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Low Carbon economic dispatch of Integrated Energy System Considering Power Supply Reliability and Integrated Demand Response

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Computer Modeling in Engineering & Sciences 2022年第7期131卷 319-340页

作者： Jian Dong Haixin Wang Junyou Yang Liu Gao Kang Wang Xiran Zhou School of Electrical Engineering Shenyang University of TechnologyShenyang110870China

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%.

关键词： Integrated energy system twin delayed deep deterministic policy gradient economic dispatch power supply reliability integrated demand response

economic dispatch Considering Hourly Capacity Allocation with a Variable Renewable and Hydro-Based Generation Portfolio

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Energy and Power Engineering 2022年第10期14卷 594-614页

作者： Roney N. Vitorino Dorel S. Ramos Karen Tapia-Ahumada Sergey Paltsev John M. Reilly Energy Research Office Rio de Janeiro Brazil Polytechnic School University of Sao Paulo Sao Paulo Brazil Massachusetts Institute of Technology Cambridge USA

The objective of this paper is to assess an economic dispatch considering a power system portfolio, which includes predominant amount of hydro power and increasing quantities of intermittent renewables in relation to the total electric capacity. With growing importance of intermittent wind and solar generation taking part into power systems worldwide, there is need for greater chronological resolution to estimate the flexibility of the power system to offer firm capacity. In this way, a linear optimization model operating hourly is developed to calculate the minimum power system cost, while stablishing the capacity allocation to meet the projected load throughout one-year simulation, as an estimation of how the hourly economic dispatch impacts the scheduling of generators belonging to a power system with this portfolio composition. A central focus is how to operate the available hydro capacity to back up intermittent renewables, evaluating the physical hydro operating constraints, monthly energy balance and maximum power availability. A case study was simulated based on the Brazil’s power system configuration, showing that existing hydro capacity provide hourly flexibility to back-up intermittent renewables, potentially saving 1.2 Billion R$, about 3.6% of total system cost referred to 2019. It is worthwhile to realize that the developed methodology can be employed to other power systems with similar capacity portfolio structure for the purpose of calculating its optimum allocation for a specified region and target year.

关键词： economic dispatch Energy Planning Operation Flexibility Power System Transmission System Variable Renewable Energy

economic dispatch of Power Systems with Virtual Power Plant Based Interval Optimization Method

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CSEE Journal of Power and Energy Systems 2016年第1期2卷 74-80页

作者： Chongxin Huang Dong Yue Jun Xie Yaping Li Ke Wang Institute of Advanced Technology Nanjing University of Posts and TelecommunicationsNanjing 210023China China Electric Power Research Institute Nanjing 210003China

Load prediction and power prediction uncertainties are inevitable aspects of a virtual power plant(VPP).In power system economic dispatch(ED)modeling,the interval is used to describe prediction uncertainties.An ED model with interval uncertainty is established in this paper.The probability degree definition is adopted to convert the interval-based economic dispatch model into a deterministic model for the purposes of solving the modeling problem.Simulation tests are performed on a 10-machine system using professional optimization software(LINGO).The simulation results verify the validity of the proposed interval-based scheme for the economic dispatch of a power system with VPP.

关键词： economic dispatch interval optimization method uncertainty virtual power plant

Optimal Combined Heat and Power economic dispatch Using Stochastic Fractal Search Algorithm

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Journal of Modern Power Systems and Clean Energy 2020年第2期8卷 276-286页

作者： Muwaffaq I.Alomoush the Department of Electrical Power Engineering Hijjawi Faculty for Engineering TechnologyYarmouk UniversityIrbidJordan

Combined heat and power(CHP)generation is a valuable scheme for concurrent generation of electrical and thermal energies.The interdependency of power and heat productions in CHP units introduces complications and non-convexities in their modeling and optimization.This paper uses the stochastic fractal search(SFS)optimization technique to treat the highly non-linear CHP economic dispatch(CHPED)problem,where the objective is to minimize the total operation cost of both power and heat from generation units while fulfilling several operation interdependent limits and constraints.The CHPED problem has bounded feasible operation regions and many local minima.The SFS,which is a recent metaheuristic global optimization solver,outranks many current reputable solvers.Handling constraints of the CHPED is achieved by employing external penalty parameters,which penalize infeasible solution during the iterative process.To confirm the strength of this algorithm,it has been tested on two different test systems that are regularly used.The obtained outcomes are compared with former outcomes achieved by many different methods reported in literature of CHPED.The results of this work affirm that the SFS algorithm can achieve improved near-global solution and compare favorably with other commonly used global optimization techniques in terms of the quality of solution,handling of constraints and computation time.

关键词： Combined heat and power(CHP) economic dispatch global optimization metaheuristic algorithms non-convex optimization problem power systems stochastic fractal search

Resilient distributed economic dispatch of a cyber-power system under DoS attack

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Frontiers of Information Technology & Electronic Engineering 2021年第1期22卷 40-50页

作者： Feisheng YANG Xuhui LIANG Xiaohong GUAN MOE Key Laboratory of Intelligent Network and Network Security Xi'an Jiaotong UniversityXi'an 710049China School of Automation Northwestern Polytechnical UniversityXVan 710129China

The economic dispatch problem of a smart grid under vicious denial of service(DoS)is the main focus of this paper.Taking the actual situation of power generation as a starting point,a new distributed optimization model is established which takes the environmentai pollution penalty into account.For saving the limited bandwidth,a novel distributed event-triggered scheme is proposed to keep the resilience and economy of a class of cyber-power syst ems when the communication net work is subject to malicious DoS attack.Then an improved multi-agent consensus protocol based on the gradient descent idea is designed to solve the minimization problem,and the prerequisites to minimize the system power generation cost are analyzed from the aspects of optimality and stability.Finally,the theoretical results are verified through a single-area 10-generat or unit simulation.

关键词： economic dispatch Denial of service(DoS)attack Resilient event-triggered scheme Distributed optimization

A Fast Solution Method to economic dispatch Type Problem

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Journal of Modern Power Systems and Clean Energy 2021年第5期9卷 1227-1232页

作者： Chenjia Feng Chengcheng Shao Xifan Wang Life School of Electrical Engineering Xi’an Jiaotong UniversityXi’an 710049China

economic dispatch(ED)aims to minimize the generation cost subject to power balance constraints.It is extensively used in power system operation and planning.ED problem as well as other problems with the same formulation are named as ED-type problems in this letter and a fast solution method is provided.The proposed method is achieved by solving a series of relaxed problems.With a closed-form solution for the relaxed ED-type problems,it is demonstrated that the proposed method consumes far less computing time and memory space than the off-the-shelf solvers and other quadratic programming(QP)methods.Finally,the effectiveness and computational efficiency of the proposed method are verified by the case studies,which shows the great potential in power system planning and operation.

关键词： Fast solution economic dispatch closed-form solution quadratic programming

economic dispatch of Electrical Power System Based on the Multi-objective Co-evolutionary Algorithm

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Journal of Donghua University(English Edition) 2016年第4期33卷 652-655页

作者：张向锋杨凤惠 College of Electrical Engineering Shanghai Dianji University

It is important to distribute the load efficiently to minimize the cost of the economic dispatch of electrical power system. The uncertainty and volatility of wind energy make the economic dispatch much more complex when the general power systems are combined with wind farms. The short term wind power prediction method was discussed in this paper. The method was based on the empirical mode decomposition (EMD) and ensemble empirical mode decomposition (EEMD). Furthermore,the effect of wind farms on the traditional economic dispatch of electrical power system was analyzed. The mathematical model of the economic dispatch was established considering the environmental factors and extra spinning reserve cost. The multi-objective co-evolutionary algorithm was used to figure out the model. And the results were compared with the NSGA-Ⅱ(non-dominated sorting genetic algorithm-Ⅱ) to verify its feasibility.

关键词： economic dispatch multi-objective co-evolutionary algorithm(MOCEA) wind farms electrical power system

A self-learning TLBO based dynamic economic/environmental dispatch considering multiple plug-in electric vehicle loads

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Journal of Modern Power Systems and Clean Energy 2014年第4期2卷 298-307页

作者： Zhile YANG Kang LI Qun NIU Yusheng XUE Aoife FOLEY School of Electrical Electronics and Computer ScienceQueen’s University BelfastBelfast BT95AHUK Shanghai Key Laboratory of Power Station Automation Technology School of Mechatronic Engineering and AutomationShanghai UniversityShanghai 200072China NARI Group Corporation(State Grid Electric Power Research Institute) Nanjing 211106China School of Mechanical and Aerospace Engineering Queen’s UniversityBelfast BT95AHUK

economic and environmental load dispatch aims to determine the amount of electricity generated from power plants to meet load demand while minimizing fossil fuel costs and air pollution emissions subject to operational and licensing requirements.These two scheduling problems are commonly formulated with non-smooth cost functions respectively considering various effects and constraints,such as the valve point effect,power balance and ramprate limits.The expected increase in plug-in electric vehicles is likely to see a significant impact on the power system due to high charging power consumption and significant uncertainty in charging times.In this paper,multiple electric vehicle charging profiles are comparatively integrated into a 24-hour load demand in an economic and environment dispatch model.Self-learning teaching-learning based optimization(TLBO)is employed to solve the non-convex non-linear dispatch problems.Numerical results onwell-known benchmark functions,as well as test systems with different scales of generation units show the significance of the new scheduling method.

关键词： economic dispatch Environmental dispatch Plug-in electric vehicle Self-learning Teaching learning based optimization Peak charging Off-peak charging Stochastic charging

Combined Electric and Heat System Testbeds for Power Flow Analysis and economic dispatch

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CSEE Journal of Power and Energy Systems 2021年第1期7卷 34-44页

作者： Xin Qin Xinwei Shen Ye Guo Zhaoguang Pan Qinglai Guo Hongbin Sun the Tsinghua-Berkeley Shen zhen Institute Tsinghua UniversityShenzhen 518055China the department of electric engineering Tsinghua UniversityBeijing 100084China

In combined electric and heat systems,selecting a suitable testbed for power flow analysis or economic dispatch is not easy:a large number of existing testbeds are not opensource,while others are difficult to be reused by other researchers due to the particularity of system scale,topology,and data.In this paper,we present three open-source testbeds with different scales based on practical combined electric and heat systems.To satisfy researchers"specific demands on the system topology and data,we also discuss how to modify testbeds based on existing topologies and data.Researchers can use the testbeds presented in this paper to test their innovative methods for power flow analysis and economic dispatch,and can also design their own testbeds based on the methodology in this paper,using published topologies and data.

关键词： Combined heat and power system economic dispatch power flow testbed