Peer-to-peer (P2P) energy trading is one of the promising approaches for implementing decentralized electricity market paradigms. In the P2P trading, each actor negotiates directly with a set of trading partners. Since the physical network or grid is used for energy transfer, power losses are inevitable, and grid-related costs always occur during the P2P trading. A proper market clearing mechanism is required for the P2P energy trading between different producers and consumers. This paper proposes a decentralized market clearing mechanism for the P2P energy trading considering the privacy of the agents, power losses as well as the utilization fees for using the third party owned network. Grid-related costs in the P2P energy trading are considered by calculating the network utilization fees using an electrical distance approach. The simulation results are presented to verify the effectiveness of the proposed decentralized approach for market clearing in P2P energy trading.

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Peer-to-Peer Energy Trading in Smart Grid Considering Power Losses and Network Fees

This article studied the load frequency control (LFC) of a multi-source microgrid with the presence of renewable energy sources. To maintain a sustainable power supply, the frequency of the system must be kept constant. A Proportional–Integral–Derivative (PID) controller is presented as a secondary controller to control the frequency of the microgrid in island mode, and the integral of squared time multiplied by error squared (ISTES) is used as a performance index. The use of the Craziness-Based Particle Swarm Optimization (CRPSO), which is an improved version of Particle Swarm Optimization (PSO), improves the convergence speed in optimizing the nonlinear problem of load and frequency controller design. The test microgrid is composed of the load and distributed generation units such as diesel generators, photovoltaics and wind turbines. The proposed controller provided the desired response to adjusting the microgrid frequency, achieving the final response after a short time and making it more stable and less oscillatory compared with the conventional system.

Optimal Load Frequency Control of Island Microgrids via a PID Controller in the Presence of Wind Turbine and PV

Distributed Operation for Integrated Electricity and Heat System With Hybrid Stochastic/Robust Optimization

In order to improve the profits of electricity utility company (EUC) and gas utility company (GUC) and reduce the electricity and heat cost of users, an energy trading and pricing scheme based on three-stage game is proposed. Firstly, a three-stage optimization problem is established, and the conversion between electricity and gas is considered. Meanwhile, the conversion factor is introduced and coordinated with the energy price to adjust the balance of supply and demand. Then, the equilibrium solution of the game is obtained by using Lagrange function and backward induction method. In addition, an iterative algorithm is developed to obtain the optimal conversion factor between electricity and natural gas. Numerical results show that the profits of EUC and GUC are increased by 31.6% and 14.4%, the electricity and heat profits of energy hubs (EHs) are increased by 3% and 6.4%, and the electricity and heat cost of users are reduced by 9.25% and 14.05%. Note to Practitioners—In the multi-energy market, trading and pricing strategies have attracted more and more attention. Based on this, many scholars only studied pricing strategy to balance the supply and demand. However, in the context of multi-energy coupling, the previous pricing strategy is not effective. In this paper, we propose a new pricing strategy, with which the conversion factor can cooperate with the energy price to achieve the balance between supply and demand. The new pricing strategy can increase the profits of electricity utility companies and gas utility companies and reduce the costs of users. 

An Optimization Strategy of Price and Conversion Factor Considering the Coupling of Electricity and Gas Based on Three-Stage Game

Event-triggered fault detection for nonlinear semi-Markov jump systems based on double asynchronous filtering approach

This paper proposes an optimal day-ahead optimization schedule for gas-electric integrated energy system (IES) considering the bi-directional energy flow. The hourly topology of electric power system (EPS), natural gas system (NGS), energy hubs (EH) integrated power to gas (P2G) unit, are modeled to minimize the day-ahead operation cost of IES. Then, a second-order cone programming (SOCP) method is utilized to solve the optimization problem, which is actually a mixed integer nonconvex and nonlinear programming issue. Besides, cutting planes are added to ensure the exactness of the global optimal solution. Finally, simulation results demonstrate that the proposed optimization schedule can provide a safe, effective and economical day-ahead scheduling scheme for gas-electric IES.

Day-ahead optimization schedule for gas-electric integrated energy system based on second-order cone programming

In this article, by using distributed consensus algorithm, the power compensation problem of network losses in a microgrid is considered with battery energy storage systems (BESSs). At first, the battery storage unit (BSU) is assembled at each node to maintain the power supply demand balance of the microgrid, then the power constraint is considered, which demands each BSU must run between its upper and lower bounds, otherwise, the upper or lower bounds will be used to replace the real power of the BSU. In order to keep the power balance of microgrid when network losses exist, a novel distributed consensus algorithm is proposed to compensate the missing power through the discharging process of BSUs, and the state of charge (SOC) of BESS is also considered. Besides, the case of battery faults is also considered, where the minimum layout point constraint is presented to ensure the completely compensation of the whole transmission losses. Finally, the test results of IEEE 14-bus and IEEE 57-bus microgrid systems are provided to verify the effectiveness and validity of the proposed method, respectively.

Power Compensation of Network Losses in a Microgrid With BESS by Distributed Consensus Algorithm

Multi-stage equipment optimal configuration of park-level integrated energy system considering flexible loads

This paper focuses on the finite-time guaranteed cost (FTGC) control problem for interval type-2 (IT2) fuzzy semi-Markov switching systems (S-MSSs) with additive disturbances. Based on the IT2 fuzzy S-MSSs and the state feedback control method, a novel IT2 mode-dependent fuzzy GC controller is developed under the mismatched membership functions. Then, some new sufficient conditions are given to ensure that IT2 fuzzy S-MSSs are FT stochastically stable based on the designed IT2 mode-dependent fuzzy GC controller. Furthermore, the transition rates boundaries condition is relaxed, and a new incomplete transition rates boundaries model is constructed to reflect the transition rates information. With a view to both the incomplete transition rates boundaries and the actuator fault phenomenon, the improved stability criteria are provided to stabilize the IT2 fuzzy S-MSSs within a FT interval and determine the gains of the IT2 mode-dependent fuzzy GC controller, resulting in a much greater design flexibility. Distinct from the existing results, the presented FTGC control scheme is more suitable for many practical systems, because the IT2 fuzzy S-MSSs model which is more general compared with the traditional fuzzy system and S-MSSs is considered. Finally, three illustrative examples are offered to explain the effectiveness and feasibility of proposed FTGC control approach.

Jianxi Wang

Papers

Day-ahead optimization schedule for gas-electric integrated energy system based on second-order cone programming

Power Compensation of Network Losses in a Microgrid With BESS by Distributed Consensus Algorithm

Event-triggered fault detection for nonlinear semi-Markov jump systems based on double asynchronous filtering approach

Multi-stage equipment optimal configuration of park-level integrated energy system considering flexible loads

Guaranteed Cost Control for Interval Type-2 Fuzzy Semi-Markov Switching Systems within A Finite-Time Interval