renewable power generation, a microgrid system is constructed, containing a multitype power supply and a multienergy storage structure. A multiobjective scheduling optimization model is proposed considering MS differential cost, power abandonment cost, and operation income, and demand response models are introduced to improve the ability of storage and users’ participating in peak shaving. To solve the uncertainty of WPP and PV’s output, the scenario reduction method is adopted, and a single target conversion of multiobjective functions is made through a desion attribute table. The results show that scenario reduction can put a brake on the impact of WPP and PV’s output uncertainty on system dispatch; demand response helps solve the problem of poor matching between the source and load. ESS’s co-operative effect can improve the system’s stability.

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