• Energy Research

Microgrids (MG) cluster are isolated from the utility grid but they have the potential to achieve better techno-economic performance by using joint energy and reserve sharing among MGs. This paper proposes a techno-economic framework for the optimal operation of isolated MGs-cluster by scheduling cooperative energy sharing and real-time reserve sharing for ancillary services based on the cooperative game theory. In the day-ahead scheduling, a coalitional sharing scheme is formulated as an adjustable robust optimization (ARO) problem to optimally schedule the energy and reserves of distributed generators (DGs) and energy storage systems (ESSs), thereby responding to the uncertainties of photovoltaic systems, wind turbines, and loads. These uncertainties are the main reason for power system imbalance which is mitigated by regulating the frequency in real-time and a dynamic droop control process is used to realize the reserves in a distributed manner. This control process is embedded into the ARO problem, which is formulated as an affine ARO problem and then transformed into a deterministic optimization problem that is solved by off-shore solvers Apart from the reduction in the operation cost, the frequency restoration can be improved jointly, resulting in the coupled techno-economic contribution of the MGs in the coalition. The contribution of each MG is quantified using shapely value, a cooperative game approach. Simulations are conducted for a case study with 4 MGs and the results demonstrate the merits of the proposed cooperative scheduling scheme.

Microgrids (MG) cluster are isolated from the utility grid but they have the potential to achieve better techno-economic performance by using joint energy and reserve sharing among MGs. This paper proposes a techno-economic framework for the optimal operation of isolated MGs-cluster by scheduling cooperative energy sharing and real-time reserve sharing for ancillary services based on the cooperative game theory. In the day-ahead scheduling, a coalitional sharing scheme is formulated as an adjustable robust optimization (ARO) problem to optimally schedule the energy and reserves of distributed generators (DGs) and energy storage systems (ESSs), thereby responding to the uncertainties of photovoltaic systems, wind turbines, and loads. These uncertainties are the main reason for power system imbalance which is mitigated by regulating the frequency in real-time and a dynamic droop control process is used to realize the reserves in a distributed manner. This control process is embedded into the ARO problem, which is formulated as an affine ARO problem and then transformed into a deterministic optimization problem that is solved by off-shore solvers Apart from the reduction in the operation cost, the frequency restoration can be improved jointly, resulting in the coupled techno-economic contribution of the MGs in the coalition. The contribution of each MG is quantified using shapely value, a cooperative game approach. Simulations are conducted for a case study with 4 MGs and the results demonstrate the merits of the proposed cooperative scheduling scheme.

Abstract The multi-energy interconnected energy system (MEIES) consists of multiple energy hubs (EHs) connected through the energy router (ER). To realize the optimal operation of the MEIES, this paper proposes an energy optimization and routing control strategy for the neotype MEIES based on ER using the lower and upper layers. In the lower layer, the multi-energy conversion device and storage device in the energy local area network (E-LAN) are modeled in detail, and the minimum cost electricity-heat-gas-cool multi-energy optimization strategy is realized. In the upper layer, the electric, heating, and natural gas network's energy flow is normalized by strict mathematical derivation in the energy wide area network (E-WAN). The generalized energy loss model of a multi-energy network with the unified mathematical equation is obtained. Then, based on the loss model and fully considering the differences of national conditions and policies, the unified energy routing control strategy of minimum loss local absorption (MLLA) in the monopoly market and of minimum loss multipath transmission (MLMT) in the competitive market are proposed for different decision-makers. Moreover, two kinds of ER transactions of competitive market priority ranking methods are proposed to achieve the expected incentive goal by transferring the energy loss of the transaction from one to another, which are the priority determined by the quotation and transaction volume. Finally, the feasibility and effectiveness of the overall strategy are verified by simulation and comparison.

Abstract The multi-energy interconnected energy system (MEIES) consists of multiple energy hubs (EHs) connected through the energy router (ER). To realize the optimal operation of the MEIES, this paper proposes an energy optimization and routing control strategy for the neotype MEIES based on ER using the lower and upper layers. In the lower layer, the multi-energy conversion device and storage device in the energy local area network (E-LAN) are modeled in detail, and the minimum cost electricity-heat-gas-cool multi-energy optimization strategy is realized. In the upper layer, the electric, heating, and natural gas network's energy flow is normalized by strict mathematical derivation in the energy wide area network (E-WAN). The generalized energy loss model of a multi-energy network with the unified mathematical equation is obtained. Then, based on the loss model and fully considering the differences of national conditions and policies, the unified energy routing control strategy of minimum loss local absorption (MLLA) in the monopoly market and of minimum loss multipath transmission (MLMT) in the competitive market are proposed for different decision-makers. Moreover, two kinds of ER transactions of competitive market priority ranking methods are proposed to achieve the expected incentive goal by transferring the energy loss of the transaction from one to another, which are the priority determined by the quotation and transaction volume. Finally, the feasibility and effectiveness of the overall strategy are verified by simulation and comparison.

Abstract This paper proposes a two-stage multi-attribute analysis method in conceptualizing the feasible electrification strategy with optimal capacities for a mid-rise building situated in El-Qsier urban city, Egypt. The proposed model measures the implementation practicability of hybrid mini-grid against stand-alone diesel and the utility grid extension systems. The model takes into consideration, simultaneously, a total of 12 attributes covering technical, economic, environmental, and socio-political sustainability aspects. First, an accurate Energy-Enviro-Economic (3E) optimization analysis is performed to determine the set of feasible configurations using HOMER Pro software. Second, a Multi-Attribute Decision Making (MADM) model is established based on AHP, TOPSIS, VIKOR, CODAS, WASPAS methods to identify the unique best alternative. The results of the 3E optimization and decision making analyses confirm the non-viability of the reference site for grid extension against other off-grid systems. Also, the 100 % hybrid renewable mini-grid system is nominated as the most sustainable design, and it yielded optimal capacities of 196 kW, 72 kW, 587 kW h, and 75 kW for photovoltaic, wind turbine, converter, and battery. The system has total life-cycle and energy costs of 751,597$ and 0.2374$/kWh, respectively, with a zero-emission value and maximum social benefits equals 0.6089 jobs/year. Meanwhile, the sensitivity analysis elucidates that the load growth and battery cost have a high impact on investment decisions rather than solar irradiance and wind speed.

Abstract This paper proposes a two-stage multi-attribute analysis method in conceptualizing the feasible electrification strategy with optimal capacities for a mid-rise building situated in El-Qsier urban city, Egypt. The proposed model measures the implementation practicability of hybrid mini-grid against stand-alone diesel and the utility grid extension systems. The model takes into consideration, simultaneously, a total of 12 attributes covering technical, economic, environmental, and socio-political sustainability aspects. First, an accurate Energy-Enviro-Economic (3E) optimization analysis is performed to determine the set of feasible configurations using HOMER Pro software. Second, a Multi-Attribute Decision Making (MADM) model is established based on AHP, TOPSIS, VIKOR, CODAS, WASPAS methods to identify the unique best alternative. The results of the 3E optimization and decision making analyses confirm the non-viability of the reference site for grid extension against other off-grid systems. Also, the 100 % hybrid renewable mini-grid system is nominated as the most sustainable design, and it yielded optimal capacities of 196 kW, 72 kW, 587 kW h, and 75 kW for photovoltaic, wind turbine, converter, and battery. The system has total life-cycle and energy costs of 751,597$ and 0.2374$/kWh, respectively, with a zero-emission value and maximum social benefits equals 0.6089 jobs/year. Meanwhile, the sensitivity analysis elucidates that the load growth and battery cost have a high impact on investment decisions rather than solar irradiance and wind speed.

Abstract In practical distribution networks of long-distance feeders, load's expansion and seasonal load variations seriously affect the system performance. In the context of the present advancements in D.G.s, especially generating from the renewable energy (RE) sources along with the recent support of policy-makers, it is smart consideration to transform the long-distance conventional distribution networks into the optimal DG-integrated systems for the augmentation of the technical and economic benefits jointly. In this article, a novel methodology, namely Hybrid-PPSO-GSA, is proposed and applied to maximize the techno-economic benefits via an optimal RE-DG integrated system. The proposed methodology focused on the optimal placement and sizing of RE-DG into the distribution system, considering the stochastic analysis of RE-DGs such as W.T. and P.V. with multiple objectives. The Hybrid PPSO-GSA was tested on standard 69-bus systems and particularly implemented on 94-bus long-distance practical distribution feeder located in Portuguese; for power loss reduction, voltage profile, and stability enhancement. Apart from the reduction in the power loss and voltage improvement, the energy loss can be improved jointly, resulting in the coupled techno-economic contribution of the DG-integrated system. Simulations are conducted for various scenarios, and the obtained results demonstrate the merits of the proposed scheme.