Optimal Configuration of Electricity-Heat-Gas CloudEnergy Storage Considering Demand Response

doi:10.12204/j.issn.1000-7229.2022.03.010

Abstract

Abstract:

In order to fully mobilize user-side resources in an increasingly open energy trading market, this paper proposes an optimal allocation strategy for electricity-heat-gas cloud energy storage (CES) considering demand response (DR). The proposed optimized configuration establishes an energy hub (EH) structure with electricity-heat-gas cloud energy storage, and a two-subject two-layer optimized model from the view of users and providers participating in the CES business model is established. The lower layer describes the uncertainty of new energy output according to the probability prediction method based on long-term and short-term memory and Bayesian neural network; a user-side CES charging and discharging model considering demand response, which is optimized aiming to minimize the user’s total cost, is established; and the decision information will be informed to the CES provider. The upper layer, aimed to minimize the investment and construction cost of CES providers, concentrates on optimizing the allocation of energy storage power and capacity of decision-making entities. The big M method is adopted to relax and linearize the nonlinear part of the objective and constraints, and then it is transformed into a mixed-integer linear optimization problem. Finally, four typical application scenarios are established. As to the verification of the superiority of the strategy, the CPLEX optimization solver is called through the YALMIP toolbox in Matlab to solve the models in different scenarios, and the overall costs and benefits are jointly compared.

Key words: cloud energy storage(CES), demand response(DR), integrated energy system, energy hub(EH), relaxation linearization, optimize configuration

CLC Number:

TM715

DING Xi, JIANG Wei, GUO Chuangxin, XI Zenghui, GAO Jie. Optimal Configuration of Electricity-Heat-Gas CloudEnergy Storage Considering Demand Response[J]. ELECTRIC POWER CONSTRUCTION, 2022, 43(3): 83-99.

Figures/Tables 20

Fig.1 Basic architecture of cloud energy storage

Fig.2 Structure of an electric-heat-gas coupling CES energy hub

Fig.3 Basic model of two-subject charging and discharging

Fig.4 Flow chart of optimal configuration ofelectric-thermal-gas CES considering demand response

Fig.A1 Cost comparison of CES providers indifferent scenarios

Fig.A2 Thermal load curve

Fig.A3 Gas load curve

Fig.A4 Typical photovoltaic output curve

Fig.A5 Curve of total output of wind power generator and total load of heat and gas

Table 1 Time-of-use electricity price and time division

Table 2 Heat-gas power conversion

Table A1 Example parameters

Fig.5 Forecast results of probability distribution ofphotovoltaic generation power

Fig.6 Load comparison before and after demand response

Fig.7 Total charge and discharge power of CES users

Fig.8 Charge and discharge power of CES provider

Table A2 Optimization results of each parameter

Fig.9 Energy storage power configuration indifferent scenarios

Fig.10 Energy storage capacity allocation indifferent scenarios

Fig.11 Cost comparison of CES providers indifferent scenarios

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