Operation Cost Of Microgrid Research Articles

Microgrid dynamic combined power–heat economic-emission dispatch with deferrable loads and price-based energy storage elements and power exchange

This research effort formulates and solves a biobjective dynamic combined heat and power economic-emission dispatch (DCHPED) of generation in a microgrid (MG). The MG encompasses fossil-fuel power and heat units, renewable resources, price-operated electrical and thermal energy storage elements, bidirectional-exchange of electrical power with the external grid, and fixed nondefferrable and deferrable loads. The two objective functions involve the total operation cost and the total gas emission produced by the fossil fuel units participating in the MG dynamic dispatch. Costs of emission tax and price-based energy storage and exchanges with the external grid are ingredients of the total operating costs. The Bernstein-search differential evolution (BSDE) algorithm is utilized to deal with the problem to obtain the day-ahead optimal schedules of available resources. The nonlinear nonconvex MG DCHPED optimization problem that has a large number of decision variables involves equality and inequality constraints, production costs, emission levels, taxes of released gases, ramp-rate limits of power-producing units, effects of valve-points in generating units, active power transmission losses, and feasible operation regions of cogenerating (CHP) units. The paper investigates the positive impacts of utilizing price-based electrical and thermal storage elements, deferrability of loads, and price-based power exchanges on the day-ahead MG operation cost. The paper also describes an approach to achieve the best compromise solution (BCS) of the MG DCHPED employing the fuzzy satisfying method (FSM). In addition, it shows that gas emissions and emission taxes in the MG can be both controlled by exchanging power with the external grid.

Decentralized Energy Management System for LV Microgrid Using Stochastic Dynamic Programming With Game Theory Approach Under Stochastic Environment

In this article, we propose a decentralized energy management system to minimize the daily operating cost of microgrid and the net charging cost of individual plug-in electric vehicles (PEVs) while maintaining comfort level and privacy. A novel approach based on stochastic dynamic programming (SDP) with N-person noncooperative game-theoretic approach is used for real-time scheduling of heterogeneous PEVs both ways-in the grid-to-vehicle (G2V) and vehicle-to-grid (V2G) mode. We use the SDP method for full enumeration of all possible decisions while game theory provides quick convergence to Nash-equilibrium. The proposed approach considers uncertainties of renewable generation as well as load demand and offers autonomy to the microgrid operators and PEVs owners to optimize their objectives individually. The effectiveness of the proposed approach has been tested on modified LV CIGRE and modified IEEE 33 bus test networks. The results have been compared with the deterministic and stochastic bi-level optimization. The simulation results exhibit that the proposed algorithm outperforms the other two algorithms in terms of operating cost, incentive to the PEVs owner, robustness to uncertainties, and convergence. The operating cost reduction achieved for the modified CIGRE model and modified IEEE 33 bus with the proposed approach is 20.02% and 36.53%, respectively, as compared to the deterministic framework, whereas 7.64% and 16.35% are the values obtained in comparison with the bi-level approach.

Optimal Energy Management Strategy for an Islanded Microgrid with Hybrid Energy Storage

Due to the randomness and volatility of light intensity and wind speed, renewable generation and load management are facing new challenges. This paper proposes a novel energy management strategy to extend the life cycle of the hybrid energy storage system (HESS) based on the state of charge (SOC) and reduce the total operating cost of the islanded microgrid (MG). In this paper, a demand response (DR) optimization model of independent MG is introduced considering the total cost of MG operation, carbon emission and new energy consumption penalty. Meanwhile, by analyzing the SOC of the HESS, starting and stopping criteria (SSC) of diesel generator (DG), residential load classification, an optimal energy management strategy for island grid operation of HESS based on DR is proposed. Then, the particle swarm optimization (PSO) algorithm with improved acceleration factor is applied to solve the optimization scheme. The simulation results show that a novel energy management strategy has improved the economical and reliable performance of the independent MG via setting the charging and discharging criteria of HESS and SSC of DG. Moreover, flexible scheduling of part controllable loads can be used to improve the renewable energy consumption rate and reduce the loss of load rate.

Optimal scheduling of a micro-grid with multi-period islanding constraints using hybrid CFCS technique

This paper proposes an efficient technique for optimum scheduling of micro-grids with multi-period islanding restrictions. The proposed method is joint implementation of Cuttle Fish Algorithm (CFA) and Crow Search Algorithm (CSA); is known CFCS method. Here, the CFA search behavior is modified by the CSA update position. The proposed CFCS system is utilized for optimal scheduling of micro-grid and considerably decreases the calculation load. The main purpose of proposed work is diminish the micro-grid operation cost together with the dispatch-able units operation cost, cost of power transmission as main grid with inconvenience cost recognized with consumers. The cost of power transmission from main phase can be positive or negative based on the flow direction of transmission line linking the microcircuit to main phase. Negative cost that represents an export of power to main grid emerges as economic advantage of micro-grid. Cost of inconvenience implies the penalty of modifiable loads programming outside the time intervals particular by the consumers. Constant penalty factor is utilized for prioritizing loads with respect to operation sensitivity inside the particular time intervals, in which a superior value of the penalty factor implies a least flexible load based on time interval operation settings. The value of the penalty factor is chosen reasonably greater to unit generation cost and market price. In proposed technique, the CFCS is used for establishing the correct program of the MG combinations according to load side power range. The CFCS method, objective function can be defined as system data subject to equality and inequality limitations. At that time, CFCS model is performed at MATLAB/Simulink working platform and performance is estimated to existing techniques.

Multi-objective Planning of the Economic Operation of Microgrid Considering the Energy Loss and the Start-up Cost of Conventional Units

The fluctuation of load and new energy will have an important impact on the operation mode of microgrid. In order to balance the economy and reliability of microgrid, a chance constrained model of microgrid is established firstly. Based on the reliability cost, the operation cost of microgrid under different confidence levels is calculated, and a reasonable confidence level of rotating reserve is obtained. This paper analyzes the impact of energy storage charge and discharge loss and conventional unit start-up cost on the economic operation of the isolated micro grid; for the grid connected micro grid, the economy of its own operation and the effect of auxiliary large grid peak load shedding are taken as the objective function, and the multi-objective programming method proposed in this paper is used to solve the problem. The example analysis shows that the multi-objective programming method in this paper, by combining with particle swarm optimization algorithm, can optimize the weight of different objectives reasonably, which can not only help the large power grid to cut peak and fill valley, but also realize the economy of microgrid operation.

Research on Bi-level Coordinated Optimal Dispatching Strategy for Microgrid Cluster

The interconnection of multiple microgrids can form a microgrid cluster (MGC). The economic benefit and operation reliability of the whole system can be improved through the energy mutual-aid and coordination control between microgrids. This paper proposes a bi-level coordinated optimal dispatching strategy for microgrid clusters. The upper layer aims to minimize the operating costs of the microgrid cluster system and the power fluctuation of the tie lines. The exchange power and generation power of each sub-microgrid are coordinated and controlled, which are sent to the lower level model as scheduling instructions. The lower layer takes a single microgrid as the research object. By optimizing the output of power generation unit, the operation cost of single microgrid can be minimized. Iterative solution is adopted between the bi-level optimization models. In order to avoid the premature and local convergence of the algorithm in the optimization process, the improved artificial bee colony algorithm (ABC) is used to solve the objective function. Finally, simulation examples verify the effectiveness and feasibility of the proposed strategy.

Research on Comprehensive Value of Electrical Energy Storage in CCHP Microgrid with Renewable Energy Based on Robust Optimization

The combined cooling, heating, and power (CCHP) microgrid system is good for energy gradient utility. At the same time, it can promote the renewable energy (RE) consumption and abate environmental pollution. In a CCHP microgrid system, the electrical energy storage (EES), which can storage and release electrical energy, plays an indispensable role. A robust optimization model of the CCHP microgrid participating in power market transaction is constructed to calculate the CCHP microgrid operation cost in 4 cases. The results show that the EES can significantly reduce the cost of the CCHP microgrid by 13.21%, compared with 8.36% in Group 1 without renewable energy. The EES can reduce the reserved capacity of micro gas turbine units to deal with the precariousness of RE generation and then reduce the CCHP microgrid operation cost by reducing the purchase of energy from the power grid and arbitrage. Finally, the calculation method of comprehensive value of the EES is constructed. The comprehensive value of the EES is higher in Group 2 with renewable energy compared with Group 1 without renewable energy. Through net present value (NPV) calculation and sensitivity analysis, it is found that the RE penetration level and EES cost have the greatest impact on the economic performance of EES. This shows that with the continuous rising of the RE penetration level and the gradual decrease of EES cost, great potential still waits to be tapped in the comprehensive value of EES in the future.

Interactive optimization between active distribution network with multi-microgrids based on distributed algorithm

Interaction between microgrid (MG) and active distribution network (ADN) can effectively improve the operating economics and reliability of power system. A bi-level interactive optimization model for ADN with MGs is studied in this paper. The upper level is a multi-objective problem that minimizes both the operation cost and voltage deviation of each node. The lower level aims to minimize the operation cost of MG. The interaction between adjacent MGs ensures a relatively lower electricity price. To achieve a low-carbon system, carbon trading cost is also considered at both levels. And the model is decoupled into several subproblems and solved using a distributed method. Therefore, the privacy of each entity is ensured. The results prove the effectiveness of the proposed method.

Hierarchical two‐stage robust optimisation dispatch based on co‐evolutionary theory for multiple CCHP microgrids

Combined cooling, heating, and power (CCHP) microgrids are a special form of a microgrid that is attracting increasing attention. This study contributes to the goal of minimising the operation cost of CCHP microgrids by proposing a hierarchical two-stage robust optimisation dispatch model for multiple CCHP microgrid systems. The uncertainties associated with wind power output, electric power, heating, and cooling loads, and transmission line failures are considered in the proposed model. Moreover, the electricity purchasing and selling prices of each microgrid are independently determined. The proposed model applies the outputs of fuel cells, energy storage devices, and gas turbines, the distribution factor of waste heat, and the power transmission between the microgrids and an external grid as control variables. The optimised dispatch problem is solved using McCormick envelopes relaxation and a novel column and constraint generation algorithm that provides enhanced optimisation performance by implementing co-evolutionary theory. In this way, the microgrid system is divided into several sections, and each section is represented as an individual min–max–min problem. The rationality and validity of the proposed model and the superiority of the solution performance of the improved algorithm are verified through simulation case studies involving a system composed of four CCHP microgrids.

Multi-energy coordinated microgrid scheduling with integrated demand response for flexibility improvement

Multi-energy supply system is under development with a variety of benefits for microgrid operation. In this paper, the coordinated scheduling and optimal operation strategy of coupled heat-power-gas (CHPG) microgrid are studied for flexibility improvement in consideration of implementing cogeneration technology and power to gas (P2G) technology. To enhance the operational flexibility of the CHPG in supplying multiple energy demands, an integrated demand response (IDR) model including power and gas demand response is developed by converting multiple energy sources into one another and changing the energy consumption pattern of customer under a given period. Whilst, the customer satisfaction is also taken into account in IDR model. Moreover, a credibility theory-based risk measure is presented for quantitatively assessing the randomness and fuzziness characteristics of uncertain wind power, and then we explore the balance between the operation cost and risk of microgrid with wind power integration. Case studies are undertaken on the CHPG microgrids considering IDR and uncertainty. Simulation results indicate that the proposed coordinated scheduling model and the optimal operation method are universal and effective over the entire multi-energy dispatching horizon.

Implementation of cost benefit analysis of vehicle to grid coupled real Micro-Grid by considering battery energy wear: Practical study case

The proposed research represents a spin-off of the Malta College of Arts, Science and Technology (MCAST) Micro-Grid (MG) project. Particularly, economic impact of Electric Vehicles (EV) integration into the MG is investigated in this paper. The MCAST MG consists of photovoltaic generation unit, a diesel generator and a battery storage system. In this paper, a Vehicle-to grid (V2G) concept is considered where utilities can profit from controlled energy trading operations according to EVs availability. EVs are categorized under different profiles considering energy and time availability of owners typical work hours. V2G energy cost is estimated based on battery energy wear due V2G extra cycling and refunded to EVs owners. As most of developed V2G studies don’t consider real world input data or/and EV battery aging cost in system modeling and evaluation, the present paper presents a reliable study as it considers a real life MG with in field measurement input data and appropriate battery degradation model. The adopted model represents a linear approximation with a minimum error value to make a suitable tradeoff of computational complexity and accuracy of obtained results. Economic assessment of the system according to the proposed energy management is performed, where results indicate that the V2G system assisted the MG operation during high electricity price period and achieved economic profit to EVs owners. According to numerical results, V2G energy trading achieved 29.90 EUR of gross selling revenues with only 4.46 EUR as battery degradation cost which makes a 16.41% average cost reduction of daily MG operation cost.

Two-level Energy Management Model of Grid-connected Micro-Grid Community

In order to reduce the operation and maintenance costs of a single micro grid and reduce the adverse effects caused by unnecessary energy interaction between the micro grid and the main grid while improving the overall economic benefits of the micro grid community, this paper proposes a two-level energy management model with the optimization goal of maximizing the social welfare of the micro grid community and minimizing the total electricity cost of a single micro grid. The lower-level model optimizes the output of each equipment unit in the system and the exchange power between the system and the external grid with the goal of minimizing the operating cost of each microgrid. The upper- level model optimizes the goal of maximizing the social welfare of the microgrid. Taking a microgrid community with four microgrids as an example, the simulation analysis shows that the proposed optimization model is beneficial to reduce the operating cost of a single microgrid, improve the overall revenue of the microgrid community, and reduce the power interaction pressure on the main grid.

Optimal placement of battery swap stations in microgrids with micro pumped hydro storage systems, photovoltaic, wind and geothermal distributed generators

The penetration of electric vehicles (EVs) in vehicle markets is increasing; however long charging time in battery charging stations is an obstacle for larger adoption of EVs. In order to address this problem, battery swap stations (BSSs) have been introduced to exchange near-empty EV batteries with fully charged batteries. Refilling an EV in BSS takes only a few minutes. With decentralization of power systems, BSSs are typically connected to the microgrid (MG) in their neighborhood. Although the location of BSS in MG affects MG operation cost, to the best knowledge of the author, optimal placement of BSS has not been done from the perspective of MG. Therefore, in this paper, the objective is to find optimal location of BSSs in a MG with micro pumped hydro storage (PHS), photovoltaic, wind and geothermal units, while reactive power dispatch and all network constraints are considered by AC optimal power flow. The effect of BSS capacity and maximum charging/discharging power, BSS to MG link capacity, PHS capacity and maximum power of PHS unit on MG operation and optimal BSS location are investigated. DICOPT solver in general algebraic mathematical system (GAMS) is used to solve the formulated mixed-integer nonlinear optimisation problem.

Dynamic environmental‐economic load dispatch in grid‐connected microgrids with demand response programs considering the uncertainties of demand, renewable generation and market price

AbstractMicrogrids (MGs) as a key building block of smart grids have been emerged to address the proliferation of distributed energy resources. In grid‐connected MGs, dynamic economic load dispatch (DELD) module determines optimal schedule of distributed energy resources and adjustable loads and power to be exchanged with upstream grid, while all operational constraints of the MG are respected. DELD in MGs represents a constrained optimization problem with uncertain input data, as the forecasts of demand, renewable generation and market price are uncertain. In this research, particle swarm optimization (PSO) as a bio‐inspired optimization algorithm is used to solve DELD in grid‐connected MGs, while demand response program is integrated into MG and the uncertainties of demand, renewable power generation and market price are dealt with two‐point estimate method (TPEM). Load curtailment as a demand response program is used for reducing operation cost of microgrids. The performance of PSO is compared with two optimization algorithms including grey wolf optimization and backtracking search algorithm. As per the results, at times with low grid power price, microgrid imports power from upstream grid and at times with high power price it exports power to the upstream grid. The results show that the integration of demand response has significantly reduced the operation cost of the microgrid. The effect of change in maximum curtailable power on the operation cost of the MG has been investigated.

A Risk-Averse Hybrid Approach for Optimal Participation of Power-to-Hydrogen Technology-Based Multi-Energy Microgrid in Multi-Energy Markets

Global consensus on energy economic and environmental issues, as well as increasing penetration of renewable resources, has created new challenges for researchers to explore more financial-effective, environment-friendly, reliable, and secure energy systems. To this end, this paper focuses on combined cooling, heating, and power microgrid to alleviate these issues. In this regard, a multi-carrier energy storage system composed of thermal storage system, ice storage system, and hydrogen storage system are integrated into the proposed system to benefit from their techno-economic advantages. The proposed combined cooling, heating, and power microgrid not only participates in power, gas, and thermal market to supply power, thermal, and cooling demands but also can participate in the hydrogen market using a novel power-to-hydrogen technology utilized in the hydrogen storage system to increase the entire system efficiency. Moreover, a multi-energy demand response model is applied as a new concept of demand response on both electrical and thermal loads, which provides more options for multi-energy end-users in energy management policies. Additionally, a novel hybrid robust-stochastic approach is proposed to deal with the uncertainty of wind speed and electricity price fluctuations, which enables the operator to use the advantages of both scenario-based stochastic and robust optimization methods simultaneously to handle such uncertainties. The scenario-based stochastic technique is used to handle the uncertainty of wind speed while the robust optimization method is also considered to manage the uncertainty associated with electricity price in a conservative environment. The main objective of the proposed model is to minimize the operation cost of multi-energy microgrid, which is formulated as a mixed-integer linear programming problem. Finally, to verify the effectiveness of the proposed methodology, a case study and numerical results are provided. Obtained results shows that utilizing hydrogen storage and multi-energy demand response can reduce the system operation cost up to 5% for the studied test system.

Optimal Chance-Constrained Scheduling of Reconfigurable Microgrids Considering Islanding Operation Constraints

Microgrid concept is one of the suitable strategies for increasing resilience and preventing load curtailment, especially in emergency conditions. Operation in islanded mode is one of the unique features of microgrids that can provide numerous benefits for both consumers and energy producers. Unlike the conventional distribution networks, reconfigurable microgrids enable the reconfiguration process to achieve optimal structure. In this article, a new optimal strategy for scheduling of reconfigurable microgrids considering islanding capability constraints is presented. To demonstrate the successful islanding operation, the islanding capability is considered as a probability of islanding operation (PIO) index which shows the probability, that the microgrid has adequate level of spinning reserve to meet the local load. Taking into account the forecast errors of generated power by renewable energy resources (PV and wind) as well as load demand, the 13-interval approximation is used for the simplification of nonlinearity of PIO. The scheduling of reconfigurable microgrid with islanding operation constraints is formulated as a chance-constrained goal optimization problem, where the objective is defined as minimizing the total operation cost of microgrid in terms of fuel cost, reliability cost, cost of purchasing power from the mains, and switching cost. The proposed method is implemented on a 10-bus radial reconfigurable microgrid test system with photovoltaic (PV) panels, wind turbines, battery, and microturbines, with different levels of PIO. The numerical results show the effectiveness of the proposed scheduling method.

Energy management in microgrids with battery swap stations and var compensators

The scarcity and price volatility of fossil fuels as well as environmental concerns has motivated the replacement of fossil fuel-powered vehicles by electric vehicles (EVs). Long charging time in battery charging stations is a serious barrier for large-scale adoption of EVs, so battery swap stations (BSSs) were developed wherein the near-empty batteries are exchanged with fully charged batteries and EV refilling is done in only a couple of minutes. Nowadays, BSSs are typically connected to a microgrid (MG) in their neighborhood. In this research, the optimal scheduling of MG resources and BSS is done for a grid-connected MG with dispatchable, photovoltaic and wind distributed generation (DG) units and operation cost of MG is minimised. It is assumed that the BSS services Tesla 3 EVs with 75 kWh batteries and a driving range of 496 km. A var compensator (VC) is connected to the MG that can purchase reactive power from var compensator. AC optimal power flow is done for the MG, while all network constraints, power loss and reactive power dispatch are taken into account and the cost of provision of reactive power is included in the operation cost of the MG. Generalized reduced-gradient (GRG) algorithm is used for the optimisation process. The effects of VC, optimal BSS scheduling and reactive power costs on active/reactive power dispatch and MG operation cost are duly investigated.

A microgrids energy management model based on multi-agent system using adaptive weight and chaotic search particle swarm optimization considering demand response

With the deepening of China’s low-carbon energy transformation, microgrids are an essential means to promote the consumption of renewable energy. Therefore, improving the operational efficiency of microgrids is the key to promote the development of renewable energy. This paper establishes a three-layer Multi-Agent system model considering the energy storage system and power-heat load demand response based on the actual situation of China to solve the problem of microgrids energy management. In order to verify the effect of the energy storage system and demand response in microgrids, this paper designs three simulation cases, namely the underlying case, energy storage case and demand response case. In order to prove the efficiency of the proposed method, this paper applies the proposed method to solve three cases and compare the result with other meta-heuristic algorithms. The comparison results show that: (1) Multi-Agent system model can realize the collaborative optimization of ‘source, grid, load, and storage.’ (2) The introduction of the energy storage system and demand response in microgrids can stabilize the output of renewable energy units, promote renewable energy consumption and reduce the overall operating cost of microgrids. (3) The proposed particle swarm optimization can effectively reduce the cost and the number of iterations.

Integrated active/reactive power scheduling of interdependent microgrid and EV fleets based on stochastic multi‐objective normalised normal constraint

This study proposes an integrated framework for coordinated optimisation of the interdependent microgrid (MG) and electric vehicle (EV) fleet entities using the normalised normal constraint approach. By considering the active/reactive power management option of the bidirectional charger enabled EVs in the proposed model, the authors investigate the effectiveness of EV's integration in the presence of the techno-economical objective functions. This work concentrates on the trade-off analysis of two conflicting objectives, including the economic objective of the MG's operation cost minimisation and the technical objective of the MG's voltage deviation. Besides, they consider several uncertainty sources, e.g. wind, EV and solar panel (PV) power provision, as well as market price fluctuations in the proposed model affecting the aforementioned techno-economic trade-off solution. The proposed model is a stochastic multi-objective mixed-integer non-linear programming problem where the authors apply the designed integrated framework on a modified IEEE 18-bus test case in GAMS software. Through numerical results, they demonstrate MG optimal operation changes due to different MGO priorities and study the positive effects of EVs integrated energy management on the bi-objective operation.

Multi-objective economic dispatch of a microgrid considering electric vehicle and transferable load

In order to investigate the impact of electric vehicles’ charging-discharging behaviour and demand side response resources on the economic operation of photovoltaic grid-connected microgrid system, a multi-objective model of microgrid economic dispatching with electric vehicles, transferable load and other distributed generations (diesel engines and energy storage unit) is proposed in this paper. The model takes the comprehensive operating cost of microgrid, the utilization rate of photovoltaic energy and the power fluctuation between the microgrid and main grid as objectives. Moreover, four different cases of microgrid economic dispatch considering electric vehicles and transferable load are put forward, which are electric vehicles’ orderly charging and discharging and transferable load participating in demand response in Case 1, electric vehicles’ charging randomly and the transferable load participating in demand response in Case 2, electric vehicles orderly charging and discharging and transferable load not participating in demand response in Case 3, electric vehicles’ charging randomly and the transferable load not participating in the demand response in Case 4. Multi-objective Seeker Optimization Algorithm and the method of fuzzy membership function are applied in this study to obtain the optimal results. The simulation analysis shows that the orderly charging-discharging behaviour of electric vehicles and the participation of transferable load can effectively improve the economic costs, efficiency and security of microgrid economic operation.