scholarly journals Robust operation of microgrid energy system under uncertainties and demand response program

2020 ◽  
Vol 17 (2) ◽  
pp. 1005
Author(s):  
Sahar Seyyedeh Barhagh ◽  
Amin Mohammadpour Shotorbani ◽  
Behnam Mohammadi-Ivatloo ◽  
Kazem Zare ◽  
Ali Farzamnia
Keyword(s):  
Power Systems ◽  
Demand Response ◽  
Optimization Problems ◽  
Energy Systems ◽  
Stochastic Scheduling ◽  
Energy System ◽  
Optimization Method ◽  
Operating Conditions ◽  
Mixed Integer ◽  
Demand Response Program

<span>Microgrid energy systems are one of suitable solutions to the available problems in power systems such as energy losses, and resiliency issues. Local generation by these energy systems can reduce the role of the upstream network, which is a challenge in risky conditions. Also, uncertain behavior of electricity consumers and generating units can make the optimization problems sophisticated. So, uncertainty modeling seems to be necessary. In this paper, in order to model the uncertainty of generation of photovoltaic systems, a scenario-based model is used, while the robust optimization method is used to study the uncertainty of load. Moreover, the stochastic scheduling is performed to model the uncertain nature of renewable generation units. Time-of–use rates of demand response program (DRP) is also utilized to improve the system economic performance in different operating conditions. Studied problem is modeled using a mixed-integer linear programming (MILP). The general algebraic modeling system (GAMS) package is used to solve the proposed problem. A sample microgrid is studied and the results with DRP and without DRP are compared. It is shown that same robustness is achieved with a lower increase in the operation cost using DRP.</span>

scholarly journals Modern Solutions to Modeling and Optimization of the Steady State of Multi-Energy Systems

2020 ◽  
Vol 209 ◽  
pp. 02007
Author(s):  
Dmitry Bykov ◽  
Dmitry Efimov
Keyword(s):  
Steady State ◽  
Mathematical Models ◽  
Optimization Problems ◽  
General Structure ◽  
Flow Distribution ◽  
Energy Systems ◽  
Physical Nature ◽  
Energy System ◽  
Operating Conditions ◽  
Term Operation

A complex solution of problem of creating mathematical models of multi-energy systems is possible using a unified approach. An approach that will ensure consistent construction of mathematical models and unification of computational algorithms. The paper presents the elements of the concept of energy circuits as a basis for unified modeling of systems of different physical nature. The existing and developed approaches to solving the problems of calculating the flow distribution in multi-energy systems are presented, based on the analysis of publications on this subject. The general structure of the mathematical model of the flow distribution in a multi-energy system and the set of optimization problems for steady-state operating conditions are described. A possible formulation of the optimization problem for the short-term operation of a multi-energy system is presented.

scholarly journals Control Strategy for MGT Generation System Optimized by Improved WOA to Enhance Demand Response Capability

Energies ◽  
2019 ◽  
Vol 12 (16) ◽  
pp. 3101
Author(s):  
Jiecheng Zhu ◽  
Xitian Wang ◽  
Da Xie ◽  
Chenghong Gu
Keyword(s):  
Power Systems ◽  
Demand Response ◽  
Control Strategy ◽  
Heuristic Algorithms ◽  
Optimization Problems ◽  
Optimization Method ◽  
Generation System ◽  
Whale Optimization ◽  
Valve Opening ◽  
Response Capability

The grid-connected micro gas turbine (MGT) generation system is playing an important role in power systems because of its demand response capability and application in combined heat and power (CHP) systems. When applied to promote demand response, the generation system is expected to respond to follow instructions quickly, but a rapid response harms the safety and is not conducive to the benefits of customers, which leads to a contradiction. In this paper, a closed-loop power control is introduced for the MGT to improve demand response capability. The rate of fuel valve opening is limited so as to protect the equipment from thermal fatigue threats. An optimization method is developed for identifying the control parameters, balancing the response time and unrealized energy in the regulation process. An improved whale optimization algorithm (IWOA) is proposed to implement the optimization. Results of the algorithm performance verify that WOA is competitive with other heuristic algorithms, and IWOA is more suitable for parameter optimization problems than WOA because of better efficiency and exploitation capability. Results of power response further indicate that the proposed control strategy can achieve expected aims and is suitable for the MGT generation system.

scholarly journals Optimising Energy Flexibility of Boats in PV-BESS Based Marina Energy Systems

Energies ◽  
2021 ◽  
Vol 14 (12) ◽  
pp. 3397
Author(s):  
Dawid Jozwiak ◽  
Jayakrishnan Radhakrishna Pillai ◽  
Pavani Ponnaganti ◽  
Birgitte Bak-Jensen ◽  
Jan Jantzen
Keyword(s):  
Demand Response ◽  
Alternative Energy ◽  
Storage System ◽  
Essential Element ◽  
Energy Systems ◽  
Late Summer ◽  
Energy System ◽  
Mixed Integer ◽  
Load Factor ◽  
Grid Operation

Implementation of alternative energy supply solutions requires the broad involvement of local communities. Hence, smart energy solutions are primarily investigated on a local scale, resulting in integrated community energy systems (ICESs). Within this framework, the distributed generation can be optimally utilised, matching it with the local load via storage and demand response techniques. In this study, the boat demand flexibility in the Ballen marina on Samsø—a medium-sized Danish island—is analysed for improving the local grid operation. For this purpose, suitable electricity tariffs for the marina and sailors are developed based on the conducted demand analysis. The optimal scheduling of boats and battery energy storage system (BESS) is proposed, utilising mixed-integer linear programming. The marina’s grid-flexible operation is studied for three representative weeks—peak tourist season, late summer, and late autumn period—with the combinations of high/low load and photovoltaic (PV) generation. Several benefits of boat demand response have been identified, including cost savings for both the marina and sailors, along with a substantial increase in load factor. Furthermore, the proposed algorithm increases battery utilisation during summer, improving the marina’s cost efficiency. The cooperation of boat flexibility and BESS leads to improved grid operation of the marina, with profits for both involved parties. In the future, the marina’s demand flexibility could become an essential element of the local energy system, considering the possible increase in renewable generation capacity—in the form of PV units, wind turbines or wave energy.

scholarly journals Optimal Design on Fossil-to-Renewable Energy Transition of Regional Integrated Energy Systems under CO2 Emission Abatement Control: A Case Study in Dalian, China

Energies ◽  
2021 ◽  
Vol 14 (10) ◽  
pp. 2879
Author(s):  
Xinxin Liu ◽  
Nan Li ◽  
Feng Liu ◽  
Hailin Mu ◽  
Longxi Li ◽  
...  
Keyword(s):  
Renewable Energy ◽  
Optimal Design ◽  
Co2 Emission ◽  
Energy Demand ◽  
Energy Systems ◽  
Energy System ◽  
Mixed Integer ◽  
Total Annual Cost ◽  
Emission Abatement ◽  
Integrated Energy Systems

Optimal design of regional integrated energy systems (RIES) offers great potential for better managing energy sources, lower costs and reducing environmental impact. To capture the transition process from fossil fuel to renewable energy, a flexible RIES, including the traditional energy system (TES) based on the coal and biomass based distributed energy system (BDES), was designed to meet a regional multiple energy demand. In this paper, we analyze multiple scenarios based on a new rural community in Dalian (China) to capture the relationship among the energy supply cost, increased share of biomass, system configuration transformation, and renewable subsidy according to regional CO2 emission abatement control targets. A mixed integer linear programming (MILP) model was developed to find the optimal solutions. The results indicated that a 40.58% increase in the share of biomass in the RIES was the most cost-effective way as compared to the separate TES and BDES. Based on the RIES with minimal cost, by setting a CO2 emission reduction control within 40%, the RIES could ensure a competitive total annual cost as compared to the TES. In addition, when the reduction control exceeds 40%, a subsidy of 53.83 to 261.26 RMB/t of biomass would be needed to cover the extra cost to further increase the share of biomass resource and decrease the CO2 emission.

scholarly journals Impact of demand response on BIPV and district multi-energy systems design in Singapore and Switzerland

2021 ◽  
Vol 2042 (1) ◽  
pp. 012096
Author(s):  
Christoph Waibel ◽  
Shanshan Hsieh ◽  
Arno Schlüter
Keyword(s):  
Demand Response ◽  
Programming Model ◽  
Systems Design ◽  
Energy Systems ◽  
Mixed Integer ◽  
Peak Shaving ◽  
Climate Conditions ◽  
Building Integrated Photovoltaics ◽  
Energy Hub ◽  
The Impact

Abstract This paper demonstrates the impact of demand response (DR) on optimal multi-energy systems (MES) design with building integrated photovoltaics (BIPV) on roofs and façades. Building loads and solar potentials are assessed using bottom-up models; the MES design is determined using a Mixed-Integer Linear Programming model (energy hub). A mixed-use district of 170,000 m2 floor area including office, residential, retail, education, etc. is studied under current and future climate conditions in Switzerland and Singapore. Our findings are consistent with previous studies, which indicate that DR generally leads to smaller system capacities due to peak shaving. We further show that in both the Swiss and Singapore context, cost and emissions of the MES can be reduced significantly with DR. Applying DR, the optimal area for BIPV placement increases only marginally for Singapore (~1%), whereas for Switzerland, the area is even reduced by 2-8%, depending on the carbon target. In conclusion, depending on the context, DR can have a noticeable impact on optimal MES and BIPV capacities and should thus be considered in the design of future, energy efficient districts.

scholarly journals Managing Wind Power Generation via Indexed Semi-Markov Model and Copula

Energies ◽  
2020 ◽  
Vol 13 (16) ◽  
pp. 4246 ◽  
Author(s):  
Guglielmo D’Amico ◽  
Giovanni Masala ◽  
Filippo Petroni ◽  
Robert Adam Sobolewski
Keyword(s):  
Power Generation ◽  
Power Systems ◽  
Wind Energy ◽  
Output Power ◽  
Wind Turbines ◽  
Wind Farm ◽  
Energy Systems ◽  
Wind Farms ◽  
Energy System ◽  
Spatial Dependencies

Because of the stochastic nature of wind turbines, the output power management of wind power generation (WPG) is a fundamental challenge for the integration of wind energy systems into either power systems or microgrids (i.e., isolated systems consisting of local wind energy systems only) in operation and planning studies. In general, a wind energy system can refer to both one wind farm consisting of a number of wind turbines and a given number of wind farms sited at the area in question. In power systems (microgrid) planning, a WPG should be quantified for the determination of the expected power flows and the analysis of the adequacy of power generation. Concerning this operation, the WPG should be incorporated into an optimal operation decision process, as well as unit commitment and economic dispatch studies. In both cases, the probabilistic investigation of WPG leads to a multivariate uncertainty analysis problem involving correlated random variables (the output power of either wind turbines that constitute wind farm or wind farms sited at the area in question) that follow different distributions. This paper advances a multivariate model of WPG for a wind farm that relies on indexed semi-Markov chains (ISMC) to represent the output power of each wind energy system in question and a copula function to reproduce the spatial dependencies of the energy systems’ output power. The ISMC model can reproduce long-term memory effects in the temporal dependence of turbine power and thus understand, as distinct cases, the plethora of Markovian models. Using copula theory, we incorporate non-linear spatial dependencies into the model that go beyond linear correlations. Some copula functions that are frequently used in applications are taken into consideration in the paper; i.e., Gumbel copula, Gaussian copula, and the t-Student copula with different degrees of freedom. As a case study, we analyze a real dataset of the output powers of six wind turbines that constitute a wind farm situated in Poland. This dataset is compared with the synthetic data generated by the model thorough the calculation of three adequacy indices commonly used at the first hierarchical level of power system reliability studies; i.e., loss of load probability (LOLP), loss of load hours (LOLH) and loss of load expectation (LOLE). The results will be compared with those obtained using other models that are well known in the econometric field; i.e., vector autoregressive models (VAR).

scholarly journals Development of Complex Energy Systems with Absorption Technology by Combining Elementary Processes

Energies ◽  
2019 ◽  
Vol 12 (3) ◽  
pp. 495 ◽  
Author(s):  
Kosuke Seki ◽  
Keisuke Takeshita ◽  
Yoshiharu Amano
Keyword(s):  
Alternative Energy ◽  
Energy Systems ◽  
Energy System ◽  
Operating Conditions ◽  
Optimal System ◽  
System Configuration ◽  
Bottom Up ◽  
Elementary Processes ◽  
Minimum Number ◽  
Synthesis Methodology

Optimal design of energy systems ultimately aims to develop a methodology to realize an energy system that utilizes available resources to generate maximum product with minimum components. For this aim, several researches attempt to decide the optimal system configuration as a problem of decomposing each energy system into primitive process elements. Then, they search the optimal combination sequentially from the minimum number of constituent elements. This paper proposes a bottom-up procedure to define and explore configurations by combining elementary processes for energy systems with absorption technology, which is widely applied as a heat driven technology and important for improving system’s energy efficiency and utilizing alternative energy resources. Two examples of application are presented to show the capability of the proposed methodology to find basic configurations that can generate the maximum product. The demonstration shows that the existing absorption systems, which would be calculated based on the experience of designers, could be derived by performing optimization with the synthesis methodology automatically under the simplified/idealized operating conditions. The proposed bottom-up methodology is significant for realizing an optimized absorption system. With this methodology, engineers will be able to predict all possible configurations and identify a simple yet feasible optimal system configuration.

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