•We propose a cost-effective energy management algorithm for PV-storage in the context of a shared community.•Uncertainties related with electricity demand and solar power generation are used in the ...decision-making process.•The impact of energy management is included for net present value (NPV) calculation of each system design.•An approach to identify the optimal storage sizing using NPV is presented and applied to each house of the community.
The aim of this paper is to propose a new energy management framework and storage sizing for a community composed of multiple houses and distributed solar generation. Uncertainties associated with solar generation and electricity demand are included to make the mathematical models more realistic, and as a result, provide more accurate control strategies to manage storage devices utilization. To evaluate that, a multi-stage stochastic program model designed to minimize community electricity purchase cost per day is used to support decision-making by creating control policies for energy management. Two different strategies are created to represent the interest of a single household (the individual energy management - IEM) and households that share their assets with the community (shared energy management - SEM). Our strategies consider time-of-use rates (ToU), load and resource variation during different seasons, with their distinct days of the year, to calculate net present value (NPV) associated with the energy savings. IEM and SEM are then used in a framework designed to establish the requirement of optimal energy storage size for each house of the community based on NPV values. The results of this study for an analysis considering a community with five houses show that the proposed SEM strategy reduces the overall electricity purchase costs for a summer day up to 11% and 3% compared with heuristic and IEM control respectively. Moreover, our results suggest that the application of the methodology increases peak energy savings up to 17%, scales up solar generation usage up to 23%, and the optimal storage size obtained in the shared community case reduces up to 50%.
Frequency deviations of power systems caused by grid-connected wind power fluctuations is one of the key factors which restrains the increase of wind penetration level. This paper examines a combined ...wind and hybrid energy storage system (HESS, supercapacitor, and battery) to smooth wind power fluctuations. A fuzzy-based wind-HESS system (FWHS) controller is proposed to suppress the wind power fluctuations. The proposed controller takes full advantage of the complimentary characteristics of the supercapacitor and battery with the supercapacitor and battery in charge of high and middle frequency components of wind fluctuations, respectively. A differential evolution (DE)-based optimal sizing method for HESS systems is introduced to evaluate the minimum capacity of HESS as being limited by grid frequency deviation. The efficiency of the proposed scheme in the paper for wind-HESS system is evaluated by a real Chinese power system.
•MILP optimization model for operation and investment of PV-battery systems.•Use of high resolution (10s) electrical household load and PV generation profiles.•Analysis of influence of temporal ...resolution on self-consumption and optimal sizing.•Electrical load profile characteristics influence required temporal resolution.
The interest in self-consumption of electricity generated by rooftop photovoltaic systems has grown in recent years, fueled by decreasing levelized costs of electricity and feed-in tariffs as well as increasing end customer electricity prices in the residential sector. This also fostered research on grid-connected PV-battery storage systems, which are a promising technology to increase self-consumption. In this paper a mixed-integer linear optimization model of a PV-battery system that minimizes the total discounted operating and investment costs is developed. The model is employed to study the effect of the temporal resolution of electrical load and PV generation profiles on the rate of self-consumption and the optimal sizing of PV and PV-battery systems. In contrast to previous studies high resolution (10s) measured input data for both PV generation and electrical load profiles is used for the analysis. The data was obtained by smart meter measurements in 25 different households in Germany. It is shown that the temporal resolution of load profiles is more critical for the accuracy of the determination of self-consumption rates than the resolution of the PV generation. For PV-systems without additional storage accurate results can be obtained by using 15min solar irradiation data. The required accuracy for the electrical load profiles depends strongly on the load profile characteristics. While good results can be obtained with 60s for all electrical load profiles, 15min data can still be sufficient for load profiles that do not exhibit most of their electricity consumption at power levels above 2kW. For PV-battery systems the influence of the temporal resolution on the rate of self-consumption becomes less distinct. Depending on the load profile, temporal resolutions between 5min and 60min yield good results. For optimal sizing of the PV power and the storage capacity a resolution of 60min is found to be sufficient. For the sizing of the battery inverter power of the storage system, a finer temporal resolution of at least 300s is necessary.
Real-world distributed storage systems (DSSs) are heterogeneous because storage nodes may have unequal per-symbol storage costs, and network links may have unequal per-symbol transmission costs. For ...some general classes of heterogeneous DSSs, the optimal tradeoff between storage and repair costs achievable by functional repair codes is known (at least numerically). However, it is unclear whether exact-repair codes can achieve any point of such an optimal storage-repair tradeoff curve, especially at the point of the minimum storage cost. In this paper, we provide an affirmative answer to the question by constructing the so-called heterogeneous minimum storage repair (HMSR) codes for both the average and worst-case repair costs. To optimize storage and repair costs, a heterogeneous DSS may need to adopt irregular array codes and repair a node by downloading unequal numbers of symbols from helper nodes. However, our results show that for almost all heterogeneous DSSs, exact-repair HMSR codes are regular array codes covering an adequately chosen set of nodes. Specifically, exact-repair HMSR codes are designed by stacking conventional MSR codes and applying different repair schemes to different layers. Still, this does not work for every heterogeneous DSS. It is proven that using regular or linear irregular array codes for constructing exact-repair HMSR codes is insufficient in some cases.
Structural trapping is the primary CO2 geo-storage mechanism, and it has historically been quantified by CO2 column heights, which can be permanently immobilized beneath a caprock, using a buoyancy ...force-capillary force balance. However, the high dependence of CO2-wettability (a key parameter in the above analysis) on pressure and temperature – and thus storage depth – has not been taken into account. Importantly, rock can be CO2-wet at high pressure, and this wettability reversal results in zero structural trapping below a certain storage depth (∼2400 m maximum caprock depth for a most likely scenario is estimated here). Furthermore, more relevant than the CO2 column height is the actual mass of CO2 which can be stored by structural trapping (mCO2). This aspect has now been quantified here, and importantly, mCO2 goes through a maximum at ∼1300 m depth, thus there exists an optimal storage depth at around 1300 m depth.
With the increase of renewable energy permeability and the development of distributed grid, energy storage plays an increasingly important role in the power system. A lot of studies have shown that ...energy storage can already be economically feasible. However, most previous studies concentrated on the value of energy storage in the free electricity market. In China, the power grid monopolizes the process of electricity transmission, distribution and retail, and the feed-in tariff and retail prices of electricity are regulated by government. It is difficult to analyze the application value of energy storage for China's electricity due to the lacking of data. The major contribution of this paper is to evaluate the application value according to the data of a provincial power grid. The results support the argument that energy storage can generate positive returns. The optimal storage capacity and operational strategy are also discussed in this paper.
•Estimating the application value of energy storage in China's power grid.•The efficiency of the power grid can be improved by using EES.•The EES can bring remarkable value in China.•The optimal storage capacity and operational strategy are determined.
We consider a stylized model for a power network with distributed local power generation and storage. This system is modeled as a network connection of a large number of nodes, where each node is ...characterized by a local electricity consumption, has a local electricity production (photovoltaic panels for example) and manages a local storage device. Depending on its instantaneous consumption and production rate as well as its storage management decision, each node may either buy or sell electricity, impacting the electricity spot price. The objective at each node is to minimize energy and storage costs by optimally controlling the storage device. In a noncooperative game setting, we are led to the analysis of a nonzero sum stochastic game with
N
players where the interaction takes place through the spot price mechanism. For an infinite number of agents, our model corresponds to an extended mean field game. We are able to compare this solution to the optimal strategy of a central planner and in a linear quadratic setting, we obtain and explicit solution to the extended mean field game and we show that it provides an approximate Nash equilibrium for
N
-player game.
We evaluated the costs of implementation of a sustainable electricity system with carbon net zero emission by 2050. To achieve this goal, it is assumed to reduce the use of fossil fuel-based power ...generation, increase carbon-free clean energy generation, and secure storage facilities. We compared the total costs including the capital cost of new generators and storage technologies, fuel costs, and emission costs by 2050. We also investigated the effects of various levels of carbon price, curtailment rates of renewable energy output, demand pattern shift, increasing nuclear power generation, building pumped hydro storage, and utilization of hydrogen storage as long-duration storage. One of our findings indicates that although a higher curtailment rate necessitates increased renewable energy installation to achieve national emission target, it leads to a reduction in total costs due to the decreased requirement for storage capacity. Our findings provided invaluable insights into the potential of these solutions to facilitate the transition to a more sustainable electricity system in South Korea and other countries with similar policy goals.
•Cost evaluation for South Korea’s transition to a net zero electricity system by 2050.•Storage cost estimation for official government targets based on optimal storage mix model.•Insights into the potential policy options to facilitate net zero energy transition.
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