Optimal scheduling of micro-energy grid with integrated demand response based on chance-constrained programming

Wang, Hang; Xing, Haijun; Luo, Yangfan; Zhang, Wenbo

doi:10.1016/j.ijepes.2022.108602

Cited by 35 publications

(10 citation statements)

References 26 publications

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“…For the thermal supplying tank, the energy transfer includes the temperature change, the energy from storage tank, the energy loss, the supplying energy, make-up water, the energy converted from bump and the energy buying from others, its model is described as (20).…”

Section: Fig2 Spts Structure Diagrammentioning

confidence: 99%

“…Robust optimizations with uncertainty sets are applied to solve the optimal solution under the worst case, resulting in its over conservativeness [19]. The chance-constraint programming based on Gaussian hypothesis only requires that the probability of satisfying the critical constraint is higher than a certain level and allows low probability of constraint violation [20]. However, probability distribution of uncertain variables is usually described by a simple distribution (e.g., single Gaussian and single Beta), which may lead to larger errors and infeasible solutions.…”

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confidence: 99%

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A Decentralized Peer-to-Peer Energy Trading Model in Integrated Electric-Thermal System

Huang

Sun

et al. 2023

Preprint

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To promote the energy accommodation of both electrical and heating power while considering the source-load uncertainties, this paper proposes a peer-to-peer (P2P) energy trading model among prosumers in the integrated electric-thermal system, considering the energy trading agent (ETA) with self-build energy system. The Solar Heat-Pump Hybrid Thermal Water System (SPTS) and the transferring loss of heating power is considered and modelled based on the principle of steady-state thermal transfer. Since the variations of load and PV cannot be described by any single common distribution, the chance-constraints programming based on the Gaussian mixture model (GMM) is proposed to handle the uncertainty of the net load. As the proposed power trading problem is a non-convex problem with binary variables, an improved distributed alternating direction method of multiplier (ADMM) based on the predictor-corrector and two-stage cycle iterations is proposed to enhance the convergence performance of standard ADMM. Finally, an example simulation verifies the effectiveness, results show that the proposed model can decrease the total cost by 26.7% and enhance local energy balance by 61.8% compared to other cases.

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Section: Fig2 Spts Structure Diagrammentioning

confidence: 99%

mentioning

confidence: 99%

A Decentralized Peer-to-Peer Energy Trading Model in Integrated Electric-Thermal System

Huang

Sun

et al. 2023

Preprint

View full text Add to dashboard Cite

show abstract

“…For example, Gao et al (2021) proposed an incentive demand response strategy for residential users based on evolutionary game theory, which realizes users' load control when their willingness is time-varying. Wang et al (2023) put forward an optimal scheduling model based on chance-constrained programming by combining EVs with electrothermal loads. Shao et al (2019) considered the transferability of load and the alternativity of energy, and a price-based comprehensive demand response strategy was designed for thermoelectric load control.…”

Section: Introductionmentioning

confidence: 99%

A low-carbon-oriented multi-time-scale dispatching strategy of multi-energy heterogeneous loads in clean heating scenarios of green residences

Sun²,

Li³

et al. 2023

Front. Energy Res.

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Clean energy utilization is important for the improvement of energy structure. At present, photothermal and electrothermal conversion technologies are becoming increasingly applied in many homes, which can thus be regarded as green residences. To meet the heating demand of green residences, solar hot water systems and electricity-to-heat (E2H) conversion devices, such as ground source heat pumps electric heating stoves and electric water heaters are widely installed to provide a clean form of heat. Besides, common loads, such as lighting, washing, and electric vehicles are daily loads in green residences. The above electric and thermal loads are regarded as multi-energy heterogeneous loads MEHLs can be used to decarbonize green residences by optimizing energy dispatch through flexible control. In this study, a novel energy structure of green residences was extended through the combination of SHWs, E2H, GSHPs, and EVs, as well as rooftop photovoltaic systems. Then, to minimize carbon emissions, a residential energy dispatching model was designed from day-ahead and real-time scales and a low-carbon-oriented multi-energy heterogeneous loads coordinated control strategy was proposed. Finally, to mitigate the residents’ loss of comfort caused by MEHL control, the indoor environment and water tank temperatures and the state of charge of EVs were regarded as special constraints. The simulation revealed that the proposed strategy can reduce carbon emissions by 33.07% and meet the basic demand for residential heat and electricity. Additionally, the strategy has good applicability for decarbonizing green residences.

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“…These unpredictable power outages will bring potential safety and economic risks to the system's operation. It is pointed out that reasonable configuration of various devices in the multi-energy microgrid can give full play to its multi-energy complementary characteristics (Li et al, 2021a;Wang et al, 2021;Wang et al, 2023).…”

Section: Introductionmentioning

confidence: 99%

A multi-energy microgrid configuration method in remote rural areas considering the condition value at risk

Yang²,

Liang³

et al. 2023

Front. Energy Res.

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The uncertainty caused by the growing use of renewable energy sources, such as wind and solar energy, makes it difficult to forecast the operation costs of micro-energy systems, particularly those in remote rural areas. Motivated by this point, this paper analyzes the possible operational risks and then introduces Condition Value at Risk (CVaR) to quantify the cost of the operational risk. On this basis, stochastic programming based on a multi-energy microgrid planning model that minimizes the investment cost, the operating cost, and the cost of operational risk, while considering the physical limitations of the multi-energy microgrid, is presented. Especially, scenarios of wind and solar energy output are generated using the Latin hypercube sampling method and reduced using the crowding measure-based scenario reduction method. After piecewise linearization and second-order cone relaxation, the model proposed in this paper is processed as a mixed integer linear model and solved by CPLEX. According to the achieved typical scenarios processed by the reduction method, the simulation shows that the presented configuration model can balance the investment cost and the cost of the operational risk, which effectively enhances the system’s ability to cope with uncertainties and fluctuations. Moreover, by adjusting the risk preference coefficient, the conservativeness of the planning scheme can be correspondingly adjusted.

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Optimal scheduling of micro-energy grid with integrated demand response based on chance-constrained programming

Cited by 35 publications

References 26 publications

A Decentralized Peer-to-Peer Energy Trading Model in Integrated Electric-Thermal System

A Decentralized Peer-to-Peer Energy Trading Model in Integrated Electric-Thermal System

A low-carbon-oriented multi-time-scale dispatching strategy of multi-energy heterogeneous loads in clean heating scenarios of green residences

A multi-energy microgrid configuration method in remote rural areas considering the condition value at risk

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