Techno-Economic Analysis of Peer-to-Peer Energy Trading Considering Different Distributed Energy Resources Characteristics

Multiscale design for system-wide peer-to-peer energy trading

Guest Editorial: Enhancing hosting capability for renewable energy generation in active distribution networks

Due to the absence of utility power grid infrastructure in remote military bases, on-site diesel generators serve as the primary sources for power demands. Increasing efficiency and preventing frequent start- up/shutdown operations of on-site diesel generators are therefore becoming a critical issue for reducing fuel cost. Application of vehicle-to-grid technology in a military based microgrid has embodies potential for significant fuel economy benefits since vehicles can act as mobile power sources that provides higher flexibility for supplying power demands. In addition, energy storage system integration is considered as an alternative solution for increasing on-site diesel generators efficiency and lessening their start-up/shutdown operations. To further improve fuel economy in a remote military based microgrid, this paper proposes a three-stage planning procedure for identifying the optimal locations and capacities of energy storage systems, considering multiple operating scenarios via stochastic programming. In the first stage, the optimal sizing and siting strategy of storage units for each individual operating scenario is determined. In the second stage, the expected value of optimal locations and capacities of energy storage systems for all the scenarios, which are determined the first stage are obtained as the near-optimal result. In the third stage, with fixed location and capacities of energy storage systems, the optimal operation of microgrid is simulated to demonstrate their benefits. It is assumed that, in the tested microgrid systems, several tactical military vehicles with onboard generators and energy storage units are deployed as alternative power sources. Note that on-site diesel generators and on-board vehicle generators support plug-and-play functionality, meaning their start-up/shutdown operations can be decided in real time. Furthermore, network-constrained AC unit commitment model is used to optimize operation of microgrids. The economic merits of vehicle-to-grid implementation and energy storage system integration in a military based microgrid are validated in the numerical studies.

The rapidly increasing expansion of distributed energy resources (DER), such as renewable energy systems and energy storage systems into the electric power system and the integration of advanced information and communication technologies enable DER owners to participate in the electricity market for grid services. For more efficient and reliable power system operation, the concept of peer-to-peer (P2P) energy trading has recently been proposed. The adoption of blockchain technology in P2P energy trading has been considered to be the most promising solution enabling secure smart contracts between prosumers and users. However, privacy concerns arise because the sensitive data and transaction records of the participants, i.e., the prosumers and the distribution system operator (DSO), become available to the blockchain nodes. Many efforts have been made to resolve this issue. A recent breakthrough in a P2P energy trading system on an Ethereum blockchain is that all bid values are encrypted using functional encryption and peer matching for trading is performed securely on these encrypted bids. Their protocol is based on a method that encodes integers to vectors and an algorithm that securely compares the ciphertexts of these vectors. However, the comparison method is not very efficient in terms of the range of possible bid values because the amount of computation grows linearly according to the size of this range. This paper addresses this challenge by proposing a new bid encoding algorithm called dual binary encoding, which dramatically reduces the amount of computation as it is only proportional to the square of the logarithm of the size of the encoding range. Moreover, we propose a practical mechanism for rebidding the remaining amount caused when the amounts from the two matching peers are not equal. Finally, the feasibility of the proposed method is evaluated by using a virtual energy trade testbed and a private Ethereum blockchain platform.

Becoming a building suitable for participation in peer-to-peer energy trading

The article presents calculations and power flow of a real virtual power plant (VPP), containing a fragment of low and medium voltage distribution network. The VPP contains a hydropower plant (HPP), a photovoltaic system (PV) and energy storage system (ESS). The purpose of this article is to summarize the requirements for connection of generating units to the grid. Paper discusses the impact of the requirements on the maximum installed capacity of distributed energy resource (DER) systems and on the parameters of the energy storage unit. Firstly, a comprehensive review of VPP definitions, aims, as well as the characteristics of the investigated case study of the VPP project is presented. Then, requirements related to the regulation, protection and integration of DER and ESS with power systems are discussed. Finally, investigations related to influence of DER and ESS on power network condition are presented. One of the outcomes of the paper is the method of identifying the maximum power capacity of DER and ESS in accordance with technical network requirements. The applied method uses analytic calculations, as well as simulations using Matlab environment, combined with real measurement data. The obtained results allow the influence of the operating conditions of particular DER and ESS on power flow and voltage condition to be identified, the maximum power capacity of ESS intended for the planed VPP to be determined, as well as the influence of power control strategies implemented in a PV power plant on resources available for the planning and control of a VPP to be specified. Technical limitations of the DER and ESS are used as input conditions for the economic simulations presented in the accompanying paper, which is focused on investigations of economic efficiency.

This paper presents a new optimization algorithm for home energy management systems (HEMSs) in three-phase unbalanced low-voltage (LV) distribution networks. Compared with conventional HEMS optimization methods, which consider only the active power consumption scheduling for smart home appliances and distributed energy resources (DERs) (e.g., solar photovoltaic (PV) systems and energy storage systems (ESSs)), the novelty of the proposed approach is to consider: i) both active and reactive power consumption schedulings of home appliances and DERs, ii) realistic three-phase unbalanced LV distribution networks with voltage-dependent load models, and iii) voltage control using an on-load tap changer transformer and smart inverters of PV system and ESS at the households. The proposed HEMS optimization algorithm, which is formulated using mixed-integer linear programming, is tested in the modified CIGRE LV distribution network. Numerical examples demonstrate the performance of the proposed algorithm in terms of active/reactive power consumption, three-phase voltage magnitudes, and the total cost of electricity.

The power system is confronting progress due to the high integration of distributed energy resources (DERs). These DERs are expected to cause challenges for power system operations. Therefore, innovative management approaches were proposed for integrating DERs in future power systems and maximizing DER owners’ benefits, such as peer-to-peer (P2P) energy trading. Direct energy trading between users is made possible by P2P energy trading, which supports bulk power infrastructure operations while supporting local power and energy balance. P2P energy trading is a promising approach to expanding the installation of renewable energy sources and achieving the system flexibility required for the shift to low-carbon energy. The grid is anticipated to gain from P2P energy trading by having lower reserve requirements, peak demand, and network losses. Many studies and pilot projects have shown how P2P energy trading benefits prosumers as well as the grid. However, the widespread use of such trading models remains limited in today's electrical markets. This paper reviews recent advances in the P2P energy system and a perceptive discussion of the challenges that are keeping P2P from becoming a viable energy management solution in the present electrical market. First, the energy network is covered in this paper's description of these new P2P markets; next, the types of P2P energy trading, moving on to the market structure. Then, the technologies and technical approaches behind P2P energy trading are covered. After that, P2P energy trading advances in different systems are discussed. Finally, we identify challenges before making some concluding remarks.

The increasing penetration of distributed energy resources in distribution network has prompted the development and implementation of decentralized energy markets. Peer-to-Peer (P2P) energy trading is one of the most viable options for establishing a decentralized energy market. A distribution network capable of handling multiple energy transactions and a secure, user-friendly, and equally accessible trading platform are some of the critical requirements for the successful implementation of P2P energy trading. With the aforementioned considerations in mind, this paper proposes a bid limit-based network-aware P2P energy trading framework comprised of two algorithms: (i) an OPF-based maximum bid limit estimation algorithm and (ii) a market-clearing mechanism. It aims to (i) minimize back-and-forth communication required between the distribution system operator and the participants and (ii) increase the likelihood of participants qualifying for P2P energy trading. The framework is implemented on modified three-phase unbalanced IEEE-13 bus distribution network having prosumers, consumers, and independent power producers.

Data-driven evaluation for quantifying energy resilience in distribution systems with microgrids and P2P energy trading

Chance-constrained co-optimization of peer-to-peer energy trading and distribution network operations

As the continued use of fossil fuels exacerbates the effects of climate change, various government protocols are calling for increases in the utilization of renewable energy sources. Recent improvements in the efficiency of photovoltaic (PV) cells and energy storage system (ESS) capacity have prompted many electricity consumers to install such systems and become energy prosumers. Peer-to-peer (P2P) energy trading between consumers of energy deficit and prosumers with surplus energy reserves is desirable to provide incentives to install clean energy resources and achieve balance between supply and demand. This paper proposes the application of the Vickery-Clarke-Groves (VCG) auction-based trustful algorithm on such P2P energy trading. By doing so, improved auction environments for truthful energy bids and optimal energy resource allocation can be established.

Peer-to-peer (P2P) energy trading for profit-driven communities in distribution networks (DNs) has become increasingly critical in terms of economic view especially in the absence of supportive subsidies for renewable generation. However, the risk behavior of local energy communities (LECs), as well as their inherent flexibility options, can affect the profit achieved through local energy trading. This paper seeks to carefully examine to what extent the aforementioned factors contribute to the economic value of P2P energy trading for LECs. To do this, a mathematical model is developed as a multi-leader–multi-follower game which is formulated as equilibrium problems with equilibrium constraints (EPEC). In this game, operators of different LECs are leaders while the market operator who is in charge of clearing the local community market and the distribution system operator (DSO) who is responsible for addressing security constraints of the grid are deemed as followers. In addition, the conditional value at risk (CVaR) technique is utilized to model the risk-averse behavior of communities’ operators. Finally, the model is implemented into a typical DN modified by three different types of LECs. The findings of the simulation highlight that P2P energy trading can bring financial gains for a typical community under certain conditions. Flexibility originated from distributed energy resources (DERs) and sector coupling within a community provide more profit in local energy trading for the community, but risk-averse strategies have the opposite effect.

Due to the absence of utility power grid infrastructure in remote military bases, on-site diesel generators serve as the primary sources for power demands. Increasing efficiency and preventing frequent startup/shutdown operations of on-site diesel generators are therefore becoming a critical issue for reducing fuel cost. Application of vehicle-to-grid technology in a military-based microgrid embodies potential for significant fuel economy benefits since on-board vehicle generators and energy storage units can serve as mobile power sources that provide higher flexibility for supplying power demands. In addition, energy storage system integration is considered as an alternative solution for increasing on-site diesel generators efficiency and lessening their startup/shutdown operations. This article proposes a three-stage planning procedure for identifying the optimal locations and capacities of energy storage systems, considering multiple operating scenarios via stochastic programming. Note that on-site diesel generators and on-board vehicle generators support plug-and-play functionality, meaning their startup/shutdown operations can be decided in real time. Furthermore, network-constrained ac unit commitment model is used to optimize operation of microgrids. It is assumed that in the tested microgrid systems, several tactical military vehicles with on-board generators and energy storage units are deployed as alternative power sources. The economic merits of vehicle-to-grid implementation and energy storage system integration in a military-based microgrid are validated in the numerical studies.

Peer-to-peer (P2P) energy trading is an emerging energy supply paradigm where customers with distributed energy resources (DERs) are allowed to directly trade and share electricity with each other. P2P energy trading can facilitate local power and energy balance, thus being a potential way to manage the rapidly increasing number of DERs in net zero transition. It is of great importance to explore P2P energy trading via public power networks, to which most DERs are connected. Despite the extensive research on P2P energy trading, there has been little large-scale commercial deployment in practice across the world. In this paper, the practical challenges of conducting P2P energy trading via public power networks are identified and presented, based on the analysis of a practical Local Virtual Private Networks (LVPNs) case in North Wales, UK. The ongoing efforts and emerging solutions to tackling the challenges are then summarized and critically reviewed. Finally, the way forward for facilitating P2P energy trading via public power networks is proposed.