Research on congestion elimination method of circuit overload and transmission congestion in the internet of things

Multimed Tools Appl (2017) 76:18047–18066 DOI 10.1007/s11042-016-3686-6 Research on congestion elimination method of circuit overload and transmission congestion in the internet of things Zhu Longchao 1 & Xu Jianjun 1 & Yan Limei 1 Received: 16 October 2015 / Revised: 23 May 2016 / Accepted: 14 June 2016 / Published online: 27 June 2016 # The Author(s) 2016. This article is published with open access at Springerlink.com Abstract Power system is facing new challenges and opportunities in the environment of the internet of things. Under the circumstance of Internet of things, the transmission congestion management of interruptible load is the important measure to improve system reliability and operating economy. Considering the condition of target selected under different circumstances, this paper proposes a new multi-objective model of transmission congestion management with interruptible load based on brand circuit overload match with interrupt capacity. The multiobject model puts forward three goals, brand circuit overload match with interruptible load, the minimum number of interruptible load nodes and the minimum total interruption of interruptible load. Against other optimization methods can not prioritize to multiple targets and it can easily lead to convergence in the process of solving problems, the paper presents construct evaluation function based on the linear weighted sum to optimize multi-objective linear problem. This method can be sorted prior to multi-objective optimization model. And it has better convergence than other optimization methods in the solution process. Finally, it tests and verifies the correctness of method through the IEEE 30 bus power system. And it successfully applied to grid congestion management in oil. Keywords Transmission Congestion . The Internet of things . OPF . Branch Circuit Overload Capacity . Interrupt amount 1 Introduction The rise of the Internet of things, make the power system has to face many new problems. As at the beginning the rise of the Internet, and the problems faced in today^s power system also * Yan Limei 1 College of Electrical Information & Engineering, Northeast Petroleum University, Daqing 163318, China 18048 Multimed Tools Appl (2017) 76:18047–18066 need to face more and more serious transmission congestion problem. With the opening up of the grid and cross-regional electrical energy trade increasing, the deepening of power market reform, it is necessary to carry out a wider range of optimal allocation of resources. The gradual opening of demand side has become an important part of congestion management [3]. The increasing of electricity trade and power flow uncertainty has limited the transmission of electrical energy obviously. Consequently, transmission congestion had become an important subject to be solved. The transmission congestion of power system means that the requirements of power transmission can’t be satisfied because of the limitation of its transmission capacity, which usually includes transmission lines or transformer active power flow exceeding the permitted limit and the node voltage off-limit, etc. In order to eliminate the congestion, the management mode of congestion presents diversification. In the traditional congestion management mode, power grid companies adjust power plant power plan, and generator outputs to invoke a high power. This kind of congestion management usually concentrates on the side of power generation. Literature [17] proposes a congestion management model of joint mode; its essence is to consider all kinds of security constraints of the Optimal Power Flow (OPF) problems. Due to the fluctuation of node electricity price under this model is very big, and trade surpluses can be produced, which produce wrongful stimulate to the Independent System Operator (ISO). Therefore the PJM energy market in the United States and electricity market in the New England use financial transmission rights to solve the transmission congestion [2, 11]. User demand elasticity is also used to solve the transmission congestion. Under the market structure of both sides of supply and demand quoting at the same time, the load of each node is a decision variables affected by price, ISO can control electricity to ease congestion flexibly. Literature [5] structures congestion management model with the method of sensitivity analysis. Literature [1] uses generator rescheduling to solve the congestion, and provides a kind of congestion cost allocation method. Using IL (Interruptible Load) to solve the congestion management is a new solution of the congestion management in recent years. IL can make full use of the electricity elasticity, eliminate or relieve congestion and the power supply tension in peak load. According to the interruptible power supply contract signed by the power company and power users [10], it allows power companies to remove part of the user load as the contracted purview at a particular period of time (such as peak load). Meanwhile giving the user certain power shortage compensation can reduce the electricity load during peak hours to relieve the tense situation of power supply, thus achieve the purpose of congestion management. 2 The calculation of the maximum transmission capacity based on OPF The reason of transmission congestion appearing in the power system is the limit of the heat capacity of transmission line and the stability of the system. So, in the electricity market, in order to guarantee to make full use of the transmission capacity and not appear line congestion phenomenon, studying and calculating transmission capacities are indispensable links. At present, the method for calculating the maximum transmission capability mainly includes three [8]: the calculation method based on power transmission distribution factor, continuous power flow calculation method, the OPF calculation Multimed Tools Appl (2017) 76:18047–18066 18049 method. The OPF calculation method is calculating the maximum load capacity in the constraint condition of equality and inequality, including the power flow equation and transmission line heat constraints, etc. Compared with the other two methods, it can optimize the allocation of resources, calculate the maximum transmission capacity more accurately, and the calculation results are not too conservative. 2.1 Mathematical model Determining the maximum transmission capacity is increasing transmission and reception respectively at a given power generation node(s) and the load node(s), then solving power flow equations and checking whether there is an overload line or out of node voltage out-of-limit, repeating the process until appearing the overload line or out-of-limit node.Therefore, the mathematical model is as follows: maxλd s:t: gðx; λd Þ ¼ 0 hðxÞ ≤0 ð1Þ Where λd is a real parameter variable, reflecting the system transmission capacity of the node load and generator power in a given varying modes. g(x, λd) = g(x) + λd (...truncated)