With the widespread application of Internet of thingstechnology in smart grid, the integration of numerous intelligent terminals exacerbates network congestion and data loss, leading to increased load tracking deviations. Simultaneously, the automatic generation control (AGC) employed for maintaining supply-demand balance faces high costs, slow response rates, and limited adaptability to renewable energy. Employing gas-to-power technology in conjunction with AGC can enhance overall system efficiency and stability. This paper proposes a power allocation and pricing strategy utilizing a two-level Stackelberg game framework to reduce utility costs while boosting profits for telecom operator and gas company. We develop an electricity cost model for utilities considering regulation errors from direct load control in smart grid. Using an iterative algorithm and backward induction, we derive the Nash equilibrium for the Stackelberg game. Simulation results show that this strategy reduces utility costs and increases profits for telecom operator and gas company.

Currently, the rapid development of Internet of Things (IoT) technology is promoting the development of smart grids. However, because of the numerous loads present and the surge of data in smart grids, network congestion, transmission delay, and insufficient channel resources pose pressing challenges for accurate, real-time transmission in load control communication systems. Mobile edge computing (MEC) and nonorthogonal multiple access (NOMA) technology, as new types of communication architectures, can significantly improve the communication quality in such network system. In this article, we first establish an NOMA-MEC system model with relay assistance based on cloud-edge collaboration in smart grids, aiming to minimize the energy consumption cost of the system while satisfying constraints on relay power and computation latency. In addition, we formulate a powerful four-slot transmission strategy to support cooperative computation and communication in the proposed NOMA-MEC system with relay assistance. Since the optimization problem is nonconvex, an efficient joint cooperative computation and communication algorithm with relay assistance is developed to solve it. Numerical results show that the proposed resource allocation strategy can significantly improve the communication transmission quality and reduce the energy consumption cost of the system.

Smart Grid needs real-time monitoring of power equipment status and optimization of power distribution. In order to meet the needs of mass communication and data transmission, smart grid needs sufficient spectrum resources to ensure fast and reliable data transmission. However, the limitation of spectrum resources and the interference caused by multisystem coexistence have become the bottleneck of the development of smart grid. This article pointed out the defect of the existing spectrum resources management mode. Based on the Taguchi Quality Assessment Theory, we developed a cost model for a utility company, which used a decoding and forward cooperative relay strategy to transmit downlink horizontal propagation to a data aggregation unit. This article analyzed the bilateral auction process between utility company and licensed user to maximize social welfare, and determined the optimal spectrum transaction to improve the utilization of spectrum resources.

The packet loss during transmission of load control commands can lead to regulation errors in the smart grid and further increase the cost of utility companies due to the purchase of additional automatic generation control services. This article considers a cooperative communication network consisting of multiple data aggregation units (DAUs) and multiple relays in smart grid, and each relay can forward data for all DAUs. We optimize the transmission power allocation of the relays to reduce the demand-side regulation errors and the cost of utility companies. However, additional cost is incurred due to the rental of relay in commercial networks. In order to minimize the total costs of utility companies, a two-layer game model is proposed and an iterative algorithm is developed. Simulation results show that the cost of utility companies can be reduced under the proposed scheme.

Owing to the openness and diversification of heterogeneous communication network, communication security becomes a pressing problem. In this paper, we consider a heterogeneous communication network in which spectrum resources are shared by electric power communication network and licensed network. First, we establish the utility companies’ cost model based on Taguchi loss function. Next, we utilize cooperative relay strategy to enhance the transmission quality and achieve high-speed information transmission in smart grids. Under the premise of ensuring high-quality transmission of electric power communication services, we propose a secure transmission strategy for information resource sharing and interference price trading that utilizes smart grid infrastructure and relay to interfere with eavesdroppers to improve the security rate of licensed user (LU), which achieves mutual benefits. Furthermore, the bernstein approximation method and the successive convex approximation are adopted to obtain the open-form expression of the constraint and transform the non-convex problem into the convex problem, respectively. A distributed robust power control algorithm is then proposed to obtain the optimal solutions. Finally, numerical results verify that the proposed secure scheme and algorithm can increase the secrecy rate at LU, reduce the total electricity cost, and improve both the profit of relay and the social welfare.

This article considers both the influence of relay power and load control period on the load tracking performance in smart grid communication. First, based on regulation errors caused by load control with imperfect channel state information (CSI), the load tracking cost model integrated of load control period and relay power is established in smart grid communication. Then, a coordination mechanism of cost-sharing contract (CSC) is presented. In the CSC, the utility companies select the preferred contractual terms offered by the telecom operator (TO) to reduce their costs and coordinate the whole network system simultaneously. Finally, the theoretical analysis and simulation demonstrate that the simultaneous consideration of the relay power and load control period can reduce the costs of the utility companies, increase the profit of the TO, and improve the social welfare. Besides, the proposed coordination mechanism of CSC can coordinate the whole network system.

In industrial wireless sensor networks (IWSNs), a lot of energy is wasted in the form of electromagnetic radiations. It can be effectively utilized with energy harvesting (EH), which absorbs part of the energy in the transmission signal but reduces the throughput and reliability of IWSNs. In this article, we study the throughput optimization of IWSNs with EH from the interference radio-frequency (RF) signal considering the reliability constraint of the industrial information transmission. Under the premise of limited energy supply of EH relays, the throughput maximization of IWSNs is formulated as a nonconvex optimization problem. In order to transform the nonconvex problem to a convex optimization problem, the successive convex approximation (SCA) approach is adopted. Furthermore, a power allocation algorithm is designed to maximize the total transmission rate of the network. Simulation results demonstrate that the proposed algorithm can maximize the throughput under the primise of SINR reliability.

In this article, we study an interference management and power allocation problem when electrical power communication (EPC) networks are densely deployed in the coverage of licensed networks. The purpose is to reduce the electricity cost and improve the licensed operator's profit subject to the quality-of-service (QoS) of licensed users (LUs). First, the electricity cost is modeled based on the Taguchi loss function, which links the cost to the communication errors in the EPC networks. The operator's profit is formulated by introducing a bonus-penalty mechanism, and a rational interference threshold (IT) of the licensed base station (LBS) is set to ensure the QoS of the LU. Second, we formulate the interference management and power allocation problem as a Stackelberg game, and a successive convex approximation algorithm is used to solve this problem to achieve the optimal IT and relay power. The simulation results indicate that the cost to the utility company is reduced and the profit of the LBS increases.

The electricity costs of the Utilities are increased with the deviations from the forecasted demand, which are caused by forecast errors and demand fluctuations. The forecast errors are deterministic and can be avoided by the Utilities with long-term operations in electricity markets, whereas the demand fluctuations are stochastic and unavoidable. Demand response can be used for mitigating the demand fluctuations by measuring the electricity usage of consumers and publishing control commands periodically. The performance of demand response is dependent on the quality of communications between the control center and the consumers. The two-way communications are established based on the data aggregator units (DAU) deployed by the Utilities. To improve the quality of communications, we utilize the base stations in telecom networks to forward the metering and control data for the DAUs. The telecom operators maximize their profits and decide the fractions of transmission power allocated for relaying, and then the Utilities select the payments to obtain the corresponding transmission power allocated for relaying. We characterize the electricity costs of the Utilities based on Taguchi loss function and establish a Stackelberg game between the telecom operators and the Utilities. We prove the existence and uniqueness of Nash equilibrium for the follower-level payment selection game and develop an iterative algorithm to search for the equilibrium. Then, the Stackelberg equilibrium can be obtained by a backward induction method. Numerical results show that the cost of the Utilities can be reduced and the profits of the telecom operators are increased.

In this paper, we optimize power and spectrum allocation simultaneously to improve the demand-side communication quality in smart grid, to further reduce the cost of utility companies. The electricity cost is first modeled based on regulation errors caused by direct load control in the smart grid. Then the subbands are allocated to different data aggregator units according to the band confidence levels and the utility company's maximum cost. An algorithm is designed to optimize transmission power of the relay and refine the spectrum allocation to reduce the cost of utility companies. Simulation results demonstrate that the packet loss rate and cost of utility companies can be significantly reduced.