| Energy is the cornerstone of human survival and the lifeblood of social prosperity.In recent years,the increasingly arduous tasks of energy saving,emission reduction and flexibility promotion,are driving China to accelerate the transformation and upgrading of energy structure,and impelling the whole energy industry to build a clean,low-carbon,safe and efficient modern energy system.As the share of renewable energy on the supply side has steadily lifted,and the heterogeneous synergy of diverse energy flows has gradually evolved,the concept of integrated energy system(IES)aiming at highly "source-grid-load-storage"coordinative energy integration has emerged.The study of multiple temporal-spatial-scale modeling and scheduling mechanism of IES are in line with the requirements of energy transformation and the orientation of energy revolution,and have huge engineering application value and multi-energy complementary benefits.At the same time,the new service format and novel operation mode of multi-energy coupling also put forward challenges for the development of IES from three perspectives:new modes for flexible and multi-energy supply-demand interaction,new problems for source-grid-load-storage stochastic optimization,and new methods for low-carbon and complementary wind power accommodation.Hence,the research on IES optimal operation considering source-grid-load-storage resources has become a key technical issue to be resolved.Under this background,the research content of this article is unfolded in 5 chapters,summarized as follows.(1)The modeling and scheme verification of the interaction between multi-energy parks and power grid are studied.First,for commercial and industrial parks which have large proportion and high consumption of urban users,on the basis of elaborate modeling of the internal flexible resources,the integrated demand response(IDR)interactive effects of "peak-load shaving" and "multi-energy optimization" mode realized via optimal management strategies and structural characteristics of the park are studied;Further,for the multiple parks controlled by aggregators,taking into account the dynamic energy pricing scheme,a multi-park supply-demand interactive equilibrium model is built based on the aggregative game method.Mixed integer linear programming,Karush-Kuhn-Tucker condition and distributed iterative techniques are applied to solve the above models.Case studies show that through the IDR interaction mechanism,the proposed approaches are able to simultaneously improve the overall/individual economy of the park and the cascade utilization of energy.(2)A configuration-operation joint stochastic risk decision-making method of community-level IES is explored.The vulnerability indicators of key components are first introduced to demonstrate the risks of occasional outage in normal operation and blackout in the emergent case considering the threatening factors such as source and load randomness and potential natural disasters.Consequently,taking into account the adjustment ability of uncertain IDR resources,a risk-averse two-stage optimization framework is put forward for the configuration-operation issue of community-level IES based on the worst-case risk measurement theory and the fuzzy stochastic chance-constrained programming approach.The scenario-based method,Monte Carlo simulation,clear equivalent conversion,and big-M methods are used to achieve the effective solutions.Case study shows that IDR interaction postpones equipment investment and enables supply mode transition,thereby saving total costs.Moreover,the suggested method significantly enhances system resiliency by reducing the extreme value-at-risk and improving the supply reliability under emergent scenarios like hurricane.(3)A two-stage robust optimal scheduling model for the source-grid-load coordination in regional electricity-gas-heat system is studied.To begin with,through second-order cone relaxation,McCormick envelope approximation,and big-M methods,the linearized model of distribution-level IES including distributed power and gas networks and thermal pipe network with heat loss is established.Additionally,two-stage robust optimization(TRO)theory is applied to build a day-ahead and real-time TRO scheduling framework,which aims to eliminate the generation and demand deviations due to prediction errors through the generalized source-network-load interaction.The column&constraint generation algorithm is utilized to decompose the TRO model into the alternately solved main problem and sub-problems to ensure the economic and safe operation.Numerical test shows that the proposed approach is effective in improving system robustness and risk-averse effect against real-time compensatory electricity price fluctuation.(4)A fast and dynamic robust optimization method for low-carbon integrated electricity-gas system operation is researched.The technological breakthroughs and popularization of gas-fired units and power-to-gas devices have accelerated the development of the transmission-level integrated electricity-gas systems(IEGS),while providing new ideas for wind power accommodation in a "wind-gas complementation" manner.Firstly,the carbon trading cost is deduced and wrote based on the carbon trading market mechanism and emission quota allocation method mainly prevailing in China.Meanwhile,taking into account the dynamic natural gas line pack,a fast and dynamic TRO scheduling model is established,with the consideration of uncertainties from wind power and load.During the solving process,the successive second-order-cone relaxation technique is nested in the main problem to gradually reduce the gas flow simulation error;while the system deviation and total carbon trading amount are limited in the sub-problem,in which the relax-and-enforce decoupling method is applied to accelerate the solution and to compute parallelly.Case study shows that the proposed method has good low-carbon economic benefits,robustness and convergence performance,and has advantage in calculation speed.(5)A distributed and cooperative TRO scheduling method for integrated electricity-gas systems is put forward.In view of the industrial barriers and information privacy between the electricity and gas system,a day-ahead and real-time distributed and cooperative TRO model considering dynamic line pack is proposed for wind power accommodation.The model starts from a set of initial feasible fixed 0-1 variables that simultaneously consider the day-ahead forecasting and real-time extreme scenarios.The alternating direction method of multipliers and column&constraint generation algorithm are combined to formulate a three-layer closed loop iterative strategy to decouple integer and continuous variables.After distributed solution in the inner layer model,economy test in the middle layer model and robustness examination in the outer layer model,the complete decentralized autonomy of electricity and gas systems and the robust economic operation of IEGS are achieved.The analysis of numerical examples verifies the rationality and effectiveness of the proposed method in terms of calculation effect,convergence performance,robustness,and improvement of wind power accommodation.This work aims at providing methodological support for IES related research from the multiple temporal-spatial-scales of park-distribution-transmission and planning-day ahead-real time.The research results reflect the benefits of multi-energy complementary and coordinated optimization of IES,which can be applied to the optimal configuration-operation decision-making of multi-energy parks(clusters)with collaborative responses of diverse IDR mode,as well as engineering practice guidance to boost wind power accommodation by means of carbon trading mechanism and distributed cooperative strategy. |
PDF Full Text Request