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A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "F2: Distributed Energy System".

Deadline for manuscript submissions: closed (4 September 2023) | Viewed by 10341

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Dr. Yongli Wang

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Guest Editor

School of Economics and Management, North China Electric Power University, Beijng 102206, China
Interests: integrated energy system; energy internet; electric power economic management; power demand side management; power system planning; power market; power load forecasting
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Special Issue Information

Dear Colleagues,

At present, energy transformation will undergo disruptive changes and we are facing great challenges related to it. Integrated energy systems can integrate multiple energy resources in a region and realize coordinated planning, optimized operation, collaborative management, and interactive responses and complementary mutual benefits among multiple heterogeneous energy subsystems, as well as effectively improve energy utilization efficiency while meeting the diversified energy demand, and thus promote sustainable energy development. However, the operation optimization of integrated energy systems involves multiple heterogeneous energy synergies and multiple energy subjects, and its operation optimization and scheduling control is difficult. The time scales and scheduling principles of each energy subsystem differ greatly in terms of actual operation and scheduling, so it is difficult to conduct simulation analysis and coordinate control under the same time scale and unified scheduling principles. At the same time, the randomness of various types of energy loads and renewable energy output on the customer side present a challenge for the operation optimization of the integrated energy systems.

The purpose of this Special Issue is to present and disseminate the latest advances in the operational optimization of integrated energy systems.

Topics of interest for publication include, but are not limited to:

Integrated energy system operation optimization and control;
Integrated energy system operation assessment;
Integrated energy system operation reliability and stability;
Regional integrated energy systems;
Energy internet;
Collaborative scheduling of source-grid-load-storage;
Big Data and artificial intelligence;
Energy management and efficiency;
Demand response management;
Game theory;
Carbon trading;
Blockchain;
Smart algorithms.

Dr. Yongli Wang
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Energies is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

integrated energy systems
optimization
operation
assessment
modelling
scheduling
control

Published Papers (7 papers)

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Research

14 pages, 919 KiB

Open AccessArticle

A Robust Optimization Approach for Smart Energy Market Revenue Management

by Bin Zhang, Li Sun, Mengyao Yang, Kin-Keung Lai and Bhagwat Ram

Energies 2023, 16(19), 7000; https://doi.org/10.3390/en16197000 - 9 Oct 2023

Viewed by 767

Abstract

We propose a network optimization model for smart energy market management in the context of an uncertain environment. The network optimization considers the stochastic programming approach to capture the randomness of the unknown demands. We utilize the particle swarm optimization technique in the proposed model to solve the proposed optimization problem. The present research is based on the inclusion of stochastic demands and uncertain energy prices. Optimizing produced energy is crucial for efficient usage and meeting the targets. The proposed model also focuses on addressing sustainability concerns by minimizing energy consumption in the scheduling process. An improved particle swarm optimization technique is implemented for energy-efficient production. Parameters such as number of particles, iterations, and energy usage specification are customized. A fitness function is taken that considers both completion time and energy consumption. The optimal of energy consumption is also visualized. The decision makers employ risk aversion in the objective function of the optimization problem to measure the risk deviation of the expected energy management. Full article

(This article belongs to the Special Issue New Insight into Operational Optimization of Integrated Energy Systems)

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29 pages, 5092 KiB

Open AccessArticle

Assessing the Effects of Tradable Green Certificates and Renewable Portfolio Standards through Demand-Side Decision-Making Simulation: A Case of a System Containing Photovoltaic Power

by Yanbin Xu, Jiaxin Ma, Yuqing Wang and Ming Zeng

Energies 2023, 16(8), 3517; https://doi.org/10.3390/en16083517 - 18 Apr 2023

Cited by 1 | Viewed by 1286

Abstract

Understanding the effect of a tradable green certificate (TGC) and renewable portfolio standard (RPS) policy mix is of great importance for sustainable renewable-energy development and carbon neutrality, given that the demand side subjects are the responsible subjects under China’s RPSs and studies from the demand-side perspective are relatively limited. To fill this gap, this paper analyzes the coupled relationship between the TGC market and the electricity market as well as the reflexivity of the TGC market. Meanwhile, on the basis of modeling TGC prices and renewable-energy uncertainty, this paper constructs a Markov decision process (MDP) model to simulate the sequential decision-making process of the demand side and further proposes a solution model based on dynamic programming and evolutionary algorithms. The results show that: (1) In addition to policy parameters such as RPS weight, TGC price caps and penalties, a preference for short-term benefits and renewable-energy uncertainty also affect transaction behaviors on the demand side. (2) Increasing RPS weight within an appropriate range can stimulate demand for renewable power and TGC, while excessively low RPS weight will result in accumulation of unsold TGC. In addition, the preference for short-term benefits can stimulate demand for renewable power and curb demand for TGC. (3) An increase in the TGC price cap can stimulate demand for renewable power and restrain demand for TGC, but this phenomenon may not exist when RPS weight is too low or responsible subjects prefer short-term benefits. (4) Setting a penalty of no less than the TGC price cap is of great significance to ensure the operation of the TGC market and RPSs. Full article

(This article belongs to the Special Issue New Insight into Operational Optimization of Integrated Energy Systems)

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27 pages, 7405 KiB

Open AccessArticle

Energy Trading Strategy of Distributed Energy Resources Aggregator in Day-Ahead Market Considering Risk Preference Behaviors

by Jun Dong, Xihao Dou, Dongran Liu, Aruhan Bao, Dongxue Wang and Yunzhou Zhang

Energies 2023, 16(4), 1629; https://doi.org/10.3390/en16041629 - 6 Feb 2023

Cited by 6 | Viewed by 1551

Abstract

Distributed energy resources aggregators (DERAs) are permitted to participate in regional wholesale markets in many counties. At present, new market players such as aggregators participate in China’s power market transactions. However, studies related to market trading strategy have mostly focused on centralized wind power and PV generation units. Few studies have been conducted on the decision-making strategies for DERAs in China’s power market. This paper proposes an auxiliary decision-making model for distributed energy systems to participate in the day-ahead market with more reasonable trading strategies. Firstly, the Gaussian mixture model (GMM) is used to deal with the uncertainties of wind power and photovoltaic (PV) output in the distributed energy system. Secondly, the information gap decision theory (IGDT) is used to deal with the uncertainty of price fluctuations in the spot electricity market. Thirdly, according to the different risk preferences of the DERAs facing market price fluctuation, the robust decision model and opportunity decision-making model in the day-ahead market are constructed, respectively. Finally, to deal with the irrational behavior of the DERAs’ perception of “gain” and “loss” with market risks in China’s two-tier market environment, the prospect theory and the marine predator’s algorithm (MPA) are employed to obtain a day-ahead trading decision scheme for DERA. The analyses show that RDES with robust preference can withstand greater price volatility in the day-ahead market; they will reduce the bidding expectations and increase the system operating cost to improve the achievability of the expected revenue. However, DERAs under the opportunity strategy is more inclined to sell electricity to the market and offset system operating costs with revenue. The proposed model can provide strategic reference for DERAs with different risk preferences to bid in day-ahead market and can improve the level of aggregators’ participation in electricity trading. Full article

(This article belongs to the Special Issue New Insight into Operational Optimization of Integrated Energy Systems)

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21 pages, 3618 KiB

Open AccessArticle

Optimal Multi-Mode Flexibility Operation of CHP Units with Electrode Type Electric Boilers: A Case Study

by Yuliang Dong, Songyuan Yu, Chengbing He, Qingbin Yu and Fang Fang

Energies 2022, 15(24), 9337; https://doi.org/10.3390/en15249337 - 9 Dec 2022

Viewed by 1089

Abstract

With the in-depth development of flexibility retrofit in combined heat and power (CHP) units, the unit commitment mode of energy supply equipment in CHP plants is more flexible. This paper presents a multi-mode flexible operation method for CHP plants with electrode electric boilers. Firstly, a simulation model of the operation characteristics of each unit in different operation modes is established, and the corresponding features of electrical and thermal outputs are obtained. Subsequently, a decision-making model of the unit commitment mode of energy supply equipment is set up, and the selection rules of the unit commitment mode of the unit under low heat load, medium heat load, and high heat load are achieved. Finally, under different unit operation combinations, a plant-level optimum load dispatch model is obtained, and the actual operating data of the CHP plant is used for optimization and comparison analysis. The results show that compared to the unit commitment mode of high back pressure and low-pressure cylinder cutting-off (HBP + LPCC), the unit commitment mode of high back pressure and extraction heating (HBP + EH) has more room for energy-saving optimization. Under the premise of safe and reliable operation, the high back pressure (HBP) unit can be loaded as much as possible. While in the combined operating of HBP + EH, the energy-saving space for optimized load dispatching is not large, so a fixed proportion of the electrical load may be considered; under the auxiliary service subsidy policy, the input power of the electric boiler can be appropriately increased; the greater the heat load of the whole plant, the more pronounced the energy-saving effect of optimum load dispatch. Full article

(This article belongs to the Special Issue New Insight into Operational Optimization of Integrated Energy Systems)

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21 pages, 5199 KiB

Open AccessArticle

Optimizing Operation Strategy in a Simulated High-Proportion Wind Power Wind–Coal Combined Base Load Power Generation System under Multiple Scenes

by Qingbin Yu, Yuliang Dong, Yanjun Du, Jiahai Yuan and Fang Fang

Energies 2022, 15(21), 8004; https://doi.org/10.3390/en15218004 - 27 Oct 2022

Cited by 1 | Viewed by 1041

Abstract

In order to accommodate more intermittent renewable energy in coal-dominated power systems, conventional thermal power plants need to improve their operational flexibility to balance the energy system at all times. However, flexible operation of coal-fired power plants could reduce energy efficiency and increase CO₂ and pollutant emission, so it is important to consider environmental implications and optimize the dispatch of wind and coal power units in the system. In this paper, based on the output profile of wind power, a wind power peak (T, H) simulation model based on Gaussian distribution was established. Using a high-proportion wind power wind–coal combined base load power generation system as an example, the economical and environmentally friendly unit operation based on different wind power penetration was studied by simulation, and the decision strategy was established. Wind energy curtailment boundary was determined with power generation cost, energy consumption, CO₂ and pollutant emissions as decision targets, respectively. Weekly scale results indicate that incorporating energy consumption and pollutant emissions into consideration will lead to different decision-making strategies compared with only targeting minimizing wind curtailment. This paper established a decision-making model of wind–coal system operation strategy based on economy and environmental criteria. This work directly contributes to real system operation and is of great significance for future scheduling/dispatch studies of actual power systems. Full article

(This article belongs to the Special Issue New Insight into Operational Optimization of Integrated Energy Systems)

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25 pages, 3027 KiB

Open AccessArticle

Low-Carbon Economic Dispatching of Multi-Energy Virtual Power Plant with Carbon Capture Unit Considering Uncertainty and Carbon Market

by Huiru Zhao, Chao Zhang, Yihang Zhao and Xuejie Wang

Energies 2022, 15(19), 7225; https://doi.org/10.3390/en15197225 - 1 Oct 2022

Cited by 5 | Viewed by 1488

Abstract

Multi-energy virtual power plants (MEVPPs) effectively realize multi-energy coupling. Low-carbon transformation of coal-fired units at the source side and consideration of demand response resources at the load side are important ways to achieve carbon peak and carbon neutralization. Based on this, this paper proposes a low-carbon economic dispatch model for the MEVPP system considering source-load coordination with comprehensive demand response. Combined with the characteristics of organic Rankine cycle (ORC) waste heat power generation and comprehensive demand response energy to increase the flexibility on both sides of the source and load, the problem of insufficient carbon capture during the peak load period in the process of low-carbon transformation of thermal power units has been improved. First, the ORC waste heat recovery device is introduced into the MEVPP system to decouple the cogeneration unit’s “heat-based electricity” constraint, which improves the flexibility of the unit’s power output. Secondly, we consider the synergistic effect of the comprehensive demand response and ORC waste heat recovery device and analyze the source-load coordination low-carbon dispatch mechanism. Finally, an example simulation is carried out in a typical system. The simulation example shows that this method effectively improves the carbon capture level of carbon capture power plants, takes into account the economy and low carbon of the system, and can provide a reference for the low-carbon economic dispatch of the MEVPP system. Full article

(This article belongs to the Special Issue New Insight into Operational Optimization of Integrated Energy Systems)

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20 pages, 3718 KiB

Open AccessFeature PaperArticle

Optimal Microgrid System Operating Strategy Considering Variable Wind Power Outputs and the Cooperative Game among Subsystem Operators

by Yanbin Li, Yanting Sun, Junjie Zhang and Feng Zhang

Energies 2022, 15(18), 6601; https://doi.org/10.3390/en15186601 - 9 Sep 2022

Cited by 2 | Viewed by 1050

Abstract

In recent years, the microgrid system (MGS) has become an important method for the consumption of renewable energy sources (RES). In the actual operation process, the uncertainties of RES add to the complexity of the MGS operation. Furthermore, the MGS is often operated by multiple subsystem operators. The benefit distribution among subsystem operators is an important factor affecting the overall stable operation of the MGS. In order to resist the interference of the above factors, a two-stage optimization method is proposed in this paper, which includes a bi-level robust optimization (BRO) model in the overall scheduling stage of the MGS and a nucleolus-based cooperative game (NCG) model in the internal cost allocation stage among the subsystem operators. The simulations demonstrated the following outcomes: (1) the P2G device can reduce the operating cost of the MGS by converting electricity into natural gas when the electricity price is low; (2) the two-stage optimization method can ensure the stable operation of the MGS by resisting the disturbance of uncertain wind power outputs in the overall scheduling stage and realizing a reasonable cost allocation among the subsystem operators in the internal cost allocation stage. Full article

(This article belongs to the Special Issue New Insight into Operational Optimization of Integrated Energy Systems)

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