Chance-constrained programming for optimal scheduling of combined cooling, heating, and power-based microgrid coupled with flexible technologies

Mianaei, Peyman Khorshidian; Aliahmadi, Mohammad; Faghri, Safura; Ensaf, M R; Ghasemi, Amir; Abdoos, Ali Akbar

doi:10.1016/j.scs.2021.103502

Cited by 56 publications

(8 citation statements)

References 39 publications

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“…The study aims to integrate renewable energy as much as possible by minimizing the hybrid system's power curtailment + Maximizing the renewable power generation injected into the system [123] Loads, market prices, renewable generation…”

Section: Chance-constrained Programmingmentioning

confidence: 99%

Applications of Probabilistic Forecasting in Smart Grids: A Review

Khajeh

Laaksonen

2022

Applied Sciences

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This paper reviews the recent studies and works dealing with probabilistic forecasting models and their applications in smart grids. According to these studies, this paper tries to introduce a roadmap towards decision-making under uncertainty in a smart grid environment. In this way, it firstly discusses the common methods employed to predict the distribution of variables. Then, it reviews how the recent literature used these forecasting methods and for which uncertain parameters they wanted to obtain distributions. Unlike the existing reviews, this paper assesses several uncertain parameters for which probabilistic forecasting models have been developed. In the next stage, this paper provides an overview related to scenario generation of uncertain parameters using their distributions and how these scenarios are adopted for optimal decision-making. In this regard, this paper discusses three types of optimization problems aiming to capture uncertainties and reviews the related papers. Finally, we propose some future applications of probabilistic forecasting based on the flexibility challenges of power systems in the near future.

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Section: Chance-constrained Programmingmentioning

confidence: 99%

Applications of Probabilistic Forecasting in Smart Grids: A Review

Khajeh

Laaksonen

2022

Applied Sciences

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“…After receiving the purchase plan from the LA, the CCHP agent defines an optimization problem that tries to minimize the total cost and, at the same time, meet the LA demand. The cost function that the CCHP agent must consider is the function introduced by (16).…”

Section: Proposed Multi-energy Scheduling Modelmentioning

confidence: 99%

“…Reference [16] focuses on the operation of CCHP-based microgrid coupled with hybrid chiller, multi-energy storage, solar and wind power, etc., under the chance-constrained programming approach by considering the mutual relationship between carriers. While modelling consumption and wind and solar energies fluctuations, the proposed approach analyzes the violation of the balance constraint for each carrier and subjects it to guarantee the corresponding confidence level.…”

Section: Literature Reviewmentioning

confidence: 99%

Strategy for demand side management effectiveness assessment via a stochastic risk‐based bidding approach in a multi‐energy microgrid containing combined cooling, heat and power and photovoltaic units

Nosratabadi

Moshizi

Guerrero

2022

IET Renewable Power Gen

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This paper proposes an efficient risk-based infrastructure management approach for a multi-energy microgrid to assess the effectiveness of demand-side management (DSM) through a stochastic strategy. The studied microgrid consists of photovoltaic and combined cooling, heat and power as the energy generation units and load aggregator with the aim of DSM. Based on this structure, day-ahead operational scheduling is investigated for the microgrid in different scenarios in both summer and winter seasons. The risk consideration is also performed in the bidding procedure dealing with different scenarios and variable prices and probabilities. In this study, the conditional value at risk index is considered to assess the amount of risk and is also studied from two perspectives. In the first case, the level of risk acceptable to the investor, the load aggregator, is selected, and its impact on the day-ahead scheduling is examined. In the second case, the effect of different levels of risk-taking and their importance on the scheduling procedure are examined. The main purpose is to show the shortcomings of the traditional DSM method when load management is done for private companies with a certain level of risk and prepare the ground for future studies to solve them.

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“…Du constructed a planning model with uncertainty of new energy using Conditional Value-at-Risk (CVaR) considering the flexibility constraints of the system and verified the effectiveness of the model (Mingkun et al, 2021). MIANAEI et al incorporated flexibility constraints into their study and developed a capacity configuration model for wind, solar, and hydro-pumped storage systems utilizing the chance-constrained planning method, which ensured reliable operation while considering uncertainties (Mianaei et al, 2022).…”

Section: Introductionmentioning

confidence: 99%

A two-stage robust configuration optimization model and solution algorithm for new flexibility resources considering uncertainty response characterization

Yang,

Liu,

Yang

et al. 2024

Front. Energy Res.

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As the proportion of new energy continues to increase, the safety and stability of the new power system are challenged, urgently requiring the allocation of new flexible resources. This paper proposes a two-stage robust capacity optimization model considering flexibility demand constraints. Firstly, the uncertain characteristics of new energy are described, and a model of flexible resource adjustment capacity is established. Then, uncertain parameters are introduced to construct a robust capacity optimization model considering supply-demand balance, solved by column constraint generation algorithm and KKT theorem. Finally, a power system in a certain region of China is selected as the simulation object for empirical analysis to verify the effectiveness of the constructed model. The results show that the two-stage robust configuration optimization model constructed in this paper can address the uncertainty of power system and the flexibility demand brought by new energy, and the planning results can achieve a balance between the safety and economy of the new power system.

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Chance-constrained programming for optimal scheduling of combined cooling, heating, and power-based microgrid coupled with flexible technologies

Cited by 56 publications

References 39 publications

Applications of Probabilistic Forecasting in Smart Grids: A Review

Applications of Probabilistic Forecasting in Smart Grids: A Review

Strategy for demand side management effectiveness assessment via a stochastic risk‐based bidding approach in a multi‐energy microgrid containing combined cooling, heat and power and photovoltaic units

A two-stage robust configuration optimization model and solution algorithm for new flexibility resources considering uncertainty response characterization

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