Energy Sharing Research Articles

Optimal Energy Sharing in Hybrid Microgrid System Using Battery Energy Storage

A smart micro grid technology application facilitates the integration of renewable energy and increase its penetration. A smart grid is an electrical network which is built on advanced technology that uses dual-way digital communication to transmit electricity to buyers. The smart grid was created with the aim of using smart meters to overcome the problems faced by traditional grids. Microgrids allow for the integration of multiple renewable energy sources at different levels, improving the power system’s reliability, sustainability and efficiency. Remote places, spacecraft and maritime applications all use DC microgrids. Solar photovoltaic (PV) systems, wind energy, fuel cells, battery management systems, supercapacitors, and loads make up a DC microgrid. In this paper, some of the interesting approaches for optimal energy sharing in the hybrid microgrid are discussed.

E-Bus Based Standby Energy Sharing for EVs in the Event of Large-Scale Grid Outage

E-Bus Based Standby Energy Sharing for EVs in the Event of Large-Scale Grid Outage

에너지 공유 및 거래를 위한 커뮤니티단위계획 수립 방안 연구

에너지 공유 및 거래를 위한 커뮤니티단위계획 수립 방안 연구

Energy Sharing of Multiple Virtual Power Plants Based on a Peer Aggregation Model

With the increasing number of virtual power plants (VPP) participating in market transactions, the joint operation and energy sharing mode of multiple virtual power plants (multi-VPP) has attracted attention. A peer aggregation model for the multi-VPP energy sharing is proposed based on sharing price. At the VPP autonomous optimization level, each VPP operator formulates an autonomous optimization strategy based on the price incentives and the internal resource parameters and adopts a robust optimization method to improve the strategy’s robustness. At the overall level, a sharing level index is introduced to formulate the sharing price mechanism and an overall sharing strategy is proposed. The case simulation results show that compared with the independent operation of each VPP, participating in energy sharing can effectively promote the overall consumption of renewable energy and the overall operating cost is reduced by 18%. The introduction of the sharing level index into the sharing price can effectively improve the rationality of the formulated sharing price, and the net electricity load fluctuation has a greater impact on the system cost than the thermal load fluctuation.

Less Carbon Footprint in Edge Computing by Joint Task Offloading and Energy Sharing

Less Carbon Footprint in Edge Computing by Joint Task Offloading and Energy Sharing

Region-to-Region Energy Sharing for Prosumer Clusters in Distribution Network: A Multi-Leaders and Multi-Followers Stackelberg Game

Region-to-Region Energy Sharing for Prosumer Clusters in Distribution Network: A Multi-Leaders and Multi-Followers Stackelberg Game

Distributed Energy Sharing Decisions in Industrial Clusters Considering Disappointment Aversion under Carbon Tax Policy: a Differential Game Analysis

Distributed Energy Sharing Decisions in Industrial Clusters Considering Disappointment Aversion under Carbon Tax Policy: a Differential Game Analysis

Energy Sharing Mechanism of a Higher Order Protein System

Energy Sharing Mechanism of a Higher Order Protein System

Update Scheduling for ADMM-Based Energy Sharing in Virtual Power Plants Considering Massive Prosumer Access

With the proliferation of distributed energy resources (DERs), electricity consumers in virtual power plants (VPPs) are transitioning into prosumers and are encouraged to share surplus energy with peers. Nevertheless, large-scale energy sharing among thousands of prosumers may encounter communication-related challenges. Communication network congestion may result in a significant increase in the negotiation waiting time to reach a sharing agreement, and potentially risks exceeding the deadline of negotiation before the market gate closes, rendering energy sharing ineffective. This paper proposes an online partial-update algorithm for the alternating direction method of multipliers (ADMM)-based energy sharing. By restricting the update connection between the VPP and the prosumers, the algorithm selects a subset of the prosumers participating in ADMM updates each round, hence eliminating the excessively long waiting time caused by communication congestion. Considering the delay induced by massive prosumer communication access requests, a method for determining the optimal number of prosumers participating in updates is provided. To fully utilize the limited update opportunities, a fair and efficient prosumer update scheduling policy is designed. The VPP schedules the participation of prosumers in updates such that the convergence-critical prosumers receive higher priority, yet every prosumer is granted sufficient update opportunities. Additionally, the extra computation and communication overheads brought by the prosumer scheduling are minimized, allowing the whole algorithm to be executed in real time. Numerical studies are conducted to validate the effectiveness of the algorithm and its performance in reducing the overall convergence time.

Hydrogen influence on kapok methyl ester blended with DEE as an alternate fuel in CI engine

Kapok oil methyl ester (KOME) is used as a pilot fuel, while hydrogen and diethyl ether (DEE) are used as secondary fuels to improve the performance, emissions and combustion of a direct injection compression ignition engine. With a compression ignition engine, a slight modification to the system enables hydrogen gas through the intake manifold. A flow metre limits the quantity of energy the hydrogen may produce off, and two flame arresters prevent backfires in the fuel line. At full load and maximum hydrogen energy sharing, KOME + 20%DEE obtained a brake thermal efficiency of 30.31%, which is 14% higher than without hydrogen enrichment and about 8% higher than diesel's value (0% hydrogen energy share). The main problem with previous research is that hydrogen with a high heating value makes greater amounts of nitric oxide. Diethyl ether, on the other hand, has fixed this major problem, and the absence of carbon in hydrogen fuel lowers CO, HC and smoke emissions.

Energy and Reserve Sharing Considering Uncertainty and Communication Resources

In this paper, we study the joint energy and reserve sharing problem considering renewable generation uncertainty and limited communication resources. We propose a data-driven distributionally robust energy and reserve sharing model among different agents in electricity markets. We put forward data-driven distributionally robust chance constraints (DRCC) to determine the reserve capacity, which cannot be directly solved. The inner approximation is employed to convert the DRCC into tractable linear constraints. Taking into account the agents in the Internet of Things exchange information by a resource-limited communication network, we develop a communication-censored consensus alternating direction method of multipliers (ADMM) to utilize the limited communication resources and solve the sharing problem in a fully decentralized manner. We analyze the convergence of the proposed algorithm, and propose an adaptive penalty parameter method to speed up the convergence. Extensive simulations are conducted to verify the effectiveness of the proposed model and theoretical results.

Energy Sharing Transaction Network Establishment of Industrial Complex and Integrated Design Method

Energy Sharing Transaction Network Establishment of Industrial Complex and Integrated Design Method

Low-carbon optimal operation strategy of multi-park integrated energy system considering multi-energy sharing trading mechanism and asymmetric Nash bargaining

In the current energy transactions of multi-park integrated energy system (M-PIES), aiming at the problems that the interaction between the supply side and the demand side is not fully considered, the sharing potential of multiple energy sources is not fully tapped, the benefit distribution mechanism considering the contribution of the load aggregator (LA) is lacking, and with the all-round development of the carbon trading market (CTM), the existing ladder-type carbon trading (LCT) mechanism has insufficient capacity to limit CO2 discharges of M-PIES, etc., this paper puts forward a low-carbon optimal operation strategy of M-PIES considering the multi-energy sharing trading mechanism (MSTM) and asymmetric Nash bargaining (ANB). Firstly, the interaction between supply and demand (IS&D) is fully considered, and the benefit maximization model of PIES operator-LA multi-agent alliance considering MSTM and improved ladder-type carbon trading mechanism (ILCTM) is established by using Nash negotiation theory (NNT). Then, according to the different bargaining capabilities of each agent, a profit distribution model based on ANB is proposed, and it is solved by alternating direction method of multipliers (ADMM). Finally, through the comparison of different cases, it is proved that the proposed method can further reduce CO2 discharges of M-PIES, improve the benefits of each agent and alliance, and realize the fair and reasonable distribution of energy sharing (ES) benefits.

Novel Task Scheduling Approaches in Energy Sharing Solar-Powered IoT Networks

This paper considers task scheduling in solarpowered Internet of things (IoT) networks where devices are capable of sharing energy wirelessly. Our aim is to minimize the completion time of all tasks. We outline a novel mixed integer linear program (MILP) to schedule tasks and determine whether devices share their harvested energy via radio frequency (RF) in each time slot. The MILP considers the coupling between the energy level at devices across time slots. It also considers the dependency of tasks, whereby each task must be executed on a given set of devices in a specific order. Further, we propose a heuristic algorithm called minimum time first with energy sharing (MinTime-ES) for large scale networks. Our results show that with energy sharing, MILP and MinTime-ES achieve 28.86 and 7.83% reduction in task completion time as compared to competing algorithms that do not consider energy sharing between devices.

Online Companion: A Preference Informed Energy Sharing Framework for a Centralized Energy Community

Online Companion: A Preference Informed Energy Sharing Framework for a Centralized Energy Community

A Hierarchical Strategy for Restorative Self-Healing of Hydrogen-Penetrated Distribution Systems Considering Energy Sharing via Mobile Resources

The self-healing ability of distribution systems (DSs) against extreme events can be significantly boosted by strategically dispatching mobile emergency resources (MERs). In recent years, the penetration of hydrogen energy in energy systems has increased dramatically. Hydrogen energy and its related infrastructure, such as hydrogen refueling stations (HRSs) and mobile fuel cell vehicles (MFCVs), exhibit great potential for enhancing the self-healing ability of DSs. In this work, a two-layer hierarchical strategy for improving the restorative self-healing ability of hydrogen-penetrated DS (HPDS) with multiple microgrids (MGs) and HRSs is proposed considering their interactions and MERs such as mobile energy storages and MFCVs. In the lower layer, an optimal energy management strategy is presented for MGs considering the coordination between hydrogen and electricity via the electrolyzer and fuel cell in the HRSs. In the upper layer, an energy sharing (ES) strategy is proposed for the distribution system operator (DSO) to dispatch MERs in order to minimize the power imbalance among MGs and reduce the unserved load. Since MERs can be dispatched for many times to swap energy and hydrogen between MGs or HRSs, the concept of the equivalent time network (ETN) is introduced, and based on the ETN, a mixed integer linear programming (MILP) model is innovatively proposed to represent the traveling pattern of MERs and to optimize their ES path among MGs. Finally, the two-layer hierarchical strategy is formulated as MILP models and solved using the commercial solver. Case studies on a modified IEEE 33 bus distribution system (DS) and a regional DS in China verify the effectiveness of the proposed strategies.

An Energy Sharing Mechanism Considering Network Constraints and Market Power Limitation

As the number of prosumers with distributed energy resources (DERs) grows, the conventional centralized operation scheme may suffer from conflicting interests, privacy concerns, and incentive inadequacy. In this paper, we propose an energy sharing mechanism to address the above challenges. It takes into account network constraints and fairness among prosumers. In the proposed energy sharing market, all prosumers play a generalized Nash game. The market equilibrium is proved to have nice features in a large market or when it is a variational equilibrium. To deal with the possible market failure, inefficiency, or instability in general cases, we introduce a price regulation policy to avoid market power exploitation. The improved energy sharing mechanism with price regulation can guarantee existence and uniqueness of a socially near-optimal market equilibrium. Some advantageous properties are proved, such as prosumer's individual rationality, a sharing price structure similar to the locational marginal price, and the tendency towards social optimum with an increasing number of prosumers. For implementation, a practical bidding algorithm is developed with convergence condition. Experimental results validate the theoretical outcomes and show the practicability of our model and method.

A Distributed Online Algorithm for Promoting Energy Sharing Between EV Charging Stations

In recent years, electric vehicle (EV) charging stations have experienced an increasing supply-demand mismatch due to their fluctuating renewable generation and unpredictable charging demands. To reduce their operating costs, this paper proposes a distributed online algorithm to promote energy sharing between charging stations. We begin with the offline and centralized version of the EV charging stations operation problem, whose objective is to minimize the long-term time-average total cost. Then, we develop an online implementation approach based on the Lyapunov optimization framework. Although the proposed online algorithm runs in a prediction-free manner, we prove that by properly choosing the parameters, the time-coupling constraints remain satisfied. We also provide a theoretical bound for the optimality gap between the offline and online optimums. Furthermore, an improved alternating direction method of multipliers (ADMM) algorithm with an iteration truncation is proposed to enable distributed computation. The proposed algorithm can protect privacy while being suitable for online implementation. Case studies validate the effectiveness of the theoretical results. Performance comparisons are carried out to demonstrate the advantages of the proposed method.

A Three-Stage Model to Manage Energy Communities, Share Benefits and Provide Local Grid Services

This paper proposes a three-stage model for managing energy communities for local energy sharing and providing grid flexibility services to tackle local distribution grid constraints. The first stage addresses the minimization of each prosumer’s individual energy bill by optimizing the schedules of their flexible resources. The second stage optimizes the energy bill of the whole energy community by sharing the prosumers’ energy surplus internally and re-dispatching their batteries, while guaranteeing that each prosumer’s new energy bill is always be equal to or less than the bill that results for this prosumer from stage one. This collective optimization is designed to ensure an additional collective benefit, without loss for any community member. The third stage, which can be performed by the distribution system operator (DSO), aims to solve the local grid constraints by re-dispatching the flexible resources and, if still necessary, by curtailing local generation or consumption. Stage three minimizes the impact on the schedule obtained at previous stages by minimizing the loss of profit or utility for all prosumers, which are furthermore financially compensated accordingly. This paper describes how the settlement should be performed, including the allocation coefficients to be sent to the DSO to determine the self-consumed and supplied energies of each peer. Finally, some case studies allow an assessment of the performance of the proposed methodology. Results show, among other things, the potential benefits of allowing the allocation coefficients to take negative values to increase the retail market competition; the importance of stage one or, alternatively, the need for a fair internal price to avoid unfair collective benefit sharing among the community members; or how stage three can effectively contribute to grid constraint solving, profiting first from the existing flexible resources.

Differential Game Model of Distributed Energy Sharing in Industrial Clusters Based on the Cap-and-Trade Mechanism

The sharing economy is a new economic model that can promote the optimal allocation of resources. Distributed energy sharing in the industrial cluster is of great significance for cluster enterprises to improve energy utilization efficiency and reduce carbon emissions. In this paper, we establish a differential game model for energy sharing in the industrial cluster under the cap-and-trade mechanism analyze the equilibrium strategies of core and supporting enterprises in the industrial cluster under three different decision scenarios. We then conduct a comparative analysis of the results, and the effect of the carbon cap and carbon trading prices on energy sharing in the industrial cluster is discussed in detail. Finally, the results of the theoretical analysis were verified through numerical simulations. The conclusions are as follows: (1) The energy sharing synergy, profit for both parties, and total system profit are the highest under the centralized decision, the Stackelberg game is better than the decentralized decision, and the cost-sharing contract can achieve the overall coordination of interests; (2) A higher carbon trading price can increase the low-carbon level of energy consumption, but interestingly, when the carbon cap is below a certain limit, the increase in carbon trading price within a certain time and interval will lead to a decrease in profits for both parties and total system profit; (3) In the Stackelberg game scenario where cost-sharing contracts are introduced, the cost-sharing ratio of core enterprises will increase as the proportion of benefits to core enterprises increases and government subsidies to supporting enterprises decrease.