Microgrid Planning Research Articles

Scenario‐based multi‐objective optimisation with loadability in islanded microgrids considering load and renewable generation uncertainties

Operation of microgrids in islanded mode either by intention or by involuntary action is of increasing concern nowadays. Optimal operation and control of such islanded microgrids considering various objectives are crucial for effective planning problem. This work proposes a new methodology for optimal operation of islanded microgrids considering economic and emission objectives together with loadability in droop-regulated islanded microgrid. Loadability being one of dominant aspects to be considered for effective microgrid planning and operation to ensure increased voltage-stability margin in the entire due course of operation. In conjunction with that islanded microgrid operational constraints and uncertainty in various system parameters need to be considered to interpret real-time operation of the microgrid. In the light of above, a multi-objective optimisation problem in droop-regulated islanded microgrid is formulated with economic–emission–loadability objectives by considering uncertainties in load demand and renewable generation along with system constraints. The formulated problem is solved using multi-objective antlion optimiser algorithm and validated on the test system. The performance of the proposed approach is compared with other optimisation algorithms to show its effectiveness. The importance of considering loadability along with economic–emission objectives to achieve compromised solution resulted in ensuring better operational planning of droop-regulated islanded microgrids.

Optimal Planning and Operational Management of Open-Market Community Microgrids

In this article, a new business model comprising multiple stakeholders is proposed to develop a frame for future flexible retail energy market in community microgrids. The microgrid comprises multiple and different distributed energy resources (DERs) such as renewable generation units, battery energy storage systems (BESSs), and micro diesel engines (MDE), to minimize daily operational costs of the system. To solve the defined complex optimization model, some operational strategies are proposed and then genetic algorithm is adopted to determine the hourly optimal power dispatch. The case study shows that the proposed model minimizes the daily operating cost of the community system effectively.

Distributed energy resource and network expansion planning of a CCHP based active microgrid considering demand response programs

This paper addresses the network expansion planning of an active microgrid that utilizes Distributed Energy Resources (DERs). The microgrid uses Combined Cooling, Heating and Power (CCHP) systems with their heating and cooling network. The proposed method uses a bi-level iterative optimization algorithm for optimal expansion and operational planning of the microgrid that consists of different zones, and each zone can transact electricity with the upward utility. The transaction of electricity with the upward utility can be performed based on demand response programs that consist of the time-of-use program and/or direct load control. DERs are CHPs, small wind turbines, photovoltaic systems, electric and cooling storage, gas fired boilers and absorption and compression chillers are used to supply different zones' electrical, heating, and cooling loads. The proposed model minimizes the system's investment, operation, interruption and environmental costs; meanwhile, it maximizes electricity export revenues and the reliability of the system. The proposed method is applied to a real building complex and five different scenarios are considered to evaluate the impact of different energy supply configurations and operational paradigm on the investment and operational costs. The effectiveness of the introduced algorithm has been assessed. The implementation of the proposed algorithm reduces the aggregated investment and operational costs of the test system in about 54.7% with respect to the custom expansion planning method.

Optimal operational planning of scalable DC microgrid with demand response, islanding, and battery degradation cost considerations

With the advancements in power electronic devices, the increasing use of DC loads, DC renewable generation sources and battery storage systems, and no reactive power and frequency stability issues, DC microgrids are increasingly gaining attention in both academia and industry. In this paper, a grid-connected DC microgrid is considered, which consists of a PV system and a Li-ion battery. DC microgrids optimal operation requires battery degradation cost modeling and demand response incentive for active consumers’ participation to be addressed in detail. Therefore, a practical degradation cost model for a Li-ion battery is developed to optimize battery scheduling and achieve its realistic operational cost. Apart from energy price, scheduled islanding responsive demand response incentive is also introduced to encourage customers to shift load during scheduled grid-tie line maintenance. Levelized cost of energy of PV system is calculated for both hot and cold climate regions. Optimal operation of DC microgrid cannot be achieved without considering nodal voltages and system losses. Hence, network constraints are also included in the proposed model. Extensive numerical simulations are carried out to prove the effectiveness of the proposed approach. The achieved results would aid in DC microgrids adoption planning that would expectedly replace traditional AC grids in the future.

Optimal Planning of On-Grid Hybrid Microgrid for Remote Island Using HOMER Software, Kish in Iran

HOMER software functions as a tool for modeling and optimization of an energy generation micropower system based on renewable technologies. In this paper for the first time the monthly real load data have been used in HOMER to design a renewable-based microgrid in grid-connected mode for Kish Island, Iran. The calculations were performed in a way that the designed system could supply the load demand of the studied area with the lowest cost, least pollution, and highest reliability. To overcome the intermittency of renewable energy sources such as wind and solar, a combination of these sources in a hybrid system and installation of battery storage systems were considered. The solar radiation and wind speed data required by the software were obtained from the country’s meteorology and NASA website and used in the software. The analysis results of four scenarios, including national grid/diesel generator, national grid/diesel generator/solar cell, national grid/diesel generator/wind turbine, and national grid/diesel generator/solar cell/wind turbine, showed the prices per kWh of $0.483, $0.505, $0.472, $0.537, respectively. In these scenarios, the share of renewable energies was 0%, 8%, 11%, and 26%, respectively. The highest amount of electricity sold to the national grid was 1597095 kWh/y for the fourth scenario which had also the lowest rate of CO2 emissions by 4128650 kg/y.

A comprehensive review of energy management and planning of islanded microgrids: Part 1 — optimization formulations

This survey paper provides a critical overview of optimization formulations for planning and operation of islanded microgrids, including optimization objectives, constraints, and control variables. The optimization approaches reviewed address methods both for increasing the resiliency of advanced distribution systems and electrification of remote communities. This paper examines over 120 individual optimization studies and discovers that all optimizations studies of islanded microgrids are based on formulations selecting a combination of 16 possible objective functions, 14 constraints, and 13 control variables. Each of the objectives, constraints, and variables are discussed exhaustively both from the perspective of their importance to islanded microgrids and chronological trends in their popularity.

Optimal Planning for Partially Self-Sufficient Microgrid With Limited Annual Electricity Exchange With Distribution Grid

Existing research on on-grid microgrid planning is carried out with a free trading assumption and without considering the limitation of annual electricity exchange. Therefore, the existing planning and sizing scheme may be not viable for the application of partially self-sufficient microgrid (PSSMG) with a limited amount of electricity exchange. To address this issue, a new planning method for PSSMG is proposed in this paper considering the limited annual electricity exchanging amount (AEEA). The sizing model and energy management are linearized and simultaneously integrated into one model, which could be solved in polynomial time. In order to effectively reduce the number of variables of a full year horizon and to cope with the uncertainty both of DGs and loads, a data-driven method based on K-means algorithm is utilized to choose a set of typical days that are representative of historical data of one full year. Finally, the validity and effectiveness of the proposed model are verified by comparative numerical simulations, and the sensitivity of limited AEEA to the planning scheme is analyzed.

State of the Art in Research on Optimum Design, Reliability and Control of Renewable Energy Microgrids

This paper has presented a comprehensive review in the area of microgrid from the design to implementation. The aim is to evaluate the current status, problems and research efforts toward realising functional microgrids in the power system. The expectations about microgrid are many; therefore the study is divided into three main sections. Recent advancements in the wind energy, solar energy and their future prediction are summarised. States of arts in optimum design of renewable energy microgrid are also investigated. In addition, critical literature review in the reliability analysis of microgrids consisting of renewable energy sources is also reported. Control of microgrids consisting renewable energy sources have been presented. Some examples of existing microgrids across the globe are critically reviewed. The work therefore recommends that energy planners and all stakeholders should consider environmental and regional difference in microgrids planning. Finally, future research areas and directions in these areas are highlighted.

A mathematical formulation of the joint economic and emission dispatch problem of a renewable energy-assisted prosumer microgrid

Operational planning of prosumer microgrids with solar and wind energy sources is quite a complex task considering the intermittency of these sources and energy import/export from prosumers. Reserve capacities which can be reliably provided by dispatchable sources like conventional generators (CGs) may be needed to ensure reliability of the grid. However, these sources produce emissions which have adverse effects on the environment. Hence, emission curtailment should be incorporated in the operational planning of microgrids with these generators. In this paper, a mathematical formulation for the joint economic and emission dispatch of a renewable energy-assisted prosumer microgrid is presented and solved using the CPLEX Solver in Advanced Interactive Multidimensional Modelling System (AIMMS). A modified microgrid test system is used as a case study in this work. Results show that incorporating an emission function in the objective of the operational dispatch formulation not only reduces emissions, but could be of advantage to customers as larger capacities of their behind-the-meter resources get the chance to provide grid ancillary services; however, it also puts a restriction on the profit that could be made from selling energy to the main grid during periods when energy prices are high.

Scenario-based investment planning of isolated multi-energy microgrids considering electricity, heating and cooling demand

Multi-energy microgrids provide a flexible solution for the utilization of the distributed energy resources in order to meet the electrical, heating and cooling energy demands in the off-grid communities. However, the planning of the multi-energy microgrids is a non-trivial problem due to the complex energy flows between the sources and the loads pertaining to the electrical, heating and cooling energy, along with the intermittency of the renewable distributed generation. This work proposes a scenario-based stochastic multi-energy microgrid investment planning model that aims to minimize the investment and operation costs as well as the Carbon dioxide emissions by determining the optimal distributed energy resource mix, siting and sizing in the isolated microgrids. The proposed planning model employs the power flow and heat transfer equations to explicitly model the energy flows between electrical, heating and cooling energy sources and loads. Moreover, an uncertainty matrix is employed to tackle the operational uncertainties associated with the wind and photovoltaic generation, and the electrical, heating and cooling loads. The uncertainty matrix is modeled using the heuristic moment matching method that effectively captures the stochastic moments and correlation among the historical scenarios. The numerical results obtained from the case-study in the 19-bus microgrid test system confirm that the proposed methodology provides significant reductions in the investment and operation costs as well as the Carbon dioxide emissions. Finally, the superiority of the proposed planning solution is also validated using the deterministic planning solution as the comparison benchmark.

Flexible network planning of autonomy microgrid

In a microgrid, a rational network is necessary to improve the economy, reliability, adaptability, security, and coordination of the supply with the load demand. A flexible network optimal planning model of autonomy microgrid is proposed. Several uncertainties including the output power of distributed generation and load power are considered and each uncertainty factor is divided into several typical scenarios. The probability of each scenario is calculated by asymptotically optimal scenario analysis. The annual investment cost, the fault outage cost expectation, the annual cost regret value expectation and penalty function, the violating electrical constraints degree, and the source-network-load equilibrium degree are applied to represent the flexibility of the planning model. Allocation of energy storage system capacity is considered in the network planning model, which can reduce the negative effects on the microgrid in extreme scenarios. An energy management strategy is constructed to coordinate the distribution of source and load. The tree structure encoding is employed to ensure the connectivity of the network. Dynamic Pareto set-based particle swarm optimisation is adopted for the solution of the network planning model. Finally, the calculation results of planning schemes are demonstrated by radar chart, and the optimal one is selected by its comprehensive evaluation value.

Resilient Off-Grid Microgrids: Capacity Planning and N-1 Security

Over the past century the electric power industry has evolved to support the delivery of power over long distances with highly interconnected transmission systems. Despite this evolution, some remote communities are not connected to these systems. These communities rely on small, disconnected distribution systems, i.e., microgrids to deliver power. However, as microgrids often are not held to the same reliability standards as transmission grids, remote communities can be at risk for extended blackouts. To address this issue, we develop an optimization model and an algorithm for capacity planning and operations of microgrids that include ${N}$ -1 security and other practical modeling features like ac power flow physics, component efficiencies, and thermal limits. We demonstrate the computational effectiveness of our approach on two test systems; a modified version of the IEEE 13 node test feeder and a model of a distribution system in a remote community in Alaska.

Demand response based day‐ahead scheduling and battery sizing in microgrid management in rural areas

A considerable number of people living in rural areas, especially in developing countries have no or very limited access to electricity. Usually, connecting such areas to the main grid is economically or technically infeasible and standalone microgrid concept is used as the solution. However, even in such microgrids, the fuel costs are normally much higher compared to the urban areas due to the lack of infrastructure. Nowadays, renewable sources of energy are much cheaper than before and economically viable. If they are used efficiently with the help of storage systems and intelligent management of the consumption, a cheaper and sustainable solution can be achieved. In this study, the authors propose comparatively more realistic models for appliances' consumption in rural areas as well as new mathematical optimisation problem for optimal management with day-ahead scheduling and planning of rural microgrids. They also propose a new model to capture the inefficiency of the battery in microgrid management and investigate the optimum battery and renewable generation to run microgrid solely on renewable energy. To validate the proposed model and understand the importance of demand response and batteries in operation and capital investment costs of such systems, the authors design and simulate different scenarios and discuss the simulation results.

Sustainable planning of hybrid microgrid towards minimizing environmental pollution, operational cost and frequency fluctuations

Microgrids mainly use conventional and renewable energy resources at the same time. Conventional energy resources produce environmental pollution and need high cost for operation. In recent years, penetration of renewable resources such as photovoltaic and wind turbine has been rapidly grown in microgrids. Reduction of power losses and pollution are the main advantages of integrating renewable resources into networks. But, the renewable energy resources comprise low inertia and stability of the network integrated with such units is low. As a result, the environmental pollution and stability of microgrid are considered as the main problems and a new modeling of microgrid energy management is proposed by this paper to tackle such drawbacks. In this regard, environmental pollution is reduced by including hydrogen gas station and carbon capture-storage system. As well, the virtual synchronous generator is used to provide sufficient inertia and improving transient stability. The uncertain parameters are incorporated in the planning and stochastic programming is applied to tackle such uncertainties. Problem is mathematically expressed as a stochastic mixed integer linear programming and solved by the augmented Epsilon-constraint method. Finally, a comprehensive sensitivity analysis is carried out to evaluate the results. Based on the simulation results, by installing carbon capture-storage system, operational cost of microgrid is reduced from 64.998 $ to 56.043 $ and 1791.75 kg of carbon dioxide is stored. The revenue equal to 24 $ in one day is achieved by H2 station without any pollution. The stability of microgrid is also significantly improved by installing virtual synchronous generator. The results demonstrate the viability and effectiveness of the proposed method to minimize environmental pollution, operation cost and frequency fluctuations in microgrid energy management.

A robust energy and reserve dispatch model for prosumer microgrids incorporating demand response aggregators

The uncertainty introduced by intermittent renewable energy generation and prosumer energy imports makes operational planning of renewable energy-assisted prosumer microgrids challenging. This is due to the difficulty in obtaining accurate forecasts of the energy expected from these renewable energy sources and prosumers. Operators of such microgrids therefore require additional grid-balancing tools to maintain power supply and demand balance during grid operation. In this paper, the impact of demand response aggregators (DRAs) in a prosumer microgrid is investigated. This is achieved by developing and solving a deterministic mathematical formulation for the operational planning of the grid. Also, taking a cue from CAISO's proposed tariff revision which allows the state-of-charge of non-generator resources (like storage units) to be submitted as a bid parameter in the day-ahead market and permits scheduling coordinators of these resources to self-manage their energy limits and state-of-charge, the proposed formulation permits prosumers to submit the battery energy content as a bid parameter and self-manage their battery energy limits. Furthermore, a robust counterpart of the model is developed. Both formulations are constrained mixed integer optimization problems which are solved using the CPLEX solver in the Advanced Interactive Multidimensional Modelling System environment. The results obtained from tests carried out on a hypothetical prosumer microgrid show that the operating cost of the microgrid reduces in the presence of DRAs. In addition, the storage facility owner may benefit from self-managing its energy limits, but this may cut the amount of grid-balancing resource available to the microgrid operator, thereby increasing the operating cost of the microgrid.

Very short-term maximum Lyapunov exponent forecasting tool for distributed photovoltaic output

Photovoltaic (PV) power generation varies randomly and intermittently with respect to the weather. For a microgrid with PV sources, this fluctuation not only affects the necessary configuration of the energy-storage capacity chosen in microgrid planning and design but also influences the microgrid operation. Consequently, accurately forecasting the PV output is crucial. For the operation of a PV-dominated microgrid, a new method for very short-term (VST) forecasting based on the maximum Lyapunov exponent (MLE) is proposed. First, historical power-generation data are divided into three weather conditions: sunny, cloudy, and rainy days. Then, a PV output series for the different weather conditions is constructed, and the chaotic characteristic is verified by reconstructing an attractor graph and calculating the MLE. Finally, using the MLE method, the PV generation under different historical weather conditions is forecasted. The raw output time series are measured data from a demonstration system installed on the rooftop of Building 6 at Hangzhou Dianzi University, China. The forecasting accuracy is evaluated using several statistical metrics and compared with that of forecasts obtained via the widely used auto-regression approach. Comparing the forecasts indicates that the MLE-based method is statistically but not universally more accurate for VST forecasting.

Estimation of Load Pattern for Optimal Planning of Stand-Alone Microgrid Networks

This paper proposes a method for estimating the load pattern for optimal planning of stand-alone renewable microgrids and verifies when the basic data for microgrid design are limited. To estimate a proper load pattern for optimal microgrid design when the data obtained in advance are insufficient, the least squares method is used to compare the similarity of annual power consumption between the subject area and eight islands in Korea whose actual load patterns were previously obtained. Similarity is compared in terms of annual (every month), seasonal, bi-monthly, and monthly averages. To verify the validity of the proposed estimation method, the applied proposed estimation method is used for two islands that have already installed a microgrid consisting of photovoltaic, wind power, energy storage systems, and diesel generators. In comparing the actual data from the two islands, the costs of electricity in terms of microgrid operations show improvements of 37.2% and 29.8%, respectively.

Research on Distributed Power Capacity and Site Optimization Planning of AC/DC Hybrid Micrograms Considering Line Factors

With the rapid development of AC/DC hybrid microgrids and the widespread use of distributed power resources, planning strategies for microgrids with high-density distributed power generation have become an urgent problem. Because current research on microgrid planning has not considered line factors, this paper analyses the planning of an AC/DC hybrid microgrid based on an AC microgrid. The capacity and siting of the distributed power resources are optimized, taking into account the influence of the line investment cost and the interactive power upper limit on the planning results. In the proposed model, the objective is aimed at minimizing the sum of investment cost, load-loss economic cost, and system losses, taking into consideration power balance constraints and feeder number constraints. The commercial solver CPLEX is applied to attain the optimal distributed power capacity and site. The theoretical results are verified by an actual system.

Optimal design and development of PV-wind-battery based nano-grid system: A field-on-laboratory demonstration

The present paper has disseminated the design approach, project implementation, and economics of a nano-grid system. The deployment of the system is envisioned to acculturate the renewable technology into Indian society by field-on-laboratory demonstration (FOLD) and “bridge the gaps between research, development, and implementation.” The system consists of a solar photovoltaic (PV) (2.4 kWp), a wind turbine (3.2 kWp), and a battery bank (400 Ah). Initially, a prefeasibility study is conducted using the well-established HOMER (hybrid optimization model for electric renewable) software developed by the National Renewable Energy Laboratory (NREL), USA. The feasibility study indicates that the optimal capacity for the nano-grid system consists of a 2.16 kWp solar PV, a 3 kWp wind turbine, a 1.44 kW inverter, and a 24 kWh battery bank. The total net present cost (TNPC) and cost of energy (COE) of the system are US$20789.85 and US$0.673/kWh, respectively. However, the hybrid system consisting of a 2.4 kWp of solar PV, a 3.2 kWp of wind turbine, a 3 kVA of inverter, and a 400 Ah of battery bank has been installed due to unavailability of system components of desired values and to enhance the reliability of the system. The TNPC and COE of the system installed are found to be US$20073.63 and US$0.635/kWh, respectively and both costs are largely influenced by battery cost. Besides, this paper has illustrated the installation details of each component as well as of the system. Moreover, it has discussed the detailed cost breakup of the system. Furthermore, the performance of the system has been investigated and validated with the simulation results. It is observed that the power generated from the PV system is quite significant and is almost uniform over the year. Contrary to this, a trivial wind velocity prevails over the year apart from the month of April, May, and June, so does the power yield. This research demonstration provides a pathway for future planning of scaled-up hybrid energy systems or microgrid in this region of India or regions of similar topography.

Selecting the Optimal Micro-Grid Planning Program Using a Novel Multi-Criteria Decision Making Model Based on Grey Cumulative Prospect Theory

As useful supplements and effective support for large-scale electric power networks, micro-grid systems are the development tendency of future electric power systems. The planning performance of a micro-grid not only affects its security, reliability and economy, but also has a profound influence on the stable operation of large-scale electric power networks with the increasing penetration of micro-grids. Hence, studies related to micro-grid planning program evaluation are of great significance. This paper established a novel multi-criteria decision making (MCDM) model combining the best-worst method (BWM), the entropy weighting approach, and grey cumulative prospect theory for optimum selection of micro-grid planning programs. Firstly, an evaluation index system containing 18 sub-criteria was built from the perspectives of economy, electricity supply reliability and environmental protection. Secondly, the weights of sub-criteria were calculated integrating the subjective weights judged by the BWM and the objective weights computed by the entropy weighting method. Then, the cumulative prospect theory (CPT) combined with grey theory was employed to select the optimal micro-grid planning program. The empirical result indicates that the program with 100 kWp photovoltaic power generation unit, 200 kW wind power generation unit and 600 kWh NaS battery energy storage system is the optimal micro-grid planning program. To verify the robustness of obtained result, a sensitivity analysis related to values change of parameters under different risk preferences was conducted, and the result indicates that the selected optimal micro-grid planning program will not be influenced by various risk preferences of decision makers (DMs) and investors. The novel MCDM proposed in this paper is applicable and feasible in the micro-grid planning programs evaluation and selection.