Congestion management with demand response considering uncertainties of distributed generation outputs and market prices

Ni, Lei; Wen, Fushuan; Liu, Weijia; Jinling, Meng; Liu, Shengyuan; Dang, Sanlei

doi:10.1007/s40565-016-0257-9

Cited by 48 publications

(36 citation statements)

References 32 publications

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“…DR programs provide users more flexibility at the demand side, and have been widely studied and applied in some power companies [30]. In a MCE system, users also have the flexibilities to choose from various energy carriers in certain ranges.…”

Section: Idr Programs In Sehsmentioning

confidence: 99%

“…The equality constraints contain the AC power flow equations, as listed in (29)- (30). While the inequality constraints consist of active and reactive power output constraints of generators, limits of nodal voltage magnitudes and active power flows through power lines, which are described by (31)- (34) where Q E (x,t) represents the reactive power output from the generating unit at bus x at time t; P e (x,t) and Q e (x,t) represent the active and reactive loads at bus x at time t, respectively; P Ex /Q Ex and P Ex /Q Ex denote the lower/upper limits of P e (x,t)/Q e (x,t); V x (t) and h x (t) represent the voltage magnitude and phase angle of bus x at time t, respectively; V x and V x denote the lower and upper limit of V x (t); G xy and B xy represent the real and imaginary parts of the x-yth entry of the nodal admittance matrix, respectively.…”

Section: Electricity Transmission Networkmentioning

confidence: 99%

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Optimal operation of electricity, natural gas and heat systems considering integrated demand responses and diversified storage devices

Liu

Wen

et al. 2018

J. Mod. Power Syst. Clean Energy

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In recent years, the increasing penetration level of renewable generation and combined heat and power (CHP) technology in power systems is leading to significant changes in energy production and consumption patterns. As a result, the integrated planning and optimal operation of a multi-carrier energy (MCE) system have aroused widespread concern for reasonable utilization of multiple energy resources and efficient accommodation of renewable energy sources. In this context, an integrated demand response (IDR) scheme is designed to coordinate the operation of power to gas (P2G) devices, heat pumps, diversified storage devices and flexible loads within an extended modeling framework of energy hubs. Subsequently, the optimal dispatch of interconnected electricity, natural gas and heat systems is implemented considering the interactions among multiple energy carriers by utilizing the bi-level optimization method. Finally, the proposed method is demonstrated with a 4-bus multi-energy system and a larger test case comprised of a revised IEEE 118-bus power system and a 20-bus Belgian natural gas system.

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Section: Idr Programs In Sehsmentioning

confidence: 99%

Section: Electricity Transmission Networkmentioning

confidence: 99%

Optimal operation of electricity, natural gas and heat systems considering integrated demand responses and diversified storage devices

Liu

Wen

et al. 2018

J. Mod. Power Syst. Clean Energy

Self Cite

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“…For the electricity users, they will take the initiatives to join power DSM [14][15][16][17], which is similar to the operating mode of the active distribution network, thus the users have the intentions to positively in power consumption based on the time-of-use electricity pricing and automated demand response.…”

Section: Introductionmentioning

confidence: 99%

Local Energy Management and Optimization: A Novel Energy Universal Service Bus System Based on Energy Internet Technologies

Cheng¹,

Zhang²,

Jiang³

et al. 2018

Preprint

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This paper develops a novel energy universal service bus system (EUSBS) based on emerging energy Internet (E-net) technologies. This EUSBS is a unified identification and plug-andplay interface platform to which high penetration distributed energy and equipment (DEE), including photovoltaic (PV), fans, electric vehicle charging stations (EVCSs), energy storage equipment (ESE), and commercial and residential users (CRUs), can access in a coordinated control and optimized utilization mode. First, the functions design, overall framework and topology architecture design of the EUSBS are expounded, among which the EUSBS is mainly composed of a hardware system and a software platform. Moreover, several future application scenarios are presented. Then, the hardware part of EUSBS is designed and developed, including the framework design of this hardware subsystem, and development of the hardware equipment for PV access, fans access, EVCS access, ESE access, and CRU access. The hardware subsystem consists of smart socket, and household/floor/building concentrators. Based on this, the prototypes development of EUSBS hardware equipment is completely demonstrated. Third, the software part of the EUSBS is developed as a cloud service platform for electricity use data analysis of DEE. This software subsystem contains the power quality & energy efficiency analysis module, optimization control module, information and service module, and data monitoring and electricity behavior analysis module. Based on this design, the software interfaces are developed. Finally, an application study on energy management and optimization of a smart commercial building is conducted to evaluate the functions and practicality of this EUSBS. The EUSBS developed in this paper is able to overcome difficulties in big data collection and utilization on sides of distribution network and electricity utilization, and eventually implement a deep information-energy fusion and a friendly supplydemand interaction between the grid and users. This contribution presents a detailed and systematic development scheme of the EUSBS, and moreover, the laboratory prototypes of the hardware and software subsystems have been developed based on E-net technologies. This paper can provide some thoughts and suggestions for the research of active distribution network and comprehensive energy management and optimization in power systems, as well as references and guidance for researchers to carry out research regarding energy management, optimization and coordinated control of the smart buildings.

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“…Fotouhi Ghazvini). distribution systems [5]. High demand due to EVs and HPs can also potentially cause overloading of the electricity lines.…”

mentioning

confidence: 99%

Congestion management in active distribution networks through demand response implementation

Ghazvini

Lipari

Pau

et al. 2019

Sustainable Energy, Grids and Networks

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a b s t r a c tDespite the positive contributions of controllable electric loads such as electric vehicles (EV) and heat pumps (HP) in providing demand-side flexibility, uncoordinated operation of these loads may lead to congestions at distribution networks. This paper aims to propose a market-based mechanism to alleviate distribution network congestions through a centralized coordinated home energy management system (HEMS). In this model, the distribution system operator (DSO) implements dynamic tariffs (DT) and daily power-based network tariffs (DPT) to manage congestions induced by EVs and HPs. In this framework, the HP and EV loads are directly controlled by the retail electricity provider (REP). As DT and DPT price signals target the aggregated nodal demand, the individual uncoordinated HEMS models operating under these price signals are unable to effectively alleviate congestion. A large number of flexible residential customers with EV and HP loads are modeled in this paper, and the REP schedules the consumption based on the comfort preferences of the customers through HEMS. The effectiveness of the market-based concept in managing the congestion is demonstrated by using the IEEE 33-bus distribution system with 706 residential customers. The case study results show that considering both pricing systems can considerably mitigate the overloading occurrences in distribution lines, while applying DTs without considering DPTs may lead to severe overloading occurrences at some periods. (M.A. Fotouhi Ghazvini). distribution systems [5]. High demand due to EVs and HPs can also potentially cause overloading of the electricity lines. The distribution system operator (DSO) is confronted with congestion issues when a large number of these loads draws electricity from the grid simultaneously [6]. Uncoordinated operation of these flexible loads can cause unexpected congestions in the distribution system [5]. Real-time pricing (RTP) schemes offered by REPs in liberalized markets can also increase congestions in distribution systems by creating new peak demands in response to the time variable tariffs. The new peaks may cause overloading of lines and transformers [1].Resolving the distribution grid congestion is considered as one of the main duties of DSOs [7]. In long-term planning, the DSO can reinforce the distribution grid according to the identified needs in order to avoid possible congestions in future [8]. It can increase the grid capacity through boosting the investments in the grid infrastructure [6]. The congestion management strategies in shortterm are usually divided into three categories, which are distribution system reconfiguration (i.e., switch operation), direct load control and market-based mechanisms [1]. Market-based mechanisms compared to other two methods are more effective in the

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Congestion management with demand response considering uncertainties of distributed generation outputs and market prices

Cited by 48 publications

References 32 publications

Optimal operation of electricity, natural gas and heat systems considering integrated demand responses and diversified storage devices

Optimal operation of electricity, natural gas and heat systems considering integrated demand responses and diversified storage devices

Local Energy Management and Optimization: A Novel Energy Universal Service Bus System Based on Energy Internet Technologies

Congestion management in active distribution networks through demand response implementation

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