Operation And Planning Of The Integrated Heat And Electricity Systems Considering The Operational Flexibility And Reliability Constraints

Energy systems are undergoing a radical transformation,which is often driven by technological advances and raising environmental awareness.One of the noticeable changes in this transformation is the ever-increasing coupling and interactions among different energy vectors.In this regard,the heat and electricity integrated energy system(IHES),which includes combined heat and power(CHP)units,has gained rapid technological development and deployment globally.The IHES would couple electric power system and district heating system(DHS).In recent years,IHES stands as one of the most discussed topics among industry,government,and academic sectors.The complementarity of different energy forms,therefore,can be well exploited in the IHES context to achieve the goal of enhancing energy efficiency and improving renewable energy integration.However,the inharmony between the high-penetration wind power and the wide use of CHP has become a challenge for operating the energy systems.On the one hand,the fluctuation of wind power makes electricity price vary significantly during the operating day.Thus,the profit of CHP units can be dramatically reduced in periods of low electricity prices resulting from large wind power production.On the other hand,the electricity generation of CHP units is constrained by their heat production,which must target customers' heat demand.This leads to high wind power curtailment when the electricity production of CHP units covers most of the electricity demand during the off-peak hours.Besides operation optimization issues,reliability assessment of the IHES is also worth investigating.The reliability of the heating system is intertwined with the reliability of the electric system.When,for example,there is a failure of the conventional electricity-generating unit,the CHP units would be expected to produce more electric power to counteract the electricity shortage.The heat production of the CHP units could be reduced under such circumstances.In this way,the heating system and electric system in the IHES should be viewed as a whole in terms of reliability assessment.In this paper,the theoretical research on the flexibility and reliability analysis and optimization of the IHES at the operation and planning level is conducted.The contributions can be summarized as:(1)The demand-side flexibility of the consumers is exploited and analyzed based on the integrated demand response(IDR)model.The consumers are divided into two groups.The integration of heat and electricity energy systems providing customers with multiple options for fulfilling their energy demand is described.Customer aggregators are introduced to supply downstream demand in the most economical way.Controlling customers' energy consumption behaviors enables aggregators to adjust their energy demand in response to supply conditions.The demand-side flexibility of the first type of consumer is modeled based on the block bids.All the parameters pertaining to the aggregators' energy consumption models are internalized in the bid curves.The demand-side flexibility of the second type of consumer is modeled based on the energy hub(EH)concept.(2)The electricity output of CHP units is constrained by their heat output corresponding to customers' heat demand,which makes it difficult for the CHP units to frequently adjust their electricity output.Therefore,additional balancing power is required to integrate the variable wind power in the CHP based IHES.The IDR of the consumers is incorporated into the optimal operation of the IHES.A real-time DR exchange(DRX)market is developed where the building aggregators are stimulated to adjust buildings' energy consumption behaviors and provide the required balancing power.Compared with the existing day-ahead DRX market,the real-time DRX market can balance the very short-term wind power fluctuation and reduce the price spike.Additionally,a novel optimum feasible region method is proposed to achieve the fast clearing of the DRX market to meet the higher requirement for clearing speed in the real-time market.(3)The traditional multi-state system(MSS)model is expanded to the two Twointerdependent-performance MSS(TIP-MSS)to analyze the reliability of the IHES.The reliability models of the coupling devices in the IHES,i.e.CHP units and Electric heat pumps(EHP),are firstly developed through reliability blocks diagram analysis.Energy loads are represented by fuzzy multi-state models to capture the uncertainties related to the forecast errors.Combination of the possible states of the devices and load levels generates a scenario set that needs to be considered in the reliability assessment.The scenario-based combined heat and power dispatch(CHPD)model is developed to calculate the nodal reliability indices.Several techniques are utilized to improve the computation efficiency of the reliability assessment.On the one hand,the universal generating function(UGF)technique is used to combine the device states and consequently reduce the number of scenarios.On the other hand,the operating constraints pertaining to the DHN are linearized.In this way,the CHPD is converted into a linear programming(LP)model,which can be effectively solved.(4)An integral generation expansion planning(GEP)framework is proposed,which enables competition to occur among conventional power plants(CPPs)of the GENCO and CHP units of the DHSCO.The framework is based on decentralized decision-making and involves an iterative process for simulating the interactions among the ISO,GENCO,and DHSCO.The combined heat and power dispatch model is reconstructed to determine the LMP to offer incentives for market participants' investments.The fuzzy load duration curve(FLDC)method is proposed to model the electricity load that would influence the LMP.In each state of the FLDC,the load level is represented by a fuzzy number to characterize the uncertainties.Investment decision-making models of the GENCO and DHSCO are formulated as a mixed integer linear programming with fuzzy objectives(MILPFO).A technique is proposed to solve the MILPOF models with the consideration of the risk appetite of the market participants.