This study examines the profitability and reliability of a virtual power plant (VPP) with the existence of a diesel genset (DG) in the day-ahead (DA) and intra-day (ID) power markets. The study’s ...unique contribution lies in integrating the VPP system with non-spinning reserve DG while limiting the DG operation via minimum running time and maximum number of switching times (on/off) per day. This contribution decreases the renewables’ uncertainty and increases the VPP’s reliability. Moreover, the study proposes an optimization model as a decision-making support tool for power market participants to choose the most profitable short-term market. The proposed model suggests choosing the DA market in 62% of time (from 579 days) based on estimated VPP power supply, and market prices. Even though there is uncertainty about VPP power supply and market prices, the division between the plan and actual profits is 1.8 × 106 Japanese yen JPY per day on average. The share of surplus power sold from the mentioned gap is 5.5%, which implies the opportunity cost of inaccurate weather forecasting. The results also show that the reliability of the VPP system in the presence of a DG increases from 64.9% to 66.2% for 14 h and mitigates the loss of power load by 1.3%.
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In the context of the “Carbon peak, Carbon neutral” target, the introduction of carbon trading and the connection of new energy generation such as wind power and photovoltaics to the power grid have ...become important means to achieve a reduction to low carbon emissions. To this end, a virtual optimization model is established to take into account both low-carbon and economic aspects. Firstly, based on the basic concept of a virtual power plant, a virtual power plant model containing wind power, photovoltaic power, a gas turbine, and energy storage is established. Then, considering the uncertainty factors of wind power and PV power generation, Latin hypercube sampling (LHS) is used to simulate wind power and PV output scenarios, combined with the improved CLARA clustering algorithm to reduce the scenarios to form a classical scenario set to reduce the influence of wind power and PV output volatility. Finally, a carbon-trading mechanism and time-sharing tariff are introduced, and the model is solved with the objective function of maximizing the net benefit and minimizing the carbon emission of the Virtual Power Plant. Using arithmetic examples for verification, the results show that the introduction of carbon-trading mechanism can improve the net benefits of the Virtual Power Plant while promoting energy saving and emission reduction.
In order to solve the problems of interconnection and communication security of monitoring system the distributed energy resources (DER) with different ownership, the virtual power plant (VPP) can be ...effectively employed. This paper proposes the information model of DER monitoring terminal based on the IEC 61850–7–420, and studies the extensible message and presence protocol (XMPP) mapping to realize the real-time data communication service. The built-in security mechanisms TLS (Transport Layer Security) and SASL (simple authentication and security layer) of XMPP can ensure the security of information transmission. This paper also presents a platform to test the transmission performance of XMPP mapping, and the results show that XMPP properly meets the security communication requirements of DER monitoring system.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
The purpose of this article is to provide a model for the effective use of on/off loads and thermal loads controlled by thermostats (TCL) in providing primary frequency control (PFC). To this end, ...the mentioned loads have been aggregated in the form of a virtual power plant (VPP), allowing their cumulative capability to be offered as a bid for ancillary services. In order to determine VPP bids, a droop curve similar to the droop curve of traditional power plants has been extracted for VPP, which includes the technical limitations of VPP member loads. In formulating the VPP bidding strategy, the goal is to maximize profits and to use the capabilities of TCLs more effectively; their temperature set point is considered variable, as well as the constraint of compressor lockout, energy consumption level, device’s fire frequency and the duration of their continued response (deployment end) are incorporated in the model. The results of the model are the maximum power that can be provided to the primary frequency ancillary service market and its profit. The presented model has been simulated on a test system including 70 domestic loads in MATLAB software and checked under five different scenarios. According to the obtained results, considering the variable temperature set point for TCL leads to increasing the power of VPP by 7.33%. Moreover, considering compressor lockout constraint and increasing deployment end lead to a 22.4% and 3.54% reduction to the power of VPP respectively.
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•VPP with change of RLs status have the ability to participate in PFC.•In order to use the capabilities of TCLs more effectively, with the variable temperature set point, which leads to increased profit by 2%.•By limiting the compressor lockout, the available output power and VPP profitability will decrease by 5%.•With the increase of the development end the power that can be presented to the market and the VPP profit decrease by4%.
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The zero-carbon concept for combating climate change boosts the development of distributed renewable energies in distribution grids. However, the lack of appropriate incentives limits their gains. ...The virtual power plant aggregates distributed energy resources on the demand side for cost-effective renewable energy consumption via flexible transactions. When compared to trading directly with retailers, virtual power plants can improve their efficiency through peer-to-peer energy trading, thus promoting the development of distributed renewable energies in the distribution network. This paper proposes a peer-to-peer energy transaction mechanism between multiple virtual power plants. First, a multi-VPP model based on peer-to-peer energy trading is constructed. It includes modeling of electric vehicles, gas turbines, renewable energy, and flexible loads. Second, because prosumers are owned by different stakeholders, a distributed optimization model is developed. The model is then solved based on a fully decentralized consensus alternating direction multiplier method. In addition to the energy transaction, the benefit distribution of peer-to-peer energy trading is then investigated using the Shapley value method. The simulation results confirm the proposed peer-to-peer energy transactions can not only effectively improve the overall benefits of virtual power plant alliance, but also improves the income of renewable energies. Finally, the conclusion section summarizes the contributions and analyzes the limitations.
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With the rapid development of massive multivariate distributed energy resources on the demand side, the distribution network is transforming from traditional passive to active management. By ...constructing the virtual power plant, distribution network operators will handle the management and transactions of those distributed resources as their participation in the electricity market becomes normal. Moreover, distributed resources will affect the operating economy and security of the distribution network, such as network losses and peak loads. Thus, distribution network operators must consider both the security of distribution networks as well as the economics of distributed resources. To address this issue, a virtual power plant with the distribution network operator as the stakeholder has been built. A multi-objective optimization model based on the improved augmented ε-constraint method (AUGMECON2) method is then proposed. The key objective is to maximize operating benefits while also accounting for network losses and peak-to-valley load disparity of the slack bus. To address the uncertainty of renewable energy, a dynamic reserve capacity calculation approach is developed, taking into account the economics as well as transaction reliability. The Pareto frontier of the multi-objective optimal problem is obtained by AUGMECON2, and a compromised solution considering fairness is proposed. Finally, the proposed method is verified with case studies based on the modified IEEE33-node distribution network system.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
For synchronized functioning of distributed renewable energy resources, virtual power plant (VPP) is manifested as an upshot for maximizing net profit of the partakers taking into account ...uncertainties. Here, optimal day-ahead scheduling for VPP has been performed for meeting electrical, thermal and cooling demands. VPP comprises small hydro power plants, wind turbine generators, solar micro-cogeneration units, biomass-fuel-fired micro-cogeneration units, battery energy storage system, plug-in electric vehicles, electric chiller, absorption chiller, ice storage conditioner and thermal energy storage system. SMC units and BMC units are incorporated alternately. Demand response program is applied for electric, thermal and cooling demands to flatten demand curves and to improve system flexibility and decrease cost. The scheduling problem is solved by utilizing bottlenose dolphin optimizer (BDO), self-organizing hierarchical particle swarm optimizer with time-varying acceleration coefficients (HPSO-TVAC) and grey wolf (GWO) optimization so as to maximize net profit of VPP operator. The maximum profit obtained from BDO is about 5.25 % and 9.82 % more than the maximum profit obtained from HPSO-TVAC and GWO respectively.
•Optimal day-ahead scheduling for renewable energy-based VPP has been studied.•Electrical, thermal and cooling demands are considered.•Demand response program is applied for electric, thermal and cooling demands.•Bottlenose dolphin optimizer has been used to solve this problem.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Efficient utilization of existing energy resources within smart industrial grids constitutes an indispensable part of any energy management system (EMS). In this regard, virtual power plants (VPPs) ...play a crucial role in smart exploitation of available generated power. The present paper offers a new and exciting perspective at the EMS of Industrial VPPs (IVPPs). The grid management simultaneously makes use of demand response (DR) loads and electric vehicles (EVs) deployed at parking spaces. The EMS follows the objective of maximizing overall profit of its assemblage. At the same time, the EMS endeavors to augment the grid reliability at peak conditions and reduce load shedding of industrial centers. Naturally, there are uncertainties in such parameters as electricity market prices, EVs, and renewable energy production sources. Thus, a random-based energy management problem approach is adopted. To validate, the proposed method is experimented on the second zone of the modified IEEE-RTS standard network. The simulations reveal that the EVs’ presence in dedicated parking spaces can bring about a dramatic increase in the storage capacity of the IVPPs. This causes a reduction in the use of network’s overall power capacity. In fact, a prominent feature of the EMS is constant use of DR programs and selecting best one for each IVPP at different time hours. On the whole, the adopted procedure gives rise to a general reduction in network’s operational costs, considerable de-peaking as well as enhanced performance of EVs at parking spaces.
Most of current prosumer-energy-management approaches are focused on economic optimization by self-consumption maximization. Nevertheless, a lack of energy management strategies (EMS) that tackle ...different interaction possibilities among community-clustered solar plus battery prosumers has been detected. Furthermore, such active prosumer EMS may include participation in ancillary service markets such as automatic frequency restoration reserves (aFRR) through an optimized battery-energy storage-system (BESS) operation, as well as incorporating community-level energy management. In this study, an optimal EMS that includes aggregated aFRR-market participation of five solar plus battery prosumers participating in an energy community (EC), with the aim of reducing total costs of ownership for each individual prosumer is proposed. For its validation, different scenarios have been analyzed. The results show that the proposed EMS allows a levelized cost of energy (LCOE) reduction for all community members with respect to the base-case scenario. Moreover, the most profitable scenario for all prosumers is still the only PV.
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