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Boundary Decision-Based Multi-Objective Robust Optimization for Microgrid Dispatching 认领 引用
1
作者 Junjian Wu Jingliao Sun +2 位作者 Yejun Xiang Zhenyu Zhou Zhengchai Shi 《Energy Engineering》 EI 2026年第7期404-423,共20页
The inherent unpredictability of renewable energy generation poses significant challenges to the reliable and economic dispatch of grid-connected microgrids.In response,this paper proposes a novel robust optimization ... The inherent unpredictability of renewable energy generation poses significant challenges to the reliable and economic dispatch of grid-connected microgrids.In response,this paper proposes a novel robust optimization strategy grounded in uncertain boundary decision-making and enhanced through innovations in the multi-objective cross-entropy method.An uncertainty budget-aware environmental economic dispatch model is first established,integrating photovoltaic and wind power generation.By employing mathematical sophistication-particularly Lagrangian transformation-the proposed method effectively resolves embedded uncertainties,transforming the original model into a deterministic multi-objective optimization framework robust against renewable energy volatility.Furthermore,by incorporating the dynamic operational demands of microgrids,this paper culminates in a robust optimization approach that is both fundamentally based on and adaptively responsive to uncertainty boundaries.To address the critical challenges of convergence and diversity in multi-objective optimization,crossover operators and an adaptive parameter update mechanism are introduced,significantly refining the conventional multi-objective cross-entropy algorithm.Case studies demonstrate the rationality and effectiveness of the proposed dispatch strategy and corroborate the superior performance and applicability of the enhanced algorithm. 展开更多
关键词 Microgrid environmental economic dispatch uncertain boundary robust optimization multi-objective cross entropy algorithm
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Low-Carbon Economic Dispatch of an Integrated Energy System with Multi-Device Coupling under Ladder-Type Carbon Trading 认领 引用
2
作者 Chenxuan Zhang Yongqing Qi +1 位作者 Ximin Cao Yanchi Zhang 《Energy Engineering》 EI 2026年第2期294-313,共20页
To enhance the low-carbon economic efficiency and increase the utilization of renewable energy within integrated energy systems(IES),this paper proposes a low-carbon dispatch model integrating power-to-gas(P2G),carbon... To enhance the low-carbon economic efficiency and increase the utilization of renewable energy within integrated energy systems(IES),this paper proposes a low-carbon dispatch model integrating power-to-gas(P2G),carbon capture and storage(CCS),hydrogen fuel cell(HFC),and combined heat and power(CHP).The P2G process is refined into a two-stage structure,and HFC is introduced to enhance hydrogen utilization.Together with CCS and CHP,these devices form a multi-energy conversion system coupling electricity,heat,cooling,and gas.A laddertype carbon trading approach is adopted to flexibly manage carbon output by leveraging marginal cost adjustments.To evaluate the resilience of the proposed low-carbon scheduling strategy involving multiple energy units under the variability of renewable energy,a two-level robust optimization framework is developed.This model captures the most adverse scenarios of wind and solar generation.The dispatch strategy is validated against these extreme conditions to demonstrate its flexibility and effectiveness.The problem is solved using the GUROBI optimization tool.Results from simulations indicate that themodel increases renewable energy integration by 39.1%,and achieves reductions of 15.96%in carbon emissions and 16.29%in operational expenditures.The results demonstrate that the strategy ensures both economic efficiency and environmental performance under uncertain conditions.Compared with existing studies that separately model two-stage P2G or CCS devices,this paper integrates HFC,CHP,and CCS into a unified dispatchable system,enabling refined hydrogen utilization and flexible carbon circulation.Furthermore,the introduction of a laddertype carbon pricing mechanism,combined with multi-energy storage participation in implicit demand response,creates a dynamic and cost-sensitive dispatch framework.These modeling strategies go beyond conventional linear IES formulations and provide more realistic system representations.The proposed approach not only deepens the coupling among electric,thermal,and gas systems,but also offers a feasible pathway for high-penetration renewable integration in low-carbon energy systems. 展开更多
关键词 Integrated energy system ladder-type carbon trading low-carbon economic dispatch two-stage robust optimization
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Two-Stage Robust Optimal Dispatch of Integrated Wind-Solar-Hydro-Thermal-Storage System Containing P2G-CCS Equipment under Renewable Energy Uncertainties 认领 引用
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作者 Jiyuan Liao Jiangyan Zhao +3 位作者 Xin Li Changmao Liu Banghong Tang Zihan Ling 《Energy Engineering》 EI 2026年第9期376-401,共26页
To address the uncertainty and volatility of renewable energy while meeting the requirements of low-carbon economic operation,this paper proposes a two-stage robust optimal dispatch model for an integrated wind-solar-... To address the uncertainty and volatility of renewable energy while meeting the requirements of low-carbon economic operation,this paper proposes a two-stage robust optimal dispatch model for an integrated wind-solar-hydro-thermal-storage energy system with coupled power-to-gas(P2G)and carbon capture system(CCS).First,a mathematical model of the integrated wind-solar-hydro-thermal-storage energy system with P2G-CCS coupling is developed to promote internal carbon cycling and enhance the capability to accommodate renewable energy.Second,the scheduling problem is formulated as a two-stage robust optimization model.A cardinality-based uncertainty set is adopted to model deviations in renewable energy output,and a column-and-constraint generation(C&CG)algorithm is applied to efficiently solve the problem.Comparative case studies are conducted to quantify the performance differences between the proposed method and deterministic optimization and stochastic optimization.The results show that compared with conventional optimization methods,the proposed two-stage robust optimization model increases the carbon utilization rate of the IES to 24.38%and raises the renewable energy accommodation rate to 100%;the system's intraday balancing cost and total operating cost are reduced by 94.54%and 4.49%,respectively,and the overall indirect carbon emissions decrease by 57.96%,thus achieving coordinated optimization of economic performance,robustness,and low-carbon characteristics.In addition,further analysis of the robustness parameter indicates that an overly conservative robust strategy leads to worse economic performance and higher carbon emissions.This study provides quantitative guidance for balancing robustness,economy,and environmental benefits in integrated energy system operation. 展开更多
关键词 Integrated wind-solar-hydro-thermal-storage system two-stage robust optimization uncertainty P2G-CCS renewable energy low-carbon economic dispatch
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Low-Carbon and Economic Dispatch Strategy Considering Optimal Multi-Machine Allocation and Power Control for Grid-Forming Energy Storage in Micro-Energy Grids 认领 引用
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作者 Yiqun Kang Zhe Li +3 位作者 Li You Haozhe Xiong Yuxuan Hu Fei Wang 《Energy Engineering》 EI 2026年第9期80-94,共15页
As the world's energy framework shifts towards a low-carbon model,the widespread incorporation of renewable energy(RE)sources,primarily wind power and photovoltaics(PV),into the power grid is an unavoidable develo... As the world's energy framework shifts towards a low-carbon model,the widespread incorporation of renewable energy(RE)sources,primarily wind power and photovoltaics(PV),into the power grid is an unavoidable development.The micro-energy grid(MEG),as an integrated system that combines distributed energy,energy storage(ES),and power loads,can achieve efficient consumption of RE by implementing multi-machine optimal allocation and unified coordinated power control for parallel operation of grid-forming energy storage(GFES).For this purpose,this paper puts forward a low-carbon and economic dispatch strategy for MEG that considers multi-machine optimal allocation of GFES and unified coordinated power control for parallel operation.The strategy constructs a multi-machine optimal allocation model for GFES in the outer layer,striving to achieve the lowest operational costs for the MEG.In the inner layer,based on the obtained optimal multi-machine allocation scheme for GFES,a unified coordinated power control model for parallel operation of GFES in the MEG is constructed,targeting the minimization of pollutant gas emissions and system voltage deviation.The plant growth simulation algorithm(PGSA)is employed to solve the established models for multi-machine optimal allocation of GFES and unified coordinated power control for parallel operation in the MEG.Through simulation analysis,it has been substantiated that the proposed method can effectively achieve multi-machine optimal allocation and unified coordinated power control for parallel operation of GFES,reduce the operational costs of the MEG system,while also decreasing pollutant gas emissions and stabilizing system operation,thereby offering robust and substantial backing for the attainment of a low-carbon economy and the pursuit of sustainable development. 展开更多
关键词 Grid-forming energy storage unified coordinated power control micro energy grid plant growth simulation algorithm low-carbon and economic dispatching strategy
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Distributed Economic Dispatch Algorithms of Microgrids Integrating Grid-Connected and Isolated Modes 认领 引用 被引量：1
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作者 Zhongxin Liu Yanmeng Zhang +1 位作者 Yalin Zhang Fuyong Wang 《IEEE/CAA Journal of Automatica Sinica》 SCIE EI CSCD 2025年第1期86-98,共13页
The economic dispatch problem(EDP) of microgrids operating in both grid-connected and isolated modes within an energy internet framework is addressed in this paper. The multi-agent leader-following consensus algorithm... The economic dispatch problem(EDP) of microgrids operating in both grid-connected and isolated modes within an energy internet framework is addressed in this paper. The multi-agent leader-following consensus algorithm is employed to address the EDP of microgrids in grid-connected mode, while the push-pull algorithm with a fixed step size is introduced for the isolated mode. The proposed algorithm of isolated mode is proven to converge to the optimum when the interaction digraph of microgrids is strongly connected. A unified algorithmic framework is proposed to handle the two modes of operation of microgrids simultaneously, enabling our algorithm to achieve optimal power allocation and maintain the balance between power supply and demand in any mode and any mode switching. Due to the push-pull structure of the algorithm and the use of fixed step size,the proposed algorithm can better handle the case of unbalanced graphs, and the convergence speed is improved. It is documented that when the transmission topology is strongly connected and there is bi-directional communication between the energy router and its neighbors, the proposed algorithm in composite mode achieves economic dispatch even with arbitrary mode switching.Finally, we demonstrate the effectiveness and superiority of our algorithm through numerical simulations. 展开更多
关键词 Consensus algorithm distributed optimization economic dispatch(ED) energy router(ER) multi-agent systems
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Harnessing Trend Theory to Enhance Distributed Proximal Point Algorithm Approaches for Multi-Area Economic Dispatch Optimization 认领 引用
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作者 Yaming Ren Xing Deng 《Computers, Materials & Continua》 SCIE EI 2025年第3期4503-4533,共31页
The exponential growth in the scale of power systems has led to a significant increase in the complexity of dispatch problem resolution,particularly within multi-area interconnected power grids.This complexity necessi... The exponential growth in the scale of power systems has led to a significant increase in the complexity of dispatch problem resolution,particularly within multi-area interconnected power grids.This complexity necessitates the employment of distributed solution methodologies,which are not only essential but also highly desirable.In the realm of computational modelling,the multi-area economic dispatch problem(MAED)can be formulated as a linearly constrained separable convex optimization problem.The proximal point algorithm(PPA)is particularly adept at addressing such mathematical constructs effectively.This study introduces parallel(PPPA)and serial(SPPA)variants of the PPA as distributed algorithms,specifically designed for the computational modelling of the MAED.The PPA introduces a quadratic term into the objective function,which,while potentially complicating the iterative updates of the algorithm,serves to dampen oscillations near the optimal solution,thereby enhancing the convergence characteristics.Furthermore,the convergence efficiency of the PPA is significantly influenced by the parameter c.To address this parameter sensitivity,this research draws on trend theory from stock market analysis to propose trend theory-driven distributed PPPA and SPPA,thereby enhancing the robustness of the computational models.The computational models proposed in this study are anticipated to exhibit superior performance in terms of convergence behaviour,stability,and robustness with respect to parameter selection,potentially outperforming existing methods such as the alternating direction method of multipliers(ADMM)and Auxiliary Problem Principle(APP)in the computational simulation of power system dispatch problems.The simulation results demonstrate that the trend theory-based PPPA,SPPA,ADMM and APP exhibit significant robustness to the initial value of parameter c,and show superior convergence characteristics compared to the residual balancing ADMM. 展开更多
关键词 Multi-area economic dispatch problem proximal point algorithm trend theory
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Low-Carbon Economic Dispatch of Electric-Thermal-Hydrogen Integrated Energy System Based on Carbon Emission Flow Tracking and Step-Wise Carbon Price 认领 引用
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作者 Yukun Yang Jun He +2 位作者 Wenfeng Chen Zhi Li Kun Chen 《Energy Engineering》 EI 2025年第11期4653-4678,共26页
To address the issues of unclear carbon responsibility attribution,insufficient renewable energy absorption,and simplistic carbon trading mechanisms in integrated energy systems,this paper proposes an electricheat-hyd... To address the issues of unclear carbon responsibility attribution,insufficient renewable energy absorption,and simplistic carbon trading mechanisms in integrated energy systems,this paper proposes an electricheat-hydrogen integrated energy system(EHH-IES)optimal scheduling model considering carbon emission stream(CES)and wind-solar accommodation.First,the CES theory is introduced to quantify the carbon emission intensity of each energy conversion device and transmission branch by defining carbon emission rate,branch carbon intensity,and node carbon potential,realizing accurate tracking of carbon flow in the process of multi-energy coupling.Second,a stepped carbon pricing mechanism is established to dynamically adjust carbon trading costs based on the deviation between actual carbon emissions and initial quotas,strengthening the emission reduction incentive.Finally,a lowcarbon economic dispatch model is constructed with the objectives of minimizing operation cost,carbon trading cost,wind-solar curtailment penalty cost,and energy loss.Simulation results show that compared with the traditional economic dispatch scheme 3,the proposed schemel reduces carbon emissions by 53.97%and wind-solar curtailment by 68.89%with a 16.10%increase in total cost.This verifies that the model can effectively improve clean energy utilization and reduce carbon emissions,achieving low-carbon economic operation of EHH-IES,with CES theory ensuring precise carbon flow tracking across multi-energy links. 展开更多
关键词 Carbon emission streams integrated energy systems stepped carbon price low carbon economic dispatch wind-solar accommodation
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Environmental and Economic Optimization of Multi-Source Power Real-Time Dispatch Based on DGADE-HDJ 认领 引用
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作者 Bin Jiang Houbin Wang 《Energy Engineering》 EI 2025年第5期2001-2057,共57页
Considering the special features of dynamic environment economic dispatch of power systems with high dimensionality,strong coupling,nonlinearity,and non-convexity,a GA-DE multi-objective optimization algorithm based o... Considering the special features of dynamic environment economic dispatch of power systems with high dimensionality,strong coupling,nonlinearity,and non-convexity,a GA-DE multi-objective optimization algorithm based on dual-population pseudo-parallel genetic algorithm-differential evolution is proposed in this paper.The algorithm is based on external elite archive and Pareto dominance,and it adopts the cooperative co-evolution mechanism of differential evolution and genetic algorithm.Average entropy and cubic chaoticmapping initialization strategies are proposed to increase population diversity.In the proposed method,we analyze the distribution of neighboring solutions and apply a new Pareto solution set pruning approach.Unlike traditional models,this work takes the transmission losses as an optimization target and overcomes complex model constraints through a dynamic relaxation constraint approach.To solve the uncertainty caused by integrating wind and photovoltaic energy in power system scheduling,a multi-objective dynamic environment economical dispatch model is set up that takes the system spinning reserve and network highest losses into account.In this paper,the DE algorithm is improved to form the DGAGE algorithm for the objective optimization of the overall power system,The DE algorithm part of DGAGE is combined with the JAYA algorithm to form the system scheduling HDJ algorithm for multiple energy sources connected to the grid.The effectiveness of the proposed method is demonstrated using CEC2022 and CEC2005 test functions,showing robust optimization performance.Validation on a classical 10-unit system confirms the feasibility of the proposed algorithm in addressing power system scheduling issues.This approach provides a novel solution for dynamic power dispatch systems. 展开更多
关键词 Dynamic environment economic dispatch dual-population cooperative evolution wind-photovoltaic integration dynamic relaxation constraint mechanism differential evolution algorithm JAYA algorithm
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Modified Cuckoo Search Algorithm to Solve Economic Power Dispatch Optimization Problems 认领 引用 被引量：18
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作者 Jian Zhao Shixin Liu +2 位作者 Mengchu Zhou Xiwang Guo Liang Qi 《IEEE/CAA Journal of Automatica Sinica》 SCIE EI CSCD 2018年第4期794-806,共13页
A modified cuckoo search(CS) algorithm is proposed to solve economic dispatch(ED) problems that have nonconvex, non-continuous or non-linear solution spaces considering valve-point effects, prohibited operating zones,... A modified cuckoo search(CS) algorithm is proposed to solve economic dispatch(ED) problems that have nonconvex, non-continuous or non-linear solution spaces considering valve-point effects, prohibited operating zones, transmission losses and ramp rate limits. Comparing with the traditional cuckoo search algorithm, we propose a self-adaptive step size and some neighbor-study strategies to enhance search performance.Moreover, an improved lambda iteration strategy is used to generate new solutions. To show the superiority of the proposed algorithm over several classic algorithms, four systems with different benchmarks are tested. The results show its efficiency to solve economic dispatch problems, especially for large-scale systems. 展开更多
关键词 Cuckoo search(CS) economic dispatch(ED) prohibited operating zones ramp rate limits valve-point effects
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Boosting Kernel Search Optimizer with Slime Mould Foraging Behavior for Combined Economic Emission Dispatch Problems 认领 引用 被引量：7
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作者 Ruyi Dong Lixun Sun +3 位作者 Long Ma Ali Asghar Heidari Xinsen Zhou Huiling Chen 《Journal of Bionic Engineering》 SCIE EI CSCD 2023年第6期2863-2895,共33页
Reducing pollutant emissions from electricity production in the power system positively impacts the control of greenhouse gas emissions.Boosting kernel search optimizer(BKSO)is introduced in this research to solve the... Reducing pollutant emissions from electricity production in the power system positively impacts the control of greenhouse gas emissions.Boosting kernel search optimizer(BKSO)is introduced in this research to solve the combined economic emission dispatch(CEED)problem.Inspired by the foraging behavior in the slime mould algorithm(SMA),the kernel matrix of the kernel search optimizer(KSO)is intensified.The proposed BKSO is superior to the standard KSO in terms of exploitation ability,robustness,and convergence rate.The CEC2013 test function is used to assess the improved KSO's performance and compared to 11 well-known optimization algorithms.BKSO performs better in statistical results and convergence curves.At the same time,BKSO achieves better fuel costs and fewer pollution emissions by testing with four real CEED cases,and the Pareto solution obtained is also better than other MAs.Based on the experimental results,BKSO has better performance than other comparable MAs and can provide more economical,robust,and cleaner solutions to CEED problems. 展开更多
关键词 Combined economic emission dispatch Kernel search optimization Slime mould algorithm Valve point effect Greenhouse gases
Scenario-oriented hybrid particle swarm optimization algorithm for robust economic dispatch of power system with wind power 认领 引用 被引量：6
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作者 WANG Bing ZHANG Pengfei +2 位作者 HE Yufeng WANG Xiaozhi ZHANG Xianxia 《Journal of Systems Engineering and Electronics》 SCIE CSCD 2022年第5期1143-1150,共8页
An economic dispatch problem for power system with wind power is discussed.Using discrete scenario to describe uncertain wind powers,a threshold is given to identify bad scenario set.The bad-scenario-set robust econom... An economic dispatch problem for power system with wind power is discussed.Using discrete scenario to describe uncertain wind powers,a threshold is given to identify bad scenario set.The bad-scenario-set robust economic dispatch model is established to minimize the total penalties on bad scenarios.A specialized hybrid particle swarm optimization(PSO)algorithm is developed through hybridizing simulated annealing(SA)operators.The SA operators are performed according to a scenario-oriented adaptive search rule in a neighborhood which is constructed based on the unit commitment constraints.Finally,an experiment is conducted.The computational results show that the developed algorithm outperforms the existing algorithms. 展开更多
关键词 wind power robust economic dispatch scenario simulated annealing(SA) particle swarm optimization(PSO)
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A low-carbon economic dispatch model for electricity market with wind power based on improved ant-lion optimisation algorithm 认领 引用 被引量：5
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作者 Renwu Yan Yihan Lin +1 位作者 Ning Yu Yi Wu 《CAAI Transactions on Intelligence Technology》 SCIE EI 2023年第1期29-39,共11页
Introducing carbon trading into electricity market can convert carbon dioxide into schedulable resources with economic value.However,the randomness of wind power generation puts forward higher requirements for electri... Introducing carbon trading into electricity market can convert carbon dioxide into schedulable resources with economic value.However,the randomness of wind power generation puts forward higher requirements for electricity market transactions.Therefore,the carbon trading market is introduced into the wind power market,and a new form of low-carbon economic dispatch model is developed.First,the economic dispatch goal of wind power is be considered.It is projected to save money and reduce the cost of power generation for the system.The model includes risk operating costs to account for the impact of wind power output variability on the system,as well as wind farm negative efficiency operating costs to account for the loss caused by wind abandonment.The model also employs carbon trading market metrics to achieve the goal of lowering system carbon emissions,and analyze the impact of different carbon trading prices on the system.A low-carbon economic dispatch model for the wind power market is implemented based on the following two goals.Finally,the solution is optimised using the Ant-lion optimisation method,which combines Levi's flight mechanism and golden sine.The proposed model and algorithm's rationality is proven through the use of cases. 展开更多
关键词 ant-lion optimisation algorithm carbon trading Levi flight low-carbon economic dispatch wind power market
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Low Carbon Economic Dispatch of Integrated Energy System Considering Power Supply Reliability and Integrated Demand Response 认领 引用 被引量：2
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作者 Jian Dong Haixin Wang +3 位作者 Junyou Yang Liu Gao Kang Wang Xiran Zhou 《Computer Modeling in Engineering & Sciences》 SCIE EI 2022年第7期319-340,共22页
Integrated energy system optimization scheduling can improve energy efficiency and low carbon economy.This paper studies an electric-gas-heat integrated energy system,including the carbon capture system,energy couplin... Integrated energy system optimization scheduling can improve energy efficiency and low carbon economy.This paper studies an electric-gas-heat integrated energy system,including the carbon capture system,energy coupling equipment,and renewable energy.An energy scheduling strategy based on deep reinforcement learning is proposed to minimize operation cost,carbon emission and enhance the power supply reliability.Firstly,the lowcarbon mathematical model of combined thermal and power unit,carbon capture system and power to gas unit(CCP)is established.Subsequently,we establish a low carbon multi-objective optimization model considering system operation cost,carbon emissions cost,integrated demand response,wind and photovoltaic curtailment,and load shedding costs.Furthermore,considering the intermittency of wind power generation and the flexibility of load demand,the low carbon economic dispatch problem is modeled as a Markov decision process.The twin delayed deep deterministic policy gradient(TD3)algorithm is used to solve the complex scheduling problem.The effectiveness of the proposed method is verified in the simulation case studies.Compared with TD3,SAC,A3C,DDPG and DQN algorithms,the operating cost is reduced by 8.6%,4.3%,6.1%and 8.0%. 展开更多
关键词 Integrated energy system twin delayed deep deterministic policy gradient economic dispatch power supply reliability integrated demand response
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Energy Economic Dispatch for Photovoltaic-Storage via Distributed Event-Triggered Surplus Algorithm 认领 引用 被引量：2
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作者 Kaicheng Liu Chen Liang +2 位作者 Naiyue Wu Xiaoyang Dong Hui Yu 《Energy Engineering》 EI 2024年第9期2621-2637,共17页
This paper presents a novel approach to economic dispatch in smart grids equipped with diverse energy devices.This method integrates features including photovoltaic(PV)systems,energy storage coupling,varied energy rol... This paper presents a novel approach to economic dispatch in smart grids equipped with diverse energy devices.This method integrates features including photovoltaic(PV)systems,energy storage coupling,varied energy roles,and energy supply and demand dynamics.The systemmodel is developed by considering energy devices as versatile units capable of fulfilling various functionalities and playing multiple roles simultaneously.To strike a balance between optimality and feasibility,renewable energy resources are modeled with considerations for forecasting errors,Gaussian distribution,and penalty factors.Furthermore,this study introduces a distributed event-triggered surplus algorithm designed to address the economic dispatch problem by minimizing production costs.Rooted in surplus theory and finite time projection,the algorithm effectively rectifies network imbalances caused by directed graphs and addresses local inequality constraints.The algorithm greatly reduces the communication burden through event triggering mechanism.Finally,both theoretical proofs and numerical simulations verify the convergence and event-triggered nature of the algorithm. 展开更多
关键词 Fully distributed algorithm economic dispatch directed graph renewable energy resource
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Two-Stage Low-Carbon Economic Dispatch of Integrated Demand Response-Enabled Integrated Energy System with Ladder-Type Carbon Trading 认领 引用 被引量：2
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作者 Song Zhang Wensheng Li +3 位作者 Zhao Li Xiaolei Zhang Zhipeng Lu Xiaoning Ge 《Energy Engineering》 EI 2023年第1期181-199,共19页
Driven by the goal of“carbon neutrality”and“emission peak”,effectively controlling system carbon emissions has become significantly important to governments around the world.To this end,a novel two-stage low-carbo... Driven by the goal of“carbon neutrality”and“emission peak”,effectively controlling system carbon emissions has become significantly important to governments around the world.To this end,a novel two-stage low-carbon economic scheduling framework that considers the coordinated optimization of ladder-type carbon trading and integrated demand response(IDR)is proposed in this paper for the integrated energy system(IES),where the first stage determines the energy consumption plan of users by leveraging the price-based electrical-heat IDR.In contrast,the second stage minimizes the system total cost to optimize the outputs of generations with consideration of the uncertainty of renewables.In addition,to fully exploit the system’s emission reduction potential,a carbon trading cost model with segmented CO2 emission intervals is built by introducing a reward-penalty ladder-type carbon trading mechanism,and the flexible thermal comfort elasticity of customers is taken into account by putting forward a predicted mean vote index on the load side.The CPLEX optimizer resolves the two-stage model,and the study results on a modified IES situated in North China show the proposed model can effectively reduce carbon emissions and guarantee economical efficiency operation of the system. 展开更多
关键词 Integrated energy system low-carbon economic dispatch integrated demand response ladder-type carbon trading thermal comfort elasticity
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Black Widow Optimization for Multi Area Economic Emission Dispatch 认领 引用 被引量：2
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作者 G.Girishkumar S.Ganesan +1 位作者 N.Jayakumar S.Subramanian 《Intelligent Automation & Soft Computing》 SCIE 2023年第1期609-625,共17页
The optimizationfield has grown tremendously,and new optimization techniques are developed based on statistics and evolutionary procedures.There-fore,it is necessary to identify a suitable optimization technique for a... The optimizationfield has grown tremendously,and new optimization techniques are developed based on statistics and evolutionary procedures.There-fore,it is necessary to identify a suitable optimization technique for a particular application.In this work,Black Widow Optimization(BWO)algorithm is intro-duced to minimize the cost functions in order to optimize the Multi-Area Economic Dispatch(MAED).The BWO is implemented for two different-scale test systems,comprising 16 and 40 units with three and four areas.The performance of BWO is compared with the available optimization techniques in the literature to demonstrate the strategy’s efficacy.Results show that the optimized cost for four areas with 16 units is found to be 7336.76$/h,whereas it is 121,589$/h for four areas with 40 units using BWO.It is also noted that optimization algo-rithms other than BWO require higher cost value.The best-optimized solution for emission is achieved at 9.2784e+06 tones/h,and it is observed that there is a considerable difference between the worst and the best values.Also,the suggested technique is implemented for large-scale test systems successfully with high precision,and rapid convergence occurs in MAED. 展开更多
关键词 Black widow optimization algorithm multi-objective multi-area economic dispatch emission optimization cost optimization
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Two-stage stochastic approach for spinning reserve allocation in dynamic economic dispatch 认领 引用 被引量：1
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作者 杨明 张利 +1 位作者 韩学山 程凤璐 《Journal of Central South University》 SCIE EI CAS 2014年第2期577-586,共10页
A novel approach was proposed to allocate spinning reserve for dynamic economic dispatch.The proposed approach set up a two-stage stochastic programming model to allocate reserve.The model was solved using a decompose... A novel approach was proposed to allocate spinning reserve for dynamic economic dispatch.The proposed approach set up a two-stage stochastic programming model to allocate reserve.The model was solved using a decomposed algorithm based on Benders' decomposition.The model and the algorithm were applied to a simple 3-node system and an actual 445-node system for verification,respectively.Test results show that the model can save 84.5 US $ cost for the testing three-node system,and the algorithm can solve the model for 445-node system within 5 min.The test results also illustrate that the proposed approach is efficient and suitable for large system calculation. 展开更多
关键词 power system dynamic economic dispatch spinning reserve response risk two-stage stochastic programming Benders＇ decomposition
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A PI+R Control Scheme Based on Multi-Agent Systems for Economic Dispatch in Isolated BESSs 认领 引用 被引量：1
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作者 Yalin Zhang Zhongxin Liu Zengqiang Chen 《IEEE/CAA Journal of Automatica Sinica》 SCIE EI CSCD 2024年第10期2154-2165,共12页
Battery energy storage systems(BESSs)are widely used in smart grids.However,power consumed by inner impedance and the capacity degradation of each battery unit become particularly severe,which has resulted in an incre... Battery energy storage systems(BESSs)are widely used in smart grids.However,power consumed by inner impedance and the capacity degradation of each battery unit become particularly severe,which has resulted in an increase in operating costs.The general economic dispatch(ED)algorithm based on marginal cost(MC)consensus is usually a proportional(P)controller,which encounters the defects of slow convergence speed and low control accuracy.In order to solve the distributed ED problem of the isolated BESS network with excellent dynamic and steady-state performance,we attempt to design a proportional integral(PI)controller with a reset mechanism(PI+R)to asymptotically promote MC consensus and total power mismatch towards 0 in this paper.To be frank,the integral term in the PI controller is reset to 0 at an appropriate time when the proportional term undergoes a zero crossing,which accelerates convergence,improves control accuracy,and avoids overshoot.The eigenvalues of the system under a PI+R controller is well analyzed,ensuring the regularity of the system and enabling the reset mechanism.To ensure supply and demand balance within the isolated BESSs,a centralized reset mechanism is introduced,so that the controller is distributed in a flow set and centralized in a jump set.To cope with Zeno behavior and input delay,a dwell time that the system resides in a flow set is given.Based on this,the system with input delays can be reduced to a time-delay free system.Considering the capacity limitation of the battery,a modified MC scheme with PI+R controller is designed.The correctness of the designed scheme is verified through relevant simulations. 展开更多
关键词 Battery energy storage system(BESS) distributed control economic dispatch multi-agent system reset control
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Multiple objective particle swarm optimization technique for economic load dispatch 认领 引用 被引量：4
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作者 赵波 曹一家 《Journal of Zhejiang University-SCIENCE A》 CAS 2005年第5期420-427,共8页
A multi-objective particle swarm optimization (MOPSO) approach for multi-objective economic load dispatch problem in power system is presented in this paper. The economic load dispatch problem is a non-linear constrai... A multi-objective particle swarm optimization (MOPSO) approach for multi-objective economic load dispatch problem in power system is presented in this paper. The economic load dispatch problem is a non-linear constrained multi-objective optimization problem. The proposed MOPSO approach handles the problem as a multi-objective problem with competing and non-commensurable fuel cost, emission and system loss objectives and has a diversity-preserving mechanism using an external memory (call “repository”) and a geographically-based approach to find widely different Pareto-optimal solutions. In addition, fuzzy set theory is employed to extract the best compromise solution. Several optimization runs of the proposed MOPSO approach were carried out on the standard IEEE 30-bus test system. The results revealed the capabilities of the proposed MOPSO approach to generate well-distributed Pareto-optimal non-dominated solutions of multi-objective economic load dispatch. Com- parison with Multi-objective Evolutionary Algorithm (MOEA) showed the superiority of the proposed MOPSO approach and confirmed its potential for solving multi-objective economic load dispatch. 展开更多
关键词 Economic load dispatch Multi-objective optimization Multi-objective particle swarm optimization
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Dynamic economic dispatch combining network flow and interior point method 认领 引用 被引量：1
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作者 韩学山 赵建国 柳焯 《Journal of Harbin Institute of Technology(New Series)》 EI CAS 2003年第4期461-466,共6页
Under the environment of electric power market, economic dispatch (ED) problem should consider network constraints, unit ramp rates, besides the basic constraints. For this problem, it is important to establish the ef... Under the environment of electric power market, economic dispatch (ED) problem should consider network constraints, unit ramp rates, besides the basic constraints. For this problem, it is important to establish the effective model and algorithm. This paper examines the decoupled conditions that affect the solution optimality to this problem. It proposes an effective model and solution method. Based on the look-ahead technique, it finds the number of time intervals to guarantee the solution optimality. Next, an efficient technique for finding the optimal solution via the interior point methods is described. Test cases, which include dispatching six units over 5 time intervals on the IEEE 30 test system with line flows and ramp constraints are presented. Results indicate that the computational effort as measured by iteration counts or execution time varies only modestly with the problem size. 展开更多
关键词 Economic dispatch optimization network constraints ramp constraints interior point method
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